Download The Effect of Government Policy on China`s Stock Market

The Effect of Government Policy on China’s Stock Market
DISSERTATION
of the University of St. Gallen,
Graduate School of Business Administration,
Economics, Law and Social Sciences (HSG)
to obtain the title of
Doctor Oeconomiae
Submitted by
Liya Wang
from
China
Approved on the application of
Prof. Dr. Li Choy Chong
and
Prof. Dr. Klaus Spremann
Dissertation no. 3716
Gutenberg AG, Feldkirchstrasse 13, FL - 9494 Schaan, 2010
1
The University of St. Gallen, Graduate School of Business Administration,
Economics, Law and Social Sciences (HSG) hereby consents to the
printing of the present dissertation, without hereby expressing any
opinion on the views herein expressed.
St. Gallen, October 19, 2009
The President:
Prof. Ernst Mohr, PhD
2
Table of Contents
Abstract
5
Introduction
7
Chapter One
Literature Review
12
Chapter Two
Monetary Policy
37
Literature and Methodology
40
Money Supply
45
Interest Rate
66
Bank
Chapter Three
Chapter Four
Reserve
Ratio
and
Open
Market
Operations
73
Fiscal Policy
91
Government Spending
95
Government Bond
109
Taxation Policy
121
Overview of Policies
136
Methodology
137
Summary of Major Fluctuations and Policy
Changes
140
Game between Government and Investor
154
3
Economic Growth and Stock Market
157
Event Study
169
Stock Reform
179
Multi-Level & Functional Financial Market
196
Conclusion
227
Reference
230
Curriculum Vitae
242
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Abstract
China is moving from a planned economy toward a market-oriented
financial system as it opens its economy to foreign competition in the last
decade. Now facing the global financial crisis, the government is turning
the export-oriented strategy which powered remarkable growth during the
first 20-year of China’s growth story to a greater reliance on inner
dynamism. This paper examines the effect of various government policies
China has implemented during the 20-year development of its stock
market. I used various empirical data collected from the government
statistics bureaus, the central bank and research institutions to exam
whether monetary policy, fiscal policy and some specific capital market
related policies have direct or indirect effects on the stock market and
whether their impact is positive for China’s development. Based on
descriptive, regression analysis, Granger Causality, VAR model and case
studies, the results suggest government’s policies have had significant
impact on the stock market. I conclude that the central government has
made the necessary efforts and posted positive influences on the
development of China’s stock market, learning by doing, perfecting the
framework during the transition to a market economy, although there
have been several failed attempts along the way.
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Zusammenfassung
China bewegte sich während des letzten Jahrzehnts weg von der
Planwirtschaft hin zu einem marktorientierten Finanzsystem. Aufgrund
der globalen Finanzkrise änderte die Regierung die exportorientierte
Strategie zugusten der inneren Dynamik des Landes. Die vorliegende
Arbeit prüfte die Auswirkungen mehrerer Richtlinien der Regierung
Chinas, welche bei der Entwicklung des Aktienmarktes während den
letzten 20 Jahren erlassen wurden. Die empirischen Datensammlungen
wurden verwendet, um den direkten oder indirekten Einfluss der
Geldpolitik, Fiskalpolitik und andere spezifische kapitalmarktabhängigen
Reglementierungen auf den Aktienmarkt aufzuzeigen, sowie auch ob sich
diese Einflüsse positiv auf die chinesische Entwicklung ausgewirkt haben.
Basierend auf den Resultaten von beschreibenden Regressionsanalysen,
Granger Causality, VAR Modellen und Fallstudien waren die Einflüsse
der Regierung auf den Aktienmarkt signifikant. Daraus schliesse ich, dass
die Zentralregierung die nötigen Schritte unternommen hat, um die
Entwicklung des chinesischen Aktienmarktes positiv zu beinflussen.
Dabei ist die Gestaltung der Rahmenbedingungen während dem
Übergang zur Marktwirtschaft ein konstanter Lernprozess, bei dem auch
fehlgeschlagene Ansätze den Weg säumen.
6
Introduction
The regulator presides over the financial market, holding a mission
to maintain fairness and efficiency and to facilitate an orderly
development. Stock markets are sensitive to information. Formerly, stock
markets were less transparent and less regulated. The government could
directly interfere using diverse monetary or fiscal tools or other
regulations. Sometimes the government could even be manipulated by
external commercial influences1. As the markets liberalize, government
leaves more room to the market and relies largely on the country’s legal
framework. The disagreement and debates between government
intervention and economic freedom has been the core line of western
economic development ever since Adam Smith’s ‘The Wealth of
Nations’.
Early this year, the renowned economist Paul A. Sameulson pointed
out that it is utterly mistaken to believe ‘a market system can regulate
itself’ 2 . The supervisory role of the government has been sharply
1
The most famous example is the South Sea bubble of Britain in 1720, when the government
promulgated law to protect the monopoly of the South Sea Company.
2
See the interview of Paul A. Sameulson by NPQ in Jan 2009, who suggests ‘Don't expect recovery
before 2012’.
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curtailed in years especially in western economies, fed by the belief in the
self-regulatory nature of the market economy. Analytically based lessons
from the present crisis shall focus on revisions of the macroeconomic and
regulatory frameworks to reduce the risks of dangerous booms and
resulting busts. Thus people have shifted the focus back to the pioneering
idea Adam Smith recognized 250 years ago – limitations of the market.
Despite Smith’s detailed analysis of the working of a market economy, it
would be hard to carve out from his works any theory of the sufficiency
of the market economy. Keynesian economics again becomes the center
of discussion when the conventional measures can no longer play much
of a supporting role. Ever since the breakout of credit crunch in American
autumn, many countries have acted on monetary measures in the
beginning by continuously lowering interest rates aiming to stop the
worsening financial condition. Official interest rates in several countries
or region including the USA, Canada, Japan, UK, Switzerland, and Hong
Kong SAR are close to zero. Notably the interest rate of the bank of
England has not reached this level in its 315-year history. According to
the latest US Federal Reserve policy meeting, the ideal interest rate for its
economy in current condition would be minus 5%. A central bank
however can not cut interest rates below zero. The actual situation
8
suggests that the central governments need to adopt unconventional
policies and provide stimulus. Thus, fiscal policy has become critical to
reinstate the global recovery. Countries at the G20 summit in November
2008 agreed to ‘use fiscal measures to stimulate domestic demand to
rapid effect, and as appropriate, while maintaining a policy framework
conducive to fiscal sustainability’. The latest report from the IMF states
the G20 countries will spend USD 820 billion in 2009 in their respective
economies, or 2% of GDP. China has started a RMB 4 trillion (USD 585
billion) two-year stimulus package to boost its economic growth. The
Chinese central government will fund as much as RMB 1.2 trillion. In the
first quarter of 2009, lenders in China answered the government’s call to
open credit taps by extending more than RMB 4.6 trillion in new loans;
more than total new lending in 2007. Worries arose in observation of such
rapid loan growth that history will repeat itself as in the 1990s when
China suffered from bad loans. Government thus announced revitalization
and restructuring plans for ten major industries, to promote economic
growth pattern to domestic demand-oriented growth.
Since the formation of China’s stock exchanges in 1990, the stock
markets have developed rapidly. Stock markets have helped China to
restructure SOE ownerships, improve their corporate governance, credit
9
market and capital allocation efficiency. They are also likely to harm
economic development due to their susceptibility to market failure which
is often manifest in the volatile nature of stock markets found in many
developing countries (Singh and Weiss, 1998). Thus, government
intervention is indispensable. As a developing economy, China has been
pursuing a path of development in line with its real condition in the last
two decades, from planned economy to market-oriented export economy.
To unite a market mechanism with its socialist principles, government
intervention is inescapable in its step-by-step reform. Government policy
leads the development of stock market and, on the other hand, is affected
by and adjusts itself according to the markets.
The focus in this paper is China’s monetary policy, fiscal policy and
specific capital market related policies. I start a detailed literature review
in chapter one, discussing the development of western economics related
to the role of government intervention. Chapter two concentrates on
monetary policy. I firstly discuss the related literature and methodology,
and then proceed with a detailed empirical analysis on the relationship
between stock market, money supply and interest rates, supported by data
of M0, M1, M2 and CPI. Regression and descriptive analysis is used in
this chapter. The third chapter focuses on fiscal policy, namely
10
government spending, bond issuance and taxation policy, based on
empirical data. Portfolio allocation theory and descriptive statistics is
used. The next chapter summarizes the government policies adopted
during China’s stock market development and discusses whether the
macroeconomic conditions have a direct correlation with the stock
markets. In this chapter, stock reform is introduced in detail, followed by
the financial market related policies which government is or will
implement to improve the general capital market condition. Game theory,
VAR analysis, event and case studies are conducted.
11
Chapter One Literature Review
Till the end of 19th century, the dominate thinking was still the
‘invisible hand’ theory derived from ‘The Wealth of Nations’, the founder
of modern economics Adam Smith’s pioneer work. His discussion of the
baker-brewer-butcher seeking trade has been enshrined in many economic
books. Smith believes people’s rational egoism drives them to maximize
their self-interests and in the meantime also benefits society. His ethical
theory however is not equal to selfishness. He argued that the bank notes
would come to have the same value as gold and silver money when
people have such confidence (trust) that a banker is always ready to pay
upon demand when notes are presented at any time to him. Before ‘The
Wealth of Nations’, Smith published his first book ‘The Theory of Moral
Sentiments’ in 1759 which already put forward the relationship of
morality and law in economic activities. It is not a laissez-faire economy.
While stating that prudence was of all virtues that which is most helpful
to the individuals, Smith also argued that humanity, justice, generosity
and public spirit are the qualities most useful to others. Smith was deeply
concerned about the poverty and defended the role of the state in doings
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things the market might failed to do3. It is thus hard to carve out any
theory of the sufficiency of the market economy but this is often
overlooked. The laissez-faire notion was expounded in the 19th century,
known as Say’s Law. In Jean-Baptiste Say’s work ‘Treatise on Political
Economy’ aroused from French philosopher Étienne Bonnot de
Condillac’s utility theory of demand4 and Adam Smith’s theory of cost
on supply, he outlined the famous Law of Markets which claims that
supply creates demand. Such supply-side economics means that
overproduction in a free economy is impossible as the inventory will be
sold when price is cut to a certain level, or if supply increases but demand
does not, the price will fall to a market clearing level. Say’s ideas focus
on the underlying reason for recession. Therefore essentially Say’s Law
suggests that a recession could not take place due to a failure in demand.
As supply creates demand, there will be a demand for goods as long as
there are goods available.
As economists witness the failure of market mechanism when poor
economic phenomenon appear, Swedish economist Knut Wicksell’s
cumulative progress theory has defended a place of government
3
See Amartya Sen’s recent article ‘Adam Smith’s market never stood alone’, published in Financial
Times, May 12, 2009.
4
Condillac suggests the value depends on the utility in relation to people’s needs. It increases or
decreases when needs change.
13
intervention. As the grounder of the Swedish School, Wicksell implied in
his work that the difference between the natural rate of interest and the
money (loan) rate of interest set the financial demand. He defined the
natural rate as a rate which is neutral ‘in respect to commodity prices, and
tends neither to raise nor to lower them’ (1936 translation). When the
natural rate is equal to money (loan) rate, supply and demand for capital
are in equilibrium in an economy. When the natural rate is higher than
money (loan) rate, people will borrow money from the banks and invest.
In other words, the margin of capital is greater than its cost. Thus,
government decisions on the change of interest rate results in a system of
changes in the real economy, essentially by changing the demand for
investment. So the influence on short-term interest rates to contain
inflationary pressure and promote growth and employment lie in the work
of Wicksell.
Austrian economist Ludwig von Mises and his student Friedrich
Hayek took Wicksell’s cumulative cycle progress work further. According
to them, a ‘malinvestment’ is generated by expansionary central bank
monetary policy when borrowers are misled to borrow more. An
artificially low interest rate makes investors believe that the income they
will generate in the future exceeds their investment costs so that they
14
misallocate the capital. Therefore, a tendency towards overinvestment in
a low interest rate environment is almost inevitable. In other words, a
boom is caused by a series of wrong ‘malinvestments’. When people
eventually realize that supply outpaces demand, ‘malinvestment’ made
during a monetary boom must be liquidated as people start to reallocate
their savings and consumption and banks stop credit expansion (Rothbard,
2006). A boom busts.
After analyzing empirical data, Milton Friedman concluded the
explanation of the business cycle is false (1993). Though the boom-bust
cycle theory may correspond to the housing bubble fueled by the Federal
Reserve’s artificially low interest rate5, the two important origins of such
a cycle should be questioned. Firstly, the theory figures out that the prime
culprit is centralized monetary intervention. Besides the government, the
market itself may also create the cycle, suggested by Real Business Cycle
Theory. Imagine a scenario when supply increases, people have more to
consume. One may consume all or consume partially and invest the rest
in order to increase the future consumption. The life cycle saving theory,
for example, argues that individuals consume based on expected income
5
‘Greenspan’s Bubbles’ by William A. Fleckenstein suggests that Greenspan’s policy of keeping rates
too low for too long inflated the housing bubble. Greenspan however defended that the growth of China
and other emerging market led to excessive savings and pushed global long-term interest rates down,
which caused mortgage rates and the benchmark Fed-funds rate to diverge after moving “in lockstep”
from 1971 to 2002.
15
so they save while they work (Fisher, 1930). This theory however does
not really comply with the consumption style of the Americas. Secondly,
the above cumulative cycle theory is based upon the ‘malinvestment’
made. Could it also be caused by a symmetric ‘malconsumption’? Barro
and Grillio found that consumers’ tendency to increase the consumption
grows bigger if he/she expects the change of income to be permanent
(1994). Two scenarios could be considered at least.
a)
When the marginal propensity to consume is bigger than
one6: under this situation, consumers borrow money to
finance expenditures. In case that their income increase
is slower than the increase of expenditure, or disposable
income is smaller than spending or their expected future
income is lower than what it actually is, the demand is
artificially higher. Entrepreneurs thus will enhance the
production. When consumers could not finance the
expenditures prepaid by credit card or loan or even
finally default, the ‘malinvestment’ by entrepreneurs
must be liquidated. This consumption scenario is more
6
Marginal propensity to consumer is measured as the ratio of the change of
consumption with respect to the change in disposable income that produced
consumption. The ratio thus is a figure between 0 and 1.
16
in line with the over-extended American consumption
style. The two graphs below portray such a situation.
Chart 1
US Credit Card Debt v.s. Real Wage and Household Savings v.s. Debt
17
Source: Innovest, from Federal Reserve, Federal Deposit Insurance Corporation
and U.S. Bureau of Economic Analysis.
b)
When the consumer does not increase consumption
accordingly while the disposable or expected income is
increasing or they are more conservative in existence of
the poor economic environment, the demand grows
comparatively slower or even flattens out. The below
chart,
for
example,
displays
China’s
individual
consumption and disposable income growth from 1995
to 2007. People’s disposable income grows at a faster
18
pace than their consumption. Companies therefore
stabilize the supply according to the consumption level
to avoid overproduction, although they could have
increased the output to the same level as the income.
What is more, the consumer consumption style should
be affected by factors such as the personality, risk
preference, social consumption style etc. The research
category of economics has grown far further than the
traditional definition in the 20th century. Analyzing
subjects have been expanded to many human behaviors
from family issues such as marriage, divorce, crime, and
political matters e.g. voting behavior etc. Stigler (1984)
called such expansion of economics an imperial
economics. Family, in the subject in microeconomics, is
regarded as an ‘enterprise’ by Becker (1978).
Chart 2
Individual Consumption v.s. Disposable Income in China, rebased
19
350
300
Consumption
Disposable Income
250
200
150
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
100
Source: National Bureau of Statistics of China (NBSC)
Opposite to cumulative progress cycle theory, Irving Fisher
overhauled the quantity theory of money and states that if the quantity of
money increases, the level of prices rises when the circulation and
transaction volume of money does not change (1911), known as the
Fisher Equation. For Fisher, changes in money supply almost fully
explained the changes in long-term prices. The disagreement of Wicksell
and Fisher continued later by the debates between Keynesian and
monetarists.
20
British economist John Maynard Keynes’ research has posted major
influences on the modern economic and political literature. His thinking
has overturned the free market theory. He advocated that government
shall use fiscal and monetary tools to correct adverse economic effects. In
his main article ‘The General Theory of Employment, Interest, and
Money’ published in 1936, Keynes asserted that when the interest rate on
money exceeds the expected return on capital, people intend to hold
money instead of investing in that capital. He also claimed that the
amount of savings had little to do with variations in interest rates which in
turn had little impact on investment. As an extension to the IS/LM model7,
the Mundell-Fleming model portrays that fiscal policy has effect on
domestic economic output when capital movement is limited and
exchange rates are flexible. However, such a mechanism is likely to differ
in an open economy from a closed economy. In a very open economy,
investment and consumption may increase in response to a government
spending shock while they fall in the existence of a relatively closed
economy, suggested by the quantitative findings of Corsetti et al (2007).
An important transmission mechanism of monetary policy is
delivered through the change of interest rates, which results in the
7
For a detailed view of IS/LM model, see John Hicks’ paper ‘IS-LM: An Explanation’ (1980-1981),
Journal of Post Keynesian Economics, version 3, page 139-155.
21
changes on market rate, asset price, exchange rate and people’s
expectations. The change of interest rate influences people’s incentives to
borrow and save. The disposable income impacts people’s spending. If
credit is constrained, the consumption is significantly affected. When
interest rates climb, the cost increases by holding money, people intend to
buy other non-money valuables, and vice versa. This point not only has
been discussed by famous Keynesian money supply theory, but also by
Tobin (1956) and Baumol (1952)’s inventory theoretic approach.
Keynesian economists believe the aggregated demand is influenced by
public and private decision primarily including monetary and fiscal policy.
Now let’s have a brief look of the relationship described between the
three important tools in monetary and fiscal policy – interest rate, money
supply and bonds. Keynes believes people can hold their wealth in two
forms, money or bond. The nominal interest rate is the return on bond and
it is the opportunity cost of holding money. Keynes believes there are
three motives for the demand of liquidity:
a.
Precautionary demand: people intend to hold more liquidity
when they are less certain about the future
b.
Speculative demand: higher interest rates lead to higher cost of
holding money, people therefore intend to hold less money
22
c.
Transaction demand: the more people wish to buy, the more
amount of money they intend to hold. In this case, people’s real
income may be higher.
The key theoretical element in Keynes’ liquidity theory is the
concept of equilibrium (Chart below). When nominal interest rate is at R1
and money supply is at M1, people hold more money than preferred
(excess supply); they intend to decrease the money stock by buying more
bonds till R2. As bond prices rise with demand, nominal interest rates fall.
The same applies to point R3 where people hold less money than they
wish to (excess demand), they intend to increase the holding of money by
buying less bonds till R2, leading to the increase of nominal interest rate
and force the bond price to drop. As money supply increases from M1 to
M2, at the old equilibrium R2, people have more money than they wish to
(excess supply again where red dashed line), nominal interest rate will
drop as they invest more in bonds. Keynes argues that when nominal
interest rates reach certain point (R4), people are not willing to convert
money into bond investment when money supply increases (from M3
onwards). Thus, interest rate falls no further.
Chart 3
Keynes Equilibrium Concepts
23
Interest Rate
Excess Supply
R1
R2
Excess Demand
R3
R4
M1
M2
M3
M4
Money
Keynes thinks when nominal interest rates drop sharply, it will not
affect investment decision materially (imagine replacing above downward
curve with a downward sloping straight line with a more gradual degree
of inclination). Keynes’ theory has then been widely accepted and put into
practice in the western world.
The American economist Hyman Minsky, followed the Keynesian
tradition, supported some government intervention in financial markets.
Minsky believes a speculative euphoria develops when companies have
excess cash and debt grows to a level when borrowers can not pay off.
24
Such debt-income relation creates a financial crisis unless government
steps in. Thereafter the tightening strategy adopted by banks and lenders
leads to the contractions of economy. This capital movement is known as
the financial instability hypothesis (detailed in 1992). He defined three
distinct income-debt relations for economic units, labeled as hedge,
speculative, and Ponzi finance. The hedge borrowers can fulfill all
contractual payment obligations by current cash flow, such as banks. The
speculative borrowers can meet their payment commitments by liability
rollovers. Government and corporations with floating debts and
commercial papers are typical speculative borrowers. The Ponzi
borrowers can not fulfill either the repayment of principle or the interest
due. They borrow on the belief that the appreciation of the assets in the
future will be sufficient to finance the debt; therefore the Ponzi finance
has a low margin of safety to the holder of this kind of debt. The economy
could be an equilibrium seeking and containing system if hedge financing
dominates. The likelihood that the economy moves to a deviation
amplifying system grows with the increase of speculative and Ponzi
finance. Minsky argues ‘economies tend to move from a financial
structure dominated by hedge finance units to a structure in which there is
large weight to units engaged in speculative and Ponzi finance’. When
25
such debt expansion occurs during an inflationary state, government will
intervene with attempts such as monetary constraint. Units with cash
shortfalls will therefore be forced to sell out positions, which likely leads
to a collapse of asset values. Minsky’s proposition seems to draw the
evidence of the current financial crisis.
An alternative view to the conventional Keynesian macroeconomic
model is the neoclassical approach known as Barro-Ricardo equivalence
proposition (Barro, 1974). It argues that a lower taxation now will not
stimulate people to spend more as they would expect a future tax rise thus
save the margin from tax cut in order to pay more future taxes. So savings
would rise between the current tax-cut and future tax-raise. Thus the
permanent income of household is unaffected meaning consumption
remains also unchanged. This theory however is based on a perfect capital
market and individuals have operative altruistic bequest motivates
(Barsky et. al, 1986). In spite of these assumptions which were later
widely challenged, a key point illustrated in this modern macroeconomic
theory is that policies can have unintended consequences.
Milton Friedman accepted Keynesian economics but later challenged
it. He criticized Keynes’ absolute income consumption hypothesis and
developed permanent income hypothesis, a more comprehensive
26
explanation of the relationship between individual income and
consumption. His empirical research with Schwartz published in his 1963
book suggests that a correlation between the money supply fluctuation
and economic fluctuation as the rate of inflation and the rate of money
growth per unit of output were generally similar in two world wars. They
concluded that there is causation from price to money. Friedman held the
opinion that government’s interference in the economy should be
restricted and the fiscal tool is not efficient in improving demand. He
criticized the marginal propensity consumption theory of Keynes and
claims that when people’s original desire gets satisfied, new consumption
sentiment is generated. As such, an expansionary policy will inherently
cause inflation. The close linkage between money supply and inflation, he
argued, suggests rule-based monetary policy to control money supply is
the only efficient method. Friedman believes if the Federal Reserve
would have provided sufficient liquidity accordingly during the Great
Depression from 1929 to 1933 when the quantity of money dropped by
1/3, the tragedy could have been avoided (1999). Friedman promoted
such a macroeconomic policy which is formulated later as monetarism.
Monetarism has been put into practice by the USA and UK especially in
the 1980s. The disinflation policy adopted by the UK, however, led to the
27
growing unemployment rate. From the 1950s to the 1960s, the
unemployment was lower than 2%, which jumped to 9.1% in 1981 and
13% in 1985.
The application of Keynesian economics, namely to expand demand
by tax-cut, did not stabilize the Western economies and prevent the
stagflation in the 1970s. Keynesian theory is criticized therefore by
so-called supply-side economics. As its name implies, its main
characteristic, is to emphasize that supply can effectively create economic
growth, and demand will adjust to the change of goods and services
produced. The pioneer of this theory is the Canadian professor Robert
Mundell. Mundell advocated tax deductions and application of the gold
standard to stabilize the USD in 1974. Mundell’s proposition was
developed by economist Arthur Laffer and popularized by journalist Jude
Wanniski. Laffer is best known for studying the trade-off between tax rate
and tax revenue which is named the Laffer curve by Wanniski (1978).
Why lowering taxation may actually increase tax revenue is based on
three assumptions (Niskanen, 1988):
a)
Tax revenue does not necessarily develop in the same
direction as the marginal tax rate. When they reach a
certain point, they trend in opposite directions. Laffer
28
exhibits the curve below (2004) including two extreme
situations when the tax rate is zero and 100%. The
prohibitive range suggests the taxation is too high; a rate
cut will result in increased government revenue. Laffer
curve illustrates that there is no government income if
taxation is 100% as nobody will work if no return can be
generated. However, in a classical Communist society, an
effective 100% tax rate is in place as promoted by pure
Marxism. Such questioning remains therefore highly
theoretical rather than practical as it is essentially
overruled by basic economic thought.
Chart 4
Laffer Curve
29
b)
A lower marginal tax rate encourages people to work and
save as the lower taxation rate will be offset by greater
employment and productivity.
c)
High taxation leads to low investment return, which
reduces the total investment amount. Therefore a lower
marginal tax rate creates a higher propensity to invest.
The supply-side theory was accepted and put into practice by the
Reagan administration in the United States. To fight inflation, Reagan
30
passed the Economic Recovery Tax Act to slash taxes by USD 749 billion
over five years. Non-labor income (non-earnings income) was cut to 50%
from 70% in 1981 and the top capital gains tax limit was reduced from
28% to 20%. As a result, unemployment declined from 1983 to 1984 and
returned to the level of the 1970s in 1986 (Mishra, 1990).
Since the 1970s, the assumption and implication of rational
expectation has been largely applied by economists. The theory, originally
proposed by John Muth in 1961, was later developed by Robert Lucas Jr.
Facing scarce resources, an economic unit is expected to maximize its
outcome by allocating resources in the most efficient way. It is recognized
as the Pareto optimum. Information, policy, preference, cognitive level
and risk are the basis of estimation initially.
Rational expectation is defined to be the best guess of the future by
making use of all available information. It focuses on analyzing the
impact on economic life and influence on economic policies. It protects,
develops neo-classical economics and repudiates Keynes’ theories. It
transformed macroeconomic analysis and deepened our understanding of
economic policy. Lucas and his rational expectation theory won the Nobel
Prize for economics in 1995. Meanwhile, modern finance, based on
financial economics, rose between the 1950s and the 1960s. It agreed to a
31
large degree on rational selection. Some researchers started to use rational
selection theory, such as Olson’s collective action theory. Thereafter,
neo-classical economists inherited and developed classical economics’
rational person theory. It abandoned the objective mental factor and
turned to rational selection, replacing the concept of preference with
intention. The researchers used margin analysis in their research where
the maximizing concept requires rational selection to maximize pleasure
with minimum pain. After all, in neo-classical economics, a rational
person shall have his preference (within a feasible range) of actions,
assuming perfect information and computation capability. After deliberate
consideration, he will opt for those which benefit himself the most.
Rationale, in economics, means economical rationale. Irrational is
simply the opposite to the assumption of a perfectly rational person. A
rational action shall depend on the environment in which the goal is set.
Traditional economical analysis is based on the specific goal of the actor.
By adding particular economic factors, economists do not take
psychological conditions into account. However, action is the result of
thinking. The cognitive limitation of both knowledge and cognitive
capacity restricts perfect consideration. The only solution might be,
within a certain time frame and under certain circumstances, is to create a
32
model which helps to make the decision. This model is the heuristic
simplification and it is a decisive consideration in behavior finance,
which is called cognitive bias and irrational behavior.
Hirshleifer (2001) categorizes several types of cognitive errors
investors can make. One type of bias, self-deception, occurs when people
believe they are better than they really are. Both psychology and financial
literature define those with this type of behavior as being ‘overconfident’.
Overconfidence however can be identified in several aspects including
miscalibration, unrealistic optimism and better than average effect. Biais
et. al (2002) argued that ‘the importance of specifying what kind of
overconfidence – miscalibration, the better than average effect, illusion of
control – may be influencing trading behavior’. These investors intend to
overestimate their knowledge and underestimate the risks. Cognitive error
also causes investors to under-react or over-react to the new information.
Barnes and Ma (2002) found in their event analysis that domestic Chinese
investors overreacted to the announcements of proposals instead of the
final approvals of bonuses in stock market. Chinese stock market is
barely 20 years old so the notion of investing is relatively new to most
Chinese investors in comparison with those from more capitalistic
oriented countries. Thus, Chinese investors shall be more inclined toward
33
making mistakes and being influenced by biases. Chen et. al (2003)
studied 66’891 brokerage accounts in China and found strong evidence
that the more sophisticated Chinese investors are, the more likely they
will make trading mistakes and be affected by disposition effect. They
therefore concluded that investor sophistication does not necessarily
mitigate behavioral biases, nor improve trading performance. Shefrin
(2000) discovered two main implications of investor overconfidence. The
first is that investors take bad bets because they fail to realize that they
are at an informational disadvantage. The second is that they trade more
frequently than is prudent, which leads to excessive trading volume.
Although investors are affected by their cognitive ability to make wrong
investment decisions, researchers also find that experts (people with
higher degree of experience) may even be more prone to overconfidence
than novices as they believe theories and models applied tend to outweigh
market reality (Griffin and Tversky, 1992). Additionally, people generally
have social biases – trend-following. This is also referred to as herd
instinct. Herd instinct describes a phenomenon in which people tend to
identify with the beliefs or behaviors following a larger group of
individuals who communicate frequently with each other. As information
is not efficiently spread, investor decision predominantly depends on
34
others’ behavior rather than present information. When everybody talks
the same, black becomes white. While we all are biased to some degree,
the difference may only be that some may be more susceptible than others
due to the innate personality styles such as conscientiousness, neuroticism,
extraversion etc. Rational expectation has been used to support several
hypotheses such as policy ineffectiveness proposition and efficient market
theory which is extensively used in financial market analysis.
Many macroeconomic models are widely based on the adaptive
expectations principle which suggests authorities only act after an
improper government policy is in effect 8 . The policy ineffectiveness
proposition was proposed by Thomas J. Sargent and Neil Wallace based
on rational expectation theory (1975 and 1976). They argue that the
government can not effectively intervene in the economy by simply
manipulating output. When government implements an expansionary
monetary policy in order to stimulate production, wage and price level
will go up accordingly as rational people will foresee the influence. Thus,
in effect, real output, salary and price levels remain constant. Grossman
and Stiglitz (1980) opposed the above theory by arguing that for the
8
E.g. Nikolaos Kouvaritakis & Antonio Soria & Stephane Isoard, 2000, Modelling energy technology
dynamics: methodology for adaptive expectations models with learning by doing and learning by
searching, International Journal of Global Energy Issues, Inderscience Enterprises Ltd., volume 14(1),
page 104-115.
35
purpose of profiting from the government policy, people will not reveal
the information gained from their cognitive knowledge so that the policy
will remain effective.
Another important hypothesis developed from rational expectation is
efficient market theory which asserts the financial market to be
informationally efficient. The hypothesis was developed by Eugene Fama.
In his influential article (1970), he believes that the stock market is
extremely efficient in reflecting information. It is generally accepted that
when information is released, it spreads fast enough so that it can be
incorporated into stock prices without delay. The hypothesis is associated
with the idea of a random walk which suggests that if the information is
effectively and immediately reflected by stock prices, tomorrow’s stock
price will only reflect tomorrow’s news and it is independent from the
price changes occurring today. This assumption however, does not
correspond to many stock price movements in China.
36
Chapter Two Monetary Policy
Monetary policy attempts to stabilize the economy by controlling
interest rates (the cost of money) and the supply of money. A successful
implementation
of monetary policy requires
a
fairly accurate
consideration of how fast the impact of such policy changes could be
delivered to other parts of the economy and how large the impact is. In
China, financial markets are built as a transition to a market economy.
There has been increasing but realistic emphasis in the use of market
instruments to the extent that such a transmission mechanism can be
delivered.
The impact of money supply change can be expressed by
adjustments in investor’s portfolio allocations. An increase of capital
breaks the balance of a given portfolio, changing the marginal utility ratio
of the assets therein. Money is a comparatively stable asset. Increasing
the cash amount in a portfolio lifts the ratio of the riskless asset. To
maximize the return, a rational investor will generate a new balance by
investing more in riskier assets. If the supply of a given riskier asset stays
unchanged, its price climbs. So in principle when money supply increases,
37
stock prices follow in the same direction.
The interest rate is the price the borrower pays to use a resource at a
given time. This implies that the higher the interest rate, the more
valuable that resource is today. Interest rates change the cost of holding
cash. When interest rates increase, the borrowing cost rises. Investors will
therefore reduce the allocation to the stock market as it is considered to be
more risky. Additionally, a higher interest rate generates higher return on
cash deposits. When interest rates decline, investors buy more stocks as
they prefer to hold comparatively more profitable investments. Interest
rate changes will also affect companies’ profitability. Higher capital costs
leads to lower expected return. If the rate adjustment is already expected
by investors, based on the efficient market hypothesis, the demand for
stocks will not change much. However, if the rate decreases unexpectedly,
according to Keynes’ liquidity preference theory, people will believe
interest rates will rise in the future, meaning stocks will become cheaper.
One should sell now and buy later. This leads to a drop in stock markets.
The converse is true.
The impact of interest rates on stock markets can be summarized in
the following way:
a)
Investment replacement
38
Interest rate changes affect return on deposits. Investors will
reallocate investment between deposits, bonds, stocks or other
investments to realize maximum return. When interest rates
increase, capital may flow from stock markets to bank deposits and
bonds, resulting in falling stock prices. This replacement effect
however depends on the elasticity on interest rate change of other
investments. For instance, people's deposit activities are highly
correlated with the adjustment of interest rates, meaning deposits as
investments have a high elasticity on interest rate change; a
decrease of interest rates will impel people to look for other
investments. Such a replacement effect would also be highly
affected by investors’ risk preference.
b) Impact on company profit
The change of interest rate affects the operation of companies,
changing their profitability and investors' expectation. First of all, a
lower interest rate increases the expected future return on
investment. Secondly, interest rates are the opportunity cost of
current consumption. A lower rate encourages people to lift their
expenditures. However, if investors have pessimistic expectations
of future income, or the price drop of goods is larger than the
39
reduction of interest rate, the actual impact on lifting investment
decreases. Moreover, on the consumer side the marginal propensity
to consume would drop in a gloomy economic environment,
leading to higher marginal savings.
c)
Impact on stocks’ inherent value
Stocks’ inherent value is decided by future cash-flow. Such value
has an inverse relation to discount rate under certain risk scenarios.
A drop of discount rate causes lower inherent value, leading to
lower stock prices.
There is usually a time lag between interest rate adjustment and
stock price change. Therefore, when considering such effects it is
necessary to take a long-term perspective. Within a short period of time,
investor’s expectations have a large effect on stock markets. The market
reaction depends on whether the rate adjustment is expected in the market.
Only with unexpected adjustments, may we witness high volatility.
2.1.
Literature and Methodology
Various studies are inclined to use charts and regression methods to
analyze the relationship between money supply, interest rate change and
stock market performance. Friedman (1988) used United States data from
1961 to 1986 and found evidence suggesting that the real quantity of
40
money (M2) demanded relative to income is positively related to the
deflated price of Standard&Poor equities which lagged by three quarters
and negatively related to the contemporaneous real stock price. Sprinkel
(1964) found a relation between the money supply and interest rate
changes, two-month prior, to the bull market between 1918 and 1963.
Homa and Jaffee (1971) concluded, using regression analysis, that money
supply and interest rate changes always precede stock index movements.
Hysteretic data can then be used to predict future stock returns. However,
this theory is contradictory to efficient market hypothesis, which believes
stock prices fully reflect all available information. Therefore the investor
is rational, he will adjust the portfolio in time, leaving no excess return.
As such, monetary policy change can not be the foundation to forecast
future stock returns. Research thereafter shows that money supply and
rate changes in the past do not have predictive value. On the contrary, it is
an opposite Granger causality relation, meaning stock prices causes
change in money supply and interest rate change (Rogalski and Vinso，
1975).
Due to the conflict discovered from empirical studies, researchers
start to look at the characteristics of money supply and interest rates, and
the limitations of the approaches used in empirical studies. Sellin (2001)
41
suggests the cause of such causality contradiction originates from the
mixture of money supply and demand. Money supply is endogenous,
while interest rates are also an inherent variable of economic systems.
Money Zero Maturity (MZM) has become popular as a measure of money
supply. MZM refers to the total amount of money that is immediately
redeemable at par value on demand. It includes coins and currency in
circulation, checking and saving accounts, and money market funds. Thus,
MZM includes all financial instruments that can be freely accessed
immediately without penalty or risks. The recent research by Leuthold
Group and Factset found that the peaks in the ratio of MZM to total US
stock market capitalization have coincided with troughs in the stock
market performance historically from 1970s to January 2009.
Chart 5
MZM to Market Cap v.s. DJ Wilshire 5000 Index
42
Source: Leuthold Group, Factset, as of January 31, 2009
The definition of MZM, unfortunately, does not provide the evidence
of such money assets’ format nor location. Wikipedia has defined money
as anything that is generally accepted as payment for goods and services
and repayment of debts. Some of MZM does not fulfill such a definition.
M0 represents the upper most liquid money type – currency in
circulation. M0 is normally stable but due to its liquid characteristics, it is
exposed to seasonal fluctuations. The curve below displays the M0 curve
from February 2002 to March 2009. In China, this fluctuation pattern is
witnessed around Spring Festival on yearly basis. My analysis below is
therefore based primarily on M1.
43
Chart 6
China’s M0
35
M0, YOY
25
15
5
-5
Feb-02 Oct-02 Jun-03 Feb-04 Oct-04 Jun-05 Feb-06 Oct-06 Jun-07 Feb-08 Oct-08
Source: Bloomberg
Case studies concentrate on the instantaneous response of stock
markets following the announcement of a change in monetary policy.
This research focuses on the daily or weekly movements rather than
monthly or quarterly changes. Pearce and Roley (1983) concluded that
unexpected monetary change has a negative impact on stock prices, based
on weekly data between 1977 and 1982.
Qian Xiao’an (1998) investigated the correlation between money
supply and stock price by using static regression and variance
decomposition analysis on data from March 1994 to February 1997 in
44
China’s stock market. He found Shanghai and Shenzhen index
movements were positively correlated to M0, not correlated to M1, and
inversely correlated to M2. He believes expectation has a greater
influence on the performance of stocks than the actual change in money
supply. Tang Qiming (2000) concluded that China’s stock market is
somewhat sensitive to interest rate decreases but that every rate change
led to a different result; sometimes stocks retreated when interest rates
were lowered. Jiang Zhengsheng and Jin Ge (2001) found the inter-bank
borrowing rate was inversely related with Shanghai stock market. Using
the same approach as Qian Xiao’an, Liu Zhiyang (2002) came to the
conclusion that money supply is positively correlated to stock price, and
that this linkage is strengthening. Sun Huahao (2003), however,
discovered that M0, M1 and M2 have no impact on the market, but
interest rate changes had significant effects during the period from June
1993 and October 2002. Liu Song (2004)’s result shows the change of M1
had an obvious impact on stock markets, and stock market movements
had visible influence on M0.
2.2.
Results – Money Supply
Are stock prices set by money supply? Some researchers like Wray
45
(1998) have questioned such hypothesis.
The null hypothesis: the stock market is not correlated to M1
The chart below indicates the year-on-year M1 growth has a
significant visual correlation with the Shanghai Composite Index, from
January 1996 to March 2009. M1 moves contemporaneously with the
business cycle. M1 measures the currency in circulation plus the
checkable deposits. This type of money represents the highest liquid
money in a given economy. Essentially, stock markets are capital-fueled
markets. It makes sense that the capital inflow promotes the stock market
and an outflow of capital leads to the market drop. As a macroeconomic
indicator, M1 also presents a strong cyclical pattern. We may see from the
below graph that in China, M1 generally depicts a three-year cycle. Such
a cycle is considerably stable and predictable due to the characteristics of
a large scale of economy. What can also be discovered is the lag between
the stock market following the bottoming of M1, normally within 3
months except the most recent trough, while the tops of the stock market,
were broadly in line with the peaks of M1. What is special about the last
cycle of the stock market and M1 is that the bear run has been realized
faster than the bull run and the cycle is expanded to October 2008, 1-year
longer than usual. The sharp decrease of stock markets was associated
46
with the tight monetary policy government implemented from the
beginning of 2008 in order to cool the overheated investment and such a
sudden correction was also influenced by the worldwide credit crunch.
Moreover, the bottoming of the stock market seems to precede M1. The
volatility of M1 and Shanghai Composite indicates that except during the
course of financial crisis (1997 and 2007), stock market is less volatile,
stating that asset prices are not excessive relative to monetary variables.
Chart 7-1 M1 v.s. Shanghai Composite Index
250
25
200
20
150
15
100
50
10
0
5
-50
Shanghai, YOY
M1, YOY
-100
0
1/31/1996 6/30/1997 11/30/1998 4/30/2000 9/30/2001 2/28/2003 7/31/2004 12/31/2005 5/31/2007 10/31/2008
Source: Bloomberg, Shanghai at left scale
Chart 7-2 M1 v.s. M2
47
30
25
23
25
21
19
20
17
15
15
13
11
10
9
M2, YOY
M1, YOY
7
5
5
6/30/1998 10/31/1999 2/28/2001 6/30/2002 10/31/2003 2/28/2005 6/30/2006 10/31/2007 2/28/2009
Source: Bloomberg, M2 at left scale
In chart 7-2, we can see that except the peak in 2003 and the time
period during 2009, the general tendency of M1 and M2 seems to be
irrelevant. M2 also looks to be less volatile than M1. Kydland and
Prescott (1990) find that M2 leads the business cycle in the US. The
Granger Causality result however suggests that in China, M1 ‘Granger
Causes’ M2. It implies that Chinese intend to keep time deposit intact
(relatively prudence) while checkable deposits are the most actively
moving assets between investments and savings.
48
Additionally the correlation between M1 and stock market
year-on-year growth can not be identified in the United States during the
same period. Except the three peaks from 2000 to 2004, the below image
seems to imply a rather inverse relationship between M1 and Dow Jones
Index.
Chart 8
US M1 v.s. Dow Jones Index
49
20%
60%
15%
40%
10%
20%
5%
0%
0%
1/31/1996 7/31/1997 1/31/1999 7/31/2000 1/31/2002 7/31/2003 1/31/2005 7/31/2006 1/31/2008
-20%
-5%
-40%
M 1, YOY
-10%
Dow, Y OY
-60%
Source: Bloomberg, Dow at right scale.
The inverse relationship of M1 and Dow Jones Index can be plotted
in the below chart.
50
US M1 Line Fit Plot
60%
Dow
Predicted Dow
40%
Dow
20%
0%
-10%
-5%
0%
5%
10%
15%
20%
-20%
-40%
-60%
US M1
To test whether the visual correlation stands between M1 and stock
market in China, I use ANOVA regression analysis. The following results
can be generated based on the above data. The confidence interval is set
at 95%. The adjusted R2 shows 39.4% which is expressly high for a single
variable model. The F-statistic is large at 103.8. Additionally no zero can
be found within the confidence interval – between lower 95% and upper
95%. And X-variable (Shanghai)’s P-value is extremely small, suggesting
there is barely a likelihood that the slope of the regression line is a
non-zero value by chance, so the slope is considered statistically
significant. T-statistics and significance F states the significance level is
below 0.05. The line fit plot displays there is a significant correlation. So
51
the null hypothesis is rejected.
Regression Statistics
Multiple R
0.630811184
R Square
0.39792275
Adjusted R Square
0.394087863
Standard Error
2.906958315
Observations
159
ANOVA
df
1
157
158
SS
876.8469848
1326.713843
2203.560828
MS
876.8469848
8.450406642
F
103.7638805
Significance F
5.03568E-19
Coefficients
14.68974197
0.04419315
Standard Error
0.24643752
0.004338423
t Stat
59.60838254
10.18645574
P-value
9.8486E-110
5.03568E-19
Lower 95%
14.20298090
0.03562394
Regression
Residual
Total
Intercept
Shanghai, YOY
Upper 95%
15.176503035
0.052762361
Shanghai, YOY Line Fit Plot
30
25
M1, YOY
20
M1, YOY
15
Predicted M1, YOY
10
5
Shanghai, YOY
0
-100
-50
0
50
100
150
200
250
Using Eviews’ (version 6) estimate equation function, the regression
can also be tested in least squares method as below. The results reiterate
52
the conclusion above. Thus it can be concluded that China’s stock market
has a strong correlation with M1.A residual graph is shown below. The
fitted curve refers to the predicted value. We can see that the predicted
peak between 2002 and 2003 is higher than the actual and the forecasted
peak in 2007 is much lower than the actual top. These discrepancies
between actual situations and the predicted curve imply that government
tried to stimulate a market recovery after the Internet Bubble and intended
to cool the market in 2007, although the actual outcomes deviate
somewhat.
53
Now I look at the recent two-year development of real money supply
and stock market prices when the market experienced both bull and bear
conditions. The following graph displays the M0, M1 and M2 movements
in comparison with the Shanghai Composite Index from February 2007 to
March 2009. The volatility of M0 present in January and February 2008
is the seasonal fluctuation due to the Spring Festival so these two months
can be excluded. According to Keynes’ liquidity preference theory, M1
and M2 should grow equally, meaning that when income increases,
checkable deposits should accumulate at the same speed as term deposits.
54
It can be seen in the graph that M1 and M2 kept at the same level during
the course of 2007 while M0 descended by half. The gap between M0 and
M1/M2 indicates a large amount of liquidity (cash in circulation) may
have flooded into the stock market, and this coincided with the climb of
the stock market during the same period.
Facing the danger of an overheated stock market and inflation driven
by the booming economy, the People’s Bank of China tightened the
money supply by increasing required RMB reserve ratios 10 times in
2007, from 9.5% to 14.5%, aiming to limit the currency in circulation
soas to support a reasonable credit growth. An adjustment of bank deposit
reserve ratios is designed to have obvious effects on the total money
supply as it forces banks to adapt rapidly to the new policy and leads to
an immediate drop of credits granted. In fact, the strong policy change did
indeed slow down the growth of M1 and M2 but it didn’t overturn the
situation of excess liquidity. This was owing to a high trade surplus and a
large amount of individual bank deposits. A report from General
Administration of Customs shows that the trade surplus in May 2007
expanded to more than USD 23 billion, 73% higher than the year earlier.
Therefore, the aggressive change of bank deposit reserve ratios was
considered necessary.
55
The total money supply started to decrease in 2008, during which
time M2 stayed basically stable while both M0 and M1 dropped within a
similar scale. The discrepancy between M0/M1 and M2 suggests people
cashed out their checkable deposits. However, the stock market lost half
of its value despite such a significant growth in capital. Odean (1997)
surveyed 10’000 accounts of a large brokerage house and concluded
investors are reluctant to realize their losses while they sell winners too
quickly and hold losers too long. This is called disposition effect by
Shefrin and Statman (1985). Therefore, what occurred may be explained
in that investors added to their investments in order to rebalance their
portfolios to reach a break-even during the long bear market caused by
the global financial crisis. Some investors may also be over-confident on
themselves on predicting the bottoming of stock markets. Additionally,
people would have hesitated to realize losses by selling dropping stocks,
which also explains the tendency of the decrease to redeem checkable
deposits. The government thereafter loosened the credit policy to help
tackle the economic slowdown. The Shanghai Composite Index picked up
almost simultaneously with the increase of money supply. The swifter
elevation of M0 and M2 implies people became more cautious facing the
global financial crisis as they may have preferred to hold safer assets such
56
as cash or make longer-term time deposits.
Chart 9
Money Supply v.s. Shanghai Composite Index, rebased
250
M2
Shanghai
M1
M0
200
150
100
50
2007.02
2007.03
2007.04
2007.05
2007.06
2007.07
2007.08
2007.09
2007.10
2007.11
2007.12
2008.01
2008.02
2008.03
2008.04
2008.05
2008.06
2008.07
2008.08
2008.09
2008.10
2008.11
2008.12
2009.01
2009.02
2009.03
0
Source: NBSC, The People’s Bank of China
The Granger Casualty test between Shanghai Composite and M1’s
year-on-year growth returns the following results. Therefore it can be
concluded that due to the low p-value of 0.0002, the null hypothesis can
be rejected. I can say Shanghai ‘Granger Causes’ M1.
57
CPI
Friedman (1988) explains in his paper that a rise in stock prices
means an increase in nominal wealth, and generally, given the wider
fluctuation in stock prices than in income, also a rise in the ratio of wealth
to income. If money supply and stock markets are very much associated
with investor behaviors and their wealth condition, what can I acquire
from the relationship between M1 and the CPI? Schwert (1981) found
that inflation volatility predicts stock volatility.
The null hypothesis: there is no relationship between M1 and the
CPI.
The graph below compares the year-on-year returns of the CPI and
M1 from January 1996 to March 2009. Data is monthly, collected from
Bloomberg. It can be seen that CPI presents some level of time lag behind
the movement of M1 but I expect there is a high correlation.
58
Chart 10
CPI v.s. M1
12
25
10
20
8
6
15
4
10
2
0
01/31/96
09/30/97
05/31/99
01/31/01
09/30/02
05/31/04
01/31/06
09/30/07
5
-2
-4
CPI, YOY
M1, YOY
0
Source: Bloomberg, CPI at left scale
Using ANOVA regression analysis, I generate the below statistics
and plot a chart based on real-time data used in the above graph.
Confidence interval is set at 95%. The adjusted R2 is only 3.58% and the
P-value of the F-statistic (significance F) is not large, but these could be
caused by the single variable model. No zero can be found within the
confidence interval – between lower 95% and upper 95%. Additionally
X-variable’s P-value is also sufficiently small at 0.97%, suggesting there
is a low likelihood that the slope of the regression line is a non-zero value
by chance, so the slope is considered statistically significant. The line fit
59
plot shows there is a certain correlation but the model’s explanatory
power is low.
Regression Statistics
Multiple R
0.204603378
R Square
0.041862542
Adjusted R Square
0.035759756
Standard Error
2.95196355
Observations
159
ANOVA
df
1
157
158
SS
59.77497658
1368.111942
1427.886918
MS
59.7749766
8.7140888
Coefficients
-0.43659844
0.16470136
Standard Error
1.007140045
0.062885203
t Stat
-0.433503212
2.619079713
Regression
Residual
Total
Intercept
X Variable 1
F
Significance F
6.859578545
0.00968095
P-value
0.665244275
0.009680953
Lower 95%
-2.42589196
0.04049110
Upper 95%
1.552695076
0.288911621
X Variable 1 Line Fit Plot
12
Y
10
Predicted Y
8
Y
6
4
2
0
-2
-4
0
5
10
15
20
25
X Variable 1
The Granger Casualty test results between M1 and the CPI are
shown below. As p-value is almost at zero, the null hypothesis that M1
does not ‘Granger Cause’ CPI can be rejected. Thus, I can conclude that
60
M1 ‘Granger Cause’ CPI.
If CPI lags behind M1, could statistics fit better if I use real-time
M1 data but lagged CPI? After six month-by-month tests, I find that CPI
lags half a year behind M1, shown in the below graph. The troughs and
peaks almost fit perfectly.
Chart 11
6-month lagged CPI & M1
61
10
25
8
20
6
15
4
2
10
0
07/31/96
03/31/98
11/30/99
07/31/01
03/31/03
11/30/04
07/31/06
03/31/08
5
-2
CPI, YOY
-4
M1, YOY
0
Now I conduct the regression analysis based on the 6-month
lagged CPI data and M1 data. The following results were generated. Now
we have a much higher adjusted R2. Meanwhile, coefficients, P-value and
t-statistics are all more significant and zero again does not fall inside the
confidence interval. In comparison with the last test, the results can be
displayed more vividly in the below fit plot chart. Thus, the null
hypothesis can be rejected. There is a correlation between CPI and M1.
Inflations seem to be associated with a rapid increase in money supply
(also see chart 11).
62
Regression Statistics
Multiple R
0.47762054
R Square
0.22812138
Adjusted R Square
0.22300960
Standard Error
2.38582949
Observations
153
ANOVA
df
SS
254.0228168
859.5195361
1113.542353
MS
254.0228168
5.692182358
Coefficients Standard Error
-3.88396374
0.8798856
0.36297115
0.0543344
t Stat
-4.414169002
6.680315306
Regression
Residual
Total
Intercept
X Variable 1
1
151
152
F
Significance F
44.62661258 4.30001E-10
P-value
Lower 95%
Upper 95%
1.92063E-05 -5.622441648 -2.145485831
4.30001E-10 0.255617178 0.470325118
X Variable 1 Line Fit Plot
10
8
Y
Predicted Y
6
Y
4
2
0
-2 0
-4
5
10
15
20
25
X Variable 1
The Granger Casualty test between CPI and the Shanghai
Composite Index returns the following results. Due to the low p-value of
0.0014, I conclude that the null hypothesis can be rejected. Therefore, the
Shanghai variable ‘Granger Causes’ the CPI variable.
63
Shanghai, CPI and M1
Now I know both CPI and M1 are correlated to stock market. If I
create a model with lagged CPI and M1 as variables, will it increase the
correlation significance to the Shanghai Composite Index? The results are
shown in the table below. Now adjusted R-squared is higher than the
single factor equation with M1 or CPI in the above results.
Correlation Matrix
Shanghai
M1
Lagged CPI
Shanghai
1.000000
0.600643
0.542435
M1
0.600643
1.000000
0.477621
Lagged CPI
0.542435
0.477621
1.000000
64
The above results conclude that the stock market is highly
correlated to M1 and the CPI. Stock market changes ‘Granger Cause’ M1
and inflation indicator CPI to fluctuate. Stock markets appear to lead
money growth rates9. Thus the findings suggest stock market efficiently
digests and incorporate news about monetary policy. Stock markets move
simultaneously with M1 while CPI lags by several months. The
year-on-year growth of M1 and the Shanghai Composite Index also
indicates that Chinese investors are not always speculative during normal
times as most people believe to be. In reality, M1 and M2 could not
include all money supply in China due to the large amount of trade
surplus in recent years. Additionally, due to China’s foreign currency
9
See, for example, Rozeff, ‘Money and Stock Prices’ (1974), Kraft and Kraft, ‘Determinants of
Common Stock Prices’ (1977), and Rogaiski and Vinso, ‘Stock Returns, Money Supply and the Direction
of Causality’ (1977).
65
control, households largely hold some amount of foreign currencies
which is normally not affected by the stock market performance.
2.3.
Results – Interest Rate
The graph below exhibits the one-year real deposit rate movement
in comparison with the Shanghai Composite Index and trading volume
from 1994 to 2007. The dramatic decline of interest rate barely affected
people’s trading activities till 1998 looking at trading volume, though the
stock market climbed from 1995 to 1997. Less trading volume but higher
index price means the index increase was driven by higher stock prices.
Government continued a contracted monetary policy in 1998 and 1999
but this barely helped to lift market prices, neither was there an increase
in trading activities. Although the extreme interest rate decrease from
1995 to 1999 was meant to expand economic growth, from the
government’s point of view, the stock market failed to react to such
stimulation. The rally in 2000 followed by the expansionary monetary
policy suggests there is a lag between the initiation of policy and market
reaction, which is contrary to efficient market theory. In the mean-time,
interest rate stayed flat in 2000 and 2001 when markets experienced the
Internet Bubble. The bear market continued until the end of 2002 when
the lower interest rate did not immediately turn the market around.
Trading volume development from 2003 onwards suggests people started
to trade more actively. But the stock market reaction was the opposite
until 2005 when the stock reform began. After then, both trading volume
and stock index moved in the same direction as the increase of interest
rates. People appeared to welcome the new round of stock reforms that
66
government determinedly carried out. The fact that the stock index
ascended at a faster pace than trading volume from 2005 is the evidence
of a swifter stock price increase.
Chart 12 Interest Rate vs. Trading Volume and Shanghai Composite Index
Shanghai
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
Trading Volume
One-year Deposit Rate
Source: NBSC, the People’s Bank of China, Bloomberg
Looking at more recent data starting from 2007, it is easier to
identify patterns, especially facing a crisis. The graph below depicts the
most recent deposit rate changes in comparison with the Shanghai
Composite Index. Being aware of the overheated stock market, authorities
67
aggressively lifted the interest rate six times during the course of 2007.
The stock market started to descend after the fifth interest rate increase.
Assuming the tremendous drop from the end of 2007 to 2008 reflect the
series of interest rate increases, the rate decreases from December 2007 to
December 2008 shall bring about a certain level of recovery, which is
shown from October 2008 till the present. The movement of the stock
market displayed below together with the phenomenon discussed above
strongly suggests that there is significant delay of the implementation of
monetary policy to the realization in the stock market.
Chart 13-1
One-year Deposit Rate v.s. Shanghai Composite Index
One-year Deposit Rate
2009.04
2009.03
2009.02
2009.01
2008.12
2008.11
2008.10
2008.10
2007.12
2007.09
2007.08
2007.07
2007.05
2007.03
Shanghai
68
Source: the People’s Bank of China, Bloomberg
It is interesting to see that the interest rate and stock index lines
start from the same level and end at the same place again. It may be
concluded that the stock market and interest rate move in a rotated ‘Z’
circle during the crisis when government intervenes with monetary tools.
The tendency of both movements is perfectly identical though with
different scales. The upper shadowed area means there is excess demand
of stocks in the market which overrules the effect from the increase of
interest rates, while the lower shadowed part means supply of stocks is
larger than the correction impact created by interest rate decreases. Thus,
theoretically, if the government would have the cognitive ability to
predict the forthcoming overheating of the markets, it could have started
to implement a contracted monetary policy in advance or increase the
interest rates at a larger scale and begin to decrease the interest rate before
the stock market overacts and goes into a recession. The chart below
illustrates the Federal Reserve fund rate changes in comparison with the
Dow Jones Index from 2001 (after the Internet Bubble) till the current
financial crisis (the end of 2008). A clear ‘Z’-shaped interest rate curve
can also be witnessed. The time span however is much larger, at a
seven-year interval. The valley of interest rates after Internet Bubble in
69
the middle of 2003 corresponds to the trough of the Dow Jones Index.
The peak of the interest rates at mid 2006 is one year too early. The stock
market climbed remarkably after the interest rate cuts. This may have
resulted in a large amount of ‘malinvestments’ (speculative or Ponzi
finances) when some investors borrowed money as they expected higher
future profits to cover the costs, possibly one of the causes of the present
credit crunch.
Chart 13-2
US Federal Fund Rate v.s. Dow Jones
6
14000
5
13000
4
12000
3
11000
2
10000
1
Fed Fund Rate
0
4/18/2001
9000
DOW
8000
10/2/2001
6/30/2004
2/2/2005
9/20/2005
5/10/2006
1/22/2008 10/29/2008
Source: US Federal Reserve System
Would it be possible that the discrepancy between policy change
70
and stock market fluctuation is caused by the consumer behavior? Let’s
look at the graph below which illustrates the latest interest rate and CPI
changes. We can see from the chart that the consumption behavior has not
reacted to the change of interest rates simultaneously. The increase of
interest rates from the beginning to the end of 2007 only started to exert
influence on people’s consumption style from April 2008; and the
decrease of interest rates during 2008 started to revise the dropping goods
and services price from February 2009. This signifies that consumers
keep their consumption pattern till they realize the effect from interest
rate changes. It might not be hard to explain such phenomenon. The price
of goods and services would change more apparently when affluent
consumers start to alter their consumption patterns.
Chart 14
Interest Rate v.s. CPI (rebased), %
71
10
8
6
4
2
One-year Deposit Rate
CP I
0
2009.03
2009.01
2009.02
2008.12
2008.10
2008.11
2008.08
2008.09
2008.07
2008.05
2008.06
2008.03
2008.04
2008.02
2007.12
2008.01
2007.10
2007.11
2007.09
2007.07
2007.08
2007.05
2007.06
2007.04
2007.02
2007.03
2007.01
-2
Source: NBSC
As herd instinct suggests, people are inclined to follow a larger
group as information does not spread efficiently. When a greater number
of people begin to switch their preferences, such impact disperses even
quicker. Contrary to efficient market theory which assumes information
gets out quickly, such phenomenon can well explain the lag discussed
above. An ongoing survey conducted online by JRJ.com shows that
people are well aware of the purposes of government interest rate changes.
However, the consumption pattern does not change immediately when
72
interest rates change.
Chart 15 Survey on Interest Rate Changes
13.95%
39.09%
19.15%
27.81%
Reduce co nsumptio n
Depends o n needs
B uy real estate as so o n as price dro ps
B uy real estate o r car
2.4.
Results – Bank Reserve Ratio and Open
Market Operations
Since 2003, the People’s Bank of China raised the deposit reserve
ratio from 6% to a high of 17.5% at the middle of 2008. Beijing then
reduced the ratio by 2.5% by the end of 2008 aiming to overrule the
dropping market. The graph below displays all the deposit reserve ratio
changes since 1998 in contrast with the Shanghai Composite Index. The
curves suggest that the higher reserve ratio has doubtful contemporaneous
influence on stock markets, at least till the end of 2007. A lower bank
reserve requirement starting from mid-2008 could not produce an
73
immediate effect either. Looking at the actual securities investment of
financial institutions from 1994 to 2007, it is not difficult to understand
why the bank deposit reserve ratio change did not post significant impact
on the stock markets; the total investment in securities was always below
14.5% of the overall fund usage.
Chart 16 Deposit Reserve Ratio v.s. Shanghai Composite Index, rebased
500
400
300
200
100
Bank Reserve Ratio
Shanghai
98.03
99.11
03.09
04.04
06.07
06.08
06.11
07.01
07.02
07.04
07.05
07.06
07.08
07.09
07.10
07.11
07.12
08.01
08.03
08.04
08.05
08.06
08.09
08.10
08.11
0
Chart 17
Overview of Investment on Securities
74
16%
14%
12%
10%
8%
6%
4%
2%
0%
94 95 96 97 98 99 '00 '01 '02 '03 '04 '05 '06 '07
Source: NBSC
China’s bank deposit reserve ratio system was initiated after the
setup of the People’s Bank of China. In 1984, the deposit reserve ratio
was set according to the deposit type: corporate deposits at 20%, deposits
of rural regions at 25%, savings deposits at 40%. The high reserve
requirement limited the lending capacity of commercial banks. In 1985,
the deposit reserve ratio was fixed at 10%. In 1987 and 1988, in order to
prevent inflation and concentrate on key project financing, government
raised the deposit reserve ratio to 12% in 1987 and to 13% in 1988
respectively. In 1989, banks were required to keep a certain amount of
75
cash, called cash reserve ratio, in order to satisfy withdrawal demand. The
cash reserve ratio was set between 5% and 7%. In 1995, the People’s
Bank of China adjusted the cash reserve ratio according to the
characteristics of commercial banks. Bank of China and Industrial and
Commercial Bank of China were required to keep at least 6% of cash.
This ratio was set at 5% for both China Construction Bank and Bank of
Communications and 7% for Agricultural Bank of China. The deposit
reserve ratio was stable till 1998 when China enhanced the transition of
its economy and started to reform the banking system. The deposit
reserve and cash reserve were merged into one reserve deposit account.
The legal deposit reserve ratio was lowered thereafter from 13% to 8%
and any excess reserves can be decided by banks independently. Since
2003, some banks exhibited strong credit expansion but some of them
began to lose capital adequacy and asset quality. From 2004, government
applied different reserve ratio requirements based on asset quality and
capital adequacy ratios.
Most countries try to avoid changes in bank reserve ratios as such
changes can lead to a sudden shortage of credit and consequently result in
production/construction postponement. Most countries do not favor the
use of bank reserve ratios due to their rapid and dramatic effects. Instead,
76
rediscount rates and open market operations are preferred by most
western authorities. Rediscount rate is the rate of interest charged when a
bank borrows money from a central bank. A lower rediscount rate means
a commercial bank can borrow money at a lower cost from a country’s
central bank. This increases the currency in circulation and thus directly
increases money supply. However, the use of rediscount is in the hand of
commercial banks, not the government. The government can only adjust
rediscount rate and passively wait for the response of commercial banks.
The People’s Bank of China started the use of rediscount rates from
September 1, 1988. The rediscount has not accounted for a large amount
of China’s money supply however. The commercial credit of China is
generally relatively low and the commercial paper market is young. As
China executed a planned economy, it had direct control and
administration over credit. Commercial credit was therefore highly
limited, resulting in a dominant position of banks in social credit.
Open market operations refer to the action that a central bank
controls money supply by buying or selling government bonds or other
financial instruments. When money flows into the market as bonds are
repurchased, it increases the total money supply. When money flows into
commercial institutions, it stimulates credit expansion and in turn creates
77
an increase in money supply. In China, the Law on the People’s Bank of
China allows the central bank to purchase treasury bonds, other
government bonds and foreign exchange. In recent years, China has
begun to engage more and more in open market operations.
The following graph shows bond repurchase trades since 200210 to
March 2009, in comparison with the Shanghai Composite Index.
Government increased the bond repurchases from 2002 to 2004, and
thereafter gradually decreased these until the end of 2006. The huge
capital inflow contributed to double-digit economic growth. Stock
markets however, only started the bull run when repurchases faded. Due
to the limitation of data, I can hardly conclude the repo trading has a
five-year cycle. Nonetheless, it does necessarily exhibit a symmetric peak
with the stock market, which is worthy of note.
10
Data only available since 2002 from the People’s Bank of China website.
78
Chart 18 Repo. Trading v.s. Shanghai Composite Index
5600
6500
Repo
Shanghai
4800
5500
4000
4500
3200
3500
2400
2500
1600
1500
800
0
2002.01
500
2003.01
2004.01
2005.01
2006.01
2007.01
2008.01
2009.01
Source: the People’s Bank of China, repurchase amount (left y-axis) in 100
million yuan.
Theoretically, the larger the repurchases, the more stock markets
benefit. This theory does not seem to be true for the real time data. The
below regression and correction results de facto lead to a negative
relationship.
79
Regression Statistics
Multiple R
0.308236759
R Square
0.0950099
Adjusted R Square
Standard Error
Observations
Repo
Shanghai
Correlation Analysis
1
-0.30823676
1
0.084362957
75.20221661
87
ANOVA
df
Regression
Residual
Total
Intercept
X Variable 1
SS
50466.73875
480706.7375
531173.4763
MS
50466.73875
5655.373383
F
Significance F
8.92367936 0.003678027
Coefficients Standard Error
183.8276626 16.82890639
-0.362246977 0.121264252
t Stat
10.9233279
-2.98725281
P-value
Lower 95%
Upper 95%
7.2684E-18 150.3672679 217.2880572
0.00367803 -0.603352942 -0.121141012
1
85
86
X Variable 1 Line Fit Plot
450
400
350
300
250
200
150
100
50
0
Predicted Y
Y
Y
0
100
200
300
X Variable 1
The year-on-year returns however display a positive correlation
though it is not very significant. The analysis results and the graph are
shown below.
80
Regression Statistics
Multiple R
0.29130533
R Square
0.08485880
Adjusted R Square
Standard Error
Observations
Repo, YOY
Shanghai, YOY
Repo, YOY Shanghai, YOY
1
0.2913053
1
0.07232261
0.67653478
75
ANOVA
df
Regression
Residual
Total
1
73
74
Intercept
X Variable 1
SS
3.09821725
33.41204955
36.5102668
Coefficients Standard Error
0.17110835 0.081451598
0.17063871 0.065586093
MS
F
Significance F
3.09821725 6.769110614
0.01122366
0.45769931
t Stat
P-value
2.100736569 0.039117876
2.601751451 0.011223663
Lower 95%
0.00877544
0.03992573
Upper 95%
0.33344126
0.30135170
Chart 19 Repo. Trading v.s. Shanghai Composite Index
800%
300%
Repo, YOY
Shanghai, YOY
600%
200%
400%
100%
200%
0%
0%
-200%
2003.01
-100%
2004.01
2005.01
2006.01
2007.01
2008.01
2009.01
Source: the People’s Bank of China, Bloomberg
We can see from the above graph that the year-on-year decline of
81
bond repurchase from 2004 till 2007 did not influence the stock market
development. The sudden increase of repurchase scale starting from 2007
however coincides quite clearly with the jump of the Shanghai Composite
Index. As bond repurchases lead to the increase of money supply
ultimately, it should increase the correlation with the stock market. I add
bond repurchase year-on-year returns (REPOYOY) as an additional
variable into the regression equation. The results are shown below. The
adjusted R-squared increases to 70% and the Akaike information criterion
is lower than the earlier results with only M1 or lagged CPI as variables.
But the p-value of M1 increased dramatically and the coefficient of bond
repurchase turns out to be negative. Thus, bond repurchase does not fit
into the estimate so M1 and lagged CPI are more accurate factors in the
equation to estimate stock prices.
82
Interest rates and bank deposit reserve ratios together can control
bank lending activities. Domestic financial institutions have been
squeezed by low interest rates which dented the profits they can earn on
their huge base of customer deposits. On the other side however, strong
lending and treasury activities can generate respectable revenues. We can
see from the image below that except for the stock market bubble in 2007
to 2008, the general tendency is identical between M2, bank loans and
stock markets. Particularly RMB loans extended reached all-time highs in
March 2009. China’s banks released a record RMB 4.6 trillion in new
loans during the first quarter of 2009 in support of government efforts to
83
revive the economy. The March Goldman Sachs China Financial
Conditions Index loosened by the largest amount in single-month
movement history. A stronger increase of bank loans (displayed below)
than M2 suggests the capital has flowed into the real economy, mainly
fixed asset investment.
Chart 20 M2, Bank Loan Ratio and Shanghai Composite Index
M2
Bank Loan
Shanghai
1,000
Source: NBSC, CEIC, UBS. Left scale is the growth ratio of M2 and bank loan,
right scale presents the stock index level logarithmically.
The extreme jump of bank lending in the first quarter of 2009 was
generated by the expansionary monetary policy and government stimulus
84
measures (to be discussed in the next chapter). The fast increasing bank
lending raised worries of bad loans which arose in the 1980s and 1990s
when bank loans went into low quality SOEs and projects during reforms.
In the 1980s enterprise autonomy was introduced for the SOE reform.
Insufficient controls were imposed on the expansion of credits that SOEs
got directly from banks while banks were mistakenly given autonomy in
the same way. Aggregate demand and national output were expanded at a
fast speed. The government thereafter assigned credit quotas to banks in
difference regions, together with higher deposit rates. In the 1990s the
credit expansion was carried out on the back of increasing investments
after the Southern Expedition of Deng Xiaoping. The same administrative
methods applied in the 1980s were used to blow away the new round of
inflation. What the banking authorities did to solve all the bad loans
accumulated was to inject capital into banks and set deposit rates above
lending rates. The consequence was that the government allocated capital
which should be consumed by households to cover any potential bank
losses. Regulators also artificially lowered the deposit and lending rate in
order to slow down the increase of bad loans in order to support banks’
operational profits. This results in the fact that production surpassed
demand. Thus the government had to rely on exports to absorb the excess
85
supply. The ongoing global recession reduced the import capacity of
partner countries forcing China to overhaul its strategy. Learning from the
past, the government promulgated various regulations and rules to
monitor the credit usage carefully. The Ministry of Industry and
Information Technology recently announced that for those steel
corporations, whose excess production could not be supported by the
market, the government will forbid banks to extend additional loans to
curb production expansion. The latest statistics suggests household
lending accounted for 25% of the April’s new loan, compared with 9.2%
in March. Middle and long-term infrastructure construction accounted for
63% of the April’s new loan. This implies liquidity is flowing into the
right direction.
Consequently domestic financial companies outperformed the
Shanghai Composite Index in the first four months in 2009. The robust
profits were also reported from foreign banks’ mainland business
including HSBC which said its pretax profits increased by 137% mainly
by trading local currencies, bonds and derivatives for major corporate
clients. Citigroup also reported its net income for 2008 in the country
increased by 95% amounting to USD 191 million.
Chart 21
Financial Index v.s. Shanghai Composite Index
86
180
Shanghai
Financials
160
23.7%
140
120
4/24/2009
4/3/2009
3/13/2009
2/20/2009
1/23/2009
12/31/2008
100
Source: Bloomberg
A Case Study
Now let’s look at a specific event before the current global financial
crisis. In the year of 1998, the central bank decreased its one-year deposit
rate three times, from 5.67% to 3.78%, a total of 33.33%. However
except the first rate correction when the market reacted slightly, the later
two adjustments did not stop the market from dropping. The reason may
be explained examining the following factors (data sourced from NBSC
and the Ministry of Commerce):
87
a)
The total fixed capital investment increased 15% in the
year of 1998, higher than the 10.1% of 1997. Such an
increase was due to the expansionary fiscal policy which
enhanced
infrastructure
construction
investment.
Investment of non-SOEs and foreign invested companies
declined by 2% and 8.9% respectively compared with
1997 however. Hence the investment hike was only
created by the government’s fund injection (fiscal policy).
Monetary policy did not play a role in stimulating
non-government entities' investment behaviors.
b)
From 1993 to 1998, GDP declined from 13.5% to 7.8%
gradually. The poor macroeconomic situation made
people more cautious in their investment outlook. A
lower interest rate is supposed to ease corporate debt.
The average SOE asset-liability ratio was as high as 80%.
The total loss for SOEs in 1998 was RMB 12.7 billion,
20% more than the year before; and the year-end
inventory increased by 5.5% than 1997. Furthermore, an
essentially heavier taxation was implemented. Although
the government increased spending, the total taxation
88
increased by 13.3%, compared with a GDP growth of
7.8% and an industrial value-added growth of 8.8%.
c)
The discrepancy between actual interest rate and price
index changes: the total nominal decrease of interest
rates in 1998 was 1.89% but the price dropped at a faster
pace of 3.4%. GDP grew 7.8% in 1998, quicker than total
consumption which was up 6.8%. Additionally, the retail
price index was 2.6% lower than 1997, decreasing at an
annual 8.2% rate from 21.7% in 1994 year-on-year.
Consumers thus anticipated further decline of prices,
which hindered spending. Total bank deposits were up
18% in 1998, growing much faster than GDP. Meanwhile
the total turnover of the Shanghai and Shenzhen stock
markets decreased by 23.4% despite the fact that 106
new companies were listed in 1998.
d)
The central bank’s contradictory monetary policy: on one
hand, the deposit and lending rate decrease attracted
capital to flow out of the banks. On the other hand, the
government did not increase money supply at the same
pace. M0, M1 and M2 grew 10.1%, 11.9% and 15.3%
89
year-on-year respectively in 1998, which was 4%, 5.4%
and 6.2% respectively slower than 1997.
In general, I observe a strong relationship between China’s stock
market and interest rate changes. As monetarists suggest, the change of
interest rate potentially increases capital flows. The realization of such
policy change, however, posts delayed effects on stock markets. It is fair
to conclude that the Chinese government has made the necessary efforts
to guide the market despite several limitations. Firstly, it is not easy to
foresee what is about to happen due to the restriction of cognitive
knowledge as the economy is in transition. Secondly, interest rate control
in China limits its possible floating range. Although in 2004, the People’s
Bank of China loosened such limits and started to marketize interest rate
adjustment; lower limit of loan rate (not lower than 90% of the
benchmark rate) and higher limit of deposit rate (not higher than the
benchmark rate) still persist. Thirdly, the time-lag effect of monetary
policy decreases its regulative function. Last but not least, in China,
people’s main purposes to make bank deposits are for retirement pension,
medical service and children’s education. Such social behavior means the
change of interest rate has a comparatively limited impact in comparison
with western economies where social security is more advanced.
90
Chapter Three
Fiscal Policy
Fiscal policy refers to government attempts through changes in tax,
bond, government expenditure, and allowance etc, to influence the
direction of the economy. When government spending equals to tax
revenue, it is a neutral fiscal policy. Increasing spending or reducing tax
revenue is an expansionary fiscal policy, resulting in a budget deficit.
Oppositely, contractionary fiscal policy occurs when net spending
declines and is compensated by higher tax revenue or less spending or a
combination of the two. This would lead to a budget surplus. Such a tight
policy is implemented if inflation is high, in order to achieve price
stability. Cutting spending is often difficult because spending benefits
politically influential interest groups (Alesina and Perotti, 1995). Such
problems however are less significant in China due to its single-party
dominance.
Keynesian economics suggests that adjusting state spending and tax
rate are the best ways to stimulate aggregate demand – the total demand
for final goods and services in the economy at a given time and price
level. Thus in Keynesian theory, fiscal policy is a distinct demand-side
91
instrument. The government can affect aggregated demand directly
through its own expenditure and indirectly by taxation. While in a
monetarist’ view, government budget has important supply-side effect but
has no demand-side function unless it triggers changes in monetary policy.
In times of recession or low economic activities however, fiscal policy
would be essential and an efficient tool to stimulate speedy recovery or
growth. In theory, deficits can be paid then by an economy boom that
would follow. This theory is naturally proved by the current large rescue
plans initiated worldwide.
Economic fundamentals shall be the prerequisite of the development
of stock markets. The supply of stock return in theory is generated by the
productivity of companies in the real economy. In absence of a strong
economy, bubbles are easily produced. In 1978, the state revenue was
only a bit more than RMB 100 billion (USD 12 billion), occupying
31.24% of the GDP. This exhibits a heavy burden on households. In the
next 18 years till 1995, the income increased 11.87% on an annual basis.
In 1995, the revenue to GDP ratio decreased to 10.67%, meaning a much
higher household income. The new fiscal policy starting from 1994 has
changed largely the proportion between state income and GDP. From
1996 to 2007, state revenue increased at a faster pace than GDP. In the
92
last 5 years from 2003 to 2007, the wealth has been increasingly
accumulated by the state. The moderate macro control has provided a
good environment for stock markets. In the late 1990s, the bust of the
Asian financial crisis led to a drop of prices of goods, higher
unemployment, lower investment and consumption, and consequently
slower economic growth. An expansionary fiscal policy was adopted
since then till 2005 when the government switched to a steady fiscal
policy.
Chart 22
State Revenue and GDP, rebased in RMB billion
10,000
1,000
100
State Revenue
Rebased GDP
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
10
Source: NBSC
93
The scale of government bond issuances is the primary
consideration for government bond management. Authorities have to take
into account both consumers’ purchasing power and the government’s
repayment capability. The purchasing power of government bonds can be
categorized as macro and micro factors. The macro factor is related to a
country’s GDP while the micro factor refers to bank deposits. The
worldwide recognized practice is specified in the excessive deficit
procedure of the Treaty of Maastricht which defines that gross debt of the
government should not be above 60% of GDP. China’s deficit rate is quite
low in this sense and also in comparison with most countries. The ratio
was increased from 1% in 1981 (the first government bond issuance) to
19.7% in 2008. The increasing government debt ratio has fueled mainly
infrastructure improvement, contributing to economic growth. Spending
now would have to be paid in the future, either by bond issuance or
higher taxation. It is important to maintain the confidence of the public on
the long-run sustainability of the fiscal system; otherwise any
discretionary
short-term
expansion
of
fiscal
policy
will
have
counterproductive effects.
Chart 23
Burden Ratio of National Debt
94
25
20
15
10
5
0
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Source: National Debt Association of China
This chapter will analyze the impact of fiscal policy on stock
market in three perspectives: government spending, government bond and
taxation policy. The analysis is based on the empirical data analyzed
using descriptive statistics, regression model and portfolio allocation
theory. In taxation section, I’ll analyze the turnover velocity of the
Shanghai Composite Index.
3.1.
Results – Government Spending
State budget reflects the economic scale, balance and direction of a
country. Increasing government spending is the main tool in expansionary
95
fiscal policy. Government can finance its spending by either taxation or
issuing bonds. The result normally helps to lift stock prices. Public
spending however, shall reflect both microeconomic and macroeconomic
considerations.
The chart below illustrates the change of government spending and
the Shanghai Composite Index from 1990 to 2007. We can see from the
graph that although the general tendency is the same – trending both
upwards, the stock index appears to exhibit greater volatility. In the
period from 1990 to 1992, the stock market was first born, leading to
what one can call a start-up rally. A natural cool-down is witnessed from
1993 to 1995. The market seems to be more in line with the government’s
spending tendency from 1995 onwards. Similar to interest rates, we can
see from the image that stock market often indicates a time lag after the
change of government spending. For instance, the sudden increase of
spending from 1997 to 1999 may correspond to the market rally from
1998 to 2002, so does the period from 2004 to 2007 where a flat
expenditure seems to echo to a slight drop of the market.
Chart 24 Government Spending v.s. Shanghai Composite Index, rebased
96
10,000
Government
Shanghai
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
100
Source: NBSC
Compared with monetary policies, government spending change
creates more immediate impact on domestic economic growth and
consequently benefits the stock market. In 2008, state budget financing
accounted for 62.2% of the total urban fixed asset investment, while
domestic loans and self-raised funds financed 15.7% and 4.7%
respectively. Since the economic slowdown became apparent in the last
quarter of 2008, the government swiftly shifted to a pro-growth policy.
The two-year RMB 4-trillion stimulus measures taken by the central
government to fight the global financial crisis have proved to be effective
in various aspects. Aiming at increasing the financing of the stimulus plan,
97
China Insurance Regulatory Commission specified that life and property
insurance companies could invest as much as 6% and 4% of their total
assets respectively (based on Q1 2009) on infrastructure projects. The
stimulus package will be spent in the following manner.
Chart 25
7%
Stimulus Plan
4% 1%
9%
45%
9%
25%
Transport&Power Grid
Rural
Public Housing
Healthcare and Education
Sichuan Reconstruction
Environment
Innovation
Source: National Development and Reform Commission
It can be seen in the following economic indicators that
consumption and industrial production rebound instantly after the
implementation of the stimulus package since the beginning of 2009. The
Shanghai Composite Index climbed from 1820.81 at December 31, 2008
to 2477.57 as of April 30, 2009 registering an increase of 36% within four
months, a monthly 8% average growth. It can be seen from indicator PPI
98
that inflation pressure has been decreasing from September 2008. The
dropping speed is somewhat softening in 2009, whereas PMI and value
added of industry both registered strong rebound. Similar trends are
witnessed in the UK, Japan and the US after the government stimulus
plan implementation.
Chart 26 Various Economic Indicators’ Reactions to Stimulus Plan
15
10
5
0
PPI, YOY
-5
-10
Jan-99 Jan-00 Jan-01 Jan-02 Jan-03 Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09
99
29
Value Added of Industry, State-owned
19
9
-1
Jan-99 Jan-00 Jan-01 Jan-02 Jan-03 Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09
60
50
Manufacturing PMI
40
30
Jan-05 Jun-05 Nov-05 Apr-06 Sep-06 Feb-07 Jul-07 Dec-07 May-08 Oct-08 Mar-09
100
Source: NBSC, China Federation of Logistics and Purchasing, Bloomberg
The main driver of the acceleration is the strong increase of fixed
asset
investment
driven
by
such
government-led
infrastructure
investments. Nonetheless, self-raised funding shall accordingly increase
as business confidence improves on the back of better-than-expected
domestic demand growth. The most recent data provided by CEIS
suggests there are already signs of rebound in non-public investment
growth, especially in the property and commodity spaces (see chart
below). Within the 1405 companies which reported first quarter earnings
by the end of April, 1048 of them reported a profit, accounting for 74.6%,
in which 33.5% of them realized a net profit growth. Together with low
credit costs, fixed asset investment growth is expected to remain firm as
bank loan growth start to slow as government policy gradually normalizes.
A domestic demand rebound thereafter will create higher returns and
stronger confidence for private investment opportunities as the result of
increasing income transfers from government to households.
Chart 27 Non-infrastructure Investment Growth
101
Source: CEIS, GS Global ECS Research
Government expenditure can not only be directly injected into fixed
asset investment, it can also help to restructure inefficient SOEs. Many of
the SOEs were facing poor management and low efficiency levels in
China. To format a consolidated layout, in 2005, the government spent
RMB 22 billion on closing down 115 SOEs and resettled more than
590’000 people. The second phase was thereafter pushed forward by
isolating organizations set up by SOEs, typically schools, hospitals and
service companies. The authorities supported structural change and
debt-to-stock conversion, promoted the reform in industries such as
102
electricity, telecom, railway, airline and post, and strengthened the
11
financial supervision of the four state asset managers . These structural
changes have greatly improved these large enterprises’ competitiveness.
The present financial crisis has proved to be a benefit for the better-run
companies as the export slump has actually done a useful job of clearing
out the dead wood as businesses gravitate to the better run companies
producing higher quality items. To preserve industry development,
National Development and Reform Commission recently unveiled a steel
industry revitalization plan. The plan intends to reduce steel output by 8%
in 2009 compared with 2008, and then gradually increase again in 2011.
Additionally government will strengthen elimination of outdated capacity,
revise import tax and raise export VAT rebate rate for high-tech and high
value-added steel products. The steel industry will attract as much as
RMB 1 billion on support of R&D and technical reform, according to the
Industry & Information Technology Association. Government’s action on
promoting M&A and increasing industry concentration rate will
restructure the whole steel industry and generate three super-large steel
makers – Bao Steel Group, An Steel Group and Wu Steel Group. Such
consolidation and restructure attempt also applies to the automobile
11
These companies are China Cida Asset Management Corporation, China Orient Asset Management
Corporation, China Great Wall Asset Management Corporation, China Huarong Asset Management
Corporation.
103
industry. The revitalization foresees the establishment of 2 to 3
super-large automakers with an annual production volume of more than 2
million vehicles and 4 to 5 giant companies whose annual production
volume shall surpass 1 million vehicles. If it goes as planned, there will
be less than 10 manufactures in China’s market controlling 90% of the
market share (presently controlled by 14 players). Further plans outlined
are the revitalizing and restructuring of the country’s light industries and
petroleum refining sector. The outline for the refining sector will raise
crude oil processing capacity by about 18% by 2011 and the government
plans to build three or four major large, modern refineries in the Yangtze
River Delta and the Pearl River Delta. The plan for the light industrial
sector is meant to upgrade technology and provide more support for
SMEs which suffer from a lack of access to bank loans and other
financing. These two plans are expected to create about 3 million jobs for
the country.
Although government investment has an instant impact on the
domestic economy, self-generating growth from factors like employment
and domestic consumption is the key in order to maintain sustainability
and to offset the deterioration in exports arising from the present global
financial crisis. A structural change of economy is needed. A large part of
104
China’s success over the years has been to manufacture goods at cheap
labor cost and sell them mainly to the US and Europe. The government
realizes that the real market may be domestic however, and is now trying
to break its dependence on exports as the mainstay of its economic
growth to one relying more on its internal dynamism. The previous
disasters from the centrally planned economy and less sophisticated social
security have taught Chinese consumers the importance of saving and
fiscal prudence, a sharp contrast to the American style of living. As a
result a strong household balance sheet has offered families a measure of
protection against possible downturns. In early 2009, people began to
spend fairly freely again, even though the news from the global economy
seemed to get worse and worse. A survey conducted by China
Confidential assessed consumer spending intentions among an estimated
64-million middle and upper income households in 189 cities in March
2009. The results suggest there is a much higher propensity to spend in
lower-tier cities which have been hit less by the global downturn (less
dependent on exports) than the traditional growth powerhouses clustered
around the Yangtze and Pearl River deltas. Average sales revenues for
nine of China's top 10 retail companies bounced back 8.49% year-on-year
in the first quarter of 2009. Companies like Wal-Mart plan to expand its
105
network further in second-tier cities to capture the spending power of
inland consumers. China's nominal retail sales reached RMB 10 trillion in
2008 with an annualised growth rate of 17.8% per year over the last five
years. According to a new forecast from TNS Retail Forward, China will
surpass Japan becoming the second-largest retail market after the US.
Retail sales in the first quarter of 2009 remained robust, growing at a 15%
year-on-year pace (N.B. Feb data may be affected by Spring Festival),
while CPI and PPI inflation remained negative in April according to the
National Bureau of Statistics. Despite all these robust figures, it is hard to
build up consumer confidence in general.
Domestic consumers’
confidence and expectation has been decreasing since September 2007.
The chart below suggests despite the decent recovery in all sectors,
consumers still are relatively conservative in light of crisis.
Chart 28 China’s Consumer Confidence and Expectation
106
110
115
Consum er Confidence
Consumer E xpectation
110
105
105
100
100
95
95
90
90
85
85
80
80
1/31/1991 1/31/1993 1/31/1995 1/31/1997 1/31/1999 1/31/2001 1/31/2003 1/31/2005 1/31/2007 1/31/2009
Source: Bloomberg, 1997=100, consumer expectation at right scale
The structural growth of consumption comes from drivers like the
ongoing urbanization, a rapidly evolving consumer culture and diversity
in the consumer population. To pump up domestic consumption, the
government will subsidize purchases of cars and home appliances to
replace older models. The State Council said it will spend a total of RMB
5 billion on subsidies to consumers who trade in older vehicles for new
ones, and RMB 2 billion on the appliance subsidy program which pays a
rebate of 10% of the purchase price. In order to persuade shoppers to save
less and spend more, it is essential for the government to improve housing,
education and healthcare to aid the development of a consumer-based
107
economy. According to the World Bank, the savings rate in China has
risen as high as 50% of gross domestic product, including the retained
earnings of state-owned companies, and even families with incomes of
less than USD 200 per year would save 18% of their income, as people
believe they must save up for future healthcare costs, education expenses,
pensions and other burdens. Spending by the central government on
healthcare has been increasing in recent years. Lately government has
pledged a RMB 850-billion healthcare reform over the next three years,
to have 90% of citizens covered by 2011 and everyone insured by 2020. It
is a long-lasting project but this would be a big step forward for China.
The reforms will probably not have any immediate impact on savings
habits but it will gradually spur to rise more consumption. At the same
time in the United States, President Obama also outlined his plan to create
a USD 630 billion health reform reserve fund to provide coverage for 42
million uninsured Americans and to reduce the growth of healthcare costs
by USD 2000 billion over the next decade. The actions of governments
have proved again the ideology of political economist Adam Smith – the
state-supported indigent which goes much beyond relying only on a
profit-maximizing market economy. In his first book The Theory of
Moral Sentiments, he extensively investigated the powerful role of
108
non-profit values. In fact all the affluent countries in the world have
depended for some time on transactions that occur largely outside the
markets including healthcare, public pensions and other features of social
security. A strong social security system helps to create an
internal-dynamic to drive growth.
3.2.
Results – Government Bond
A government bond is regarded as a risk-free bond as the
government can always repay by raising taxes or printing more money to
redeem the bond at maturity. State bond issuance can change the money
supply and circulation. Without imposing the risk of inflation, the
issuance of bonds helps to relieve the costs of infrastructure construction
and economic stimulus plan. Friedman (1988) analyzed the Dow Jones
stock market index and the velocity of M2 and suggests that a rise in
stock prices reflects an increase in the expected return from risky assets.
Although there is no guarantee that this increase in relative risk will be
accompanied by a change toward risk aversion, nevertheless, a shift
toward relatively safe, fixed income securities plus money may be
expected. We shall be then confronted with the phenomenon of gains in
one asset class usually being accompanied by losses in the other, or
109
returns on one asset type decline while another declines less or even gains.
Thus, investors are inclined to allocate capital back and forth between
bond and stocks facing different risks. The chart below displays various
risks investors face from allocating 100% bond to 100% stock, based on
monthly closes of the T-bond Index (launched in 2003, tracking the
government bond performance in the Shanghai Stock Exchange) and the
Shanghai Composite Index from 2003 till April 2009. This behavior shall
result in a negative correlation between bond and share prices. Thus I
hypothesize there is a negative correlation between bond and stock prices.
Chart 29
T-Bond v.s. Stock Allocation
150%
Return
100%
50%
0%
-50%
2003
2004
2005
2006
2007
2008
2009.04
-100%
100% bond
80% bond &
20% stock
60% bond &
40% stock
40% bond &
60% stock
20% bond &
80% stock
100% stock
Volatility (Risk)
Source: Bloomberg
110
The performance of t-bond and stock market differs to the largest
decrease in the years of 2006, 2007 and 2008. How fast an investor will
change his portfolio allocation would depend on his risk tolerance level.
The graph visually supports that investors substitute t-bond with stocks
when stocks outperform, particularly in the two time frames outlined in
the graph. With the growing amount and quality of institutional investors
in China’s financial market, such replacement effect shall be more
obvious, as institutional investors are believed to be able to allocate
investment more wisely and efficiently.
Chart 30
T-bond Index v.s. Shanghai Composite Index
T-bond
2/27/09
6/30/08
10/31/07
2/28/07
6/30/06
10/31/05
2/28/05
6/30/04
10/31/03
2/28/03
Shanghai
Source: stock.sohu.com, Bloomberg
To test whether the hypothesis stands, I take firstly the returns of
111
t-bond index and Shanghai Composite Index in the above time frame, in
total 75 observations. The below regression and correlation results were
generated. The adjusted R2 and the slope are negative suggests there is a
certain degree of negative correlation but zero falls in the 95% interval. In
addition, correction analysis suggests there is a positive correlation. So on
a long-range average, the correlation in both price levels is positive
because in the long term an upward trend in stock market is also
accompanied by an upward trend in bond index. The hypothesis does not
fare
well
over
Regression Statistics
Multiple R
0.074382397
R Square
0.005532741
Adjusted R Square
Standard Error
Observations
the
Column 1
Column 2
entire
Correlation Analysis
1
0.424642232
sample.
1
-0.008090098
0.010969226
75
ANOVA
df
Regression
Residual
Total
Intercept
Shanghai
1
73
74
SS
4.8868E-05
0.008783647
0.008832515
Coefficients
Standard Error
0.002632871 0.001275673
-0.008762612 0.013749828
MS
4.8868E-05
0.000120324
F
Significance F
0.40613714 0.525930403
t Stat
P-value
Lower 95%
2.063907461 0.042581494 9.04567E-05
-0.637288898 0.525930403 -0.036165998
Upper 95%
0.005175286
0.018640773
112
T-bond Index
Shanghai Line Fit Plot
-40%
-20%
3%
2%
1%
0%
-1% 0%
-2%
-3%
-4%
-5%
-6%
-7%
20%
40%
T-bond Index
Predicted T-bond Index
Shanghai
Might focusing on a shorter period expose a useful relationship?
Now I shorten the model to a 1.5 years time frame, namely January 2003
to June 2004, July 2004 to December 2005, January 2006 to June 2007,
July 2007 to December 2008.
a)
January 2003 to June 2004: adjusted R-square, coefficient
and correlation results state there is a slight negative
correlation. But zero can be found between the lower 95%
and upper 95%.
113
Regression Statistics
Multiple R
0.11488902
R Square
0.013199487
Adjusted R Square
Standard Error
Observations
Column 1
Column 2
Correlation Analysis
1
-0.11488902
1
-0.048475545
2.969920589
18
ANOVA
df
SS
1.887718961
141.1268529
143.0145718
MS
1.887718961
8.820428304
F
Significance F
0.2140167
0.64986644
Coefficients Standard Error
103.1225396
10.51461849
-0.048220529
0.104233697
t Stat
9.807539829
-0.46261939
P-value
Lower 95%
3.59725E-08 80.83254917
0.64986644 -0.269186046
Regression
Residual
Total
Intercept
X Variable 1
b)
1
16
17
Upper 95%
125.412530
0.17274499
July 2004 to December 2005: adjusted R-square is
significant at 70%. Zero does not fall in the 95% interval.
Coefficients and correlation results imply there is a strong
negative correlation between two variables.
Regression Statistics
Multiple R
0.84735569
R Square
0.718011665
Adjusted R Square
Standard Error
Observations
Column 1
Column 2
Correlation Analysis
1
-0.84735569
1
0.700387394
3.107464211
18
ANOVA
df
Regression
Residual
Total
Intercept
X Variable 1
1
16
17
SS
393.3984183
154.5013412
547.8997595
MS
F
Significance F
393.3984183 40.73993563 9.07457E-06
9.656333823
Coefficients Standard Error
t Stat
P-value
152.2600347 8.099217266
18.7993518 2.48007E-12
-0.637937629 0.099946606 -6.382784316 9.07457E-06
Lower 95%
135.090465
-0.8498149
Upper 95%
169.4296044
-0.4260603
114
Y
X Variable 1 Line Fit Plot
110
108
106
104
102
100
98
96
94
92
0
Y
Predicted Y
20
40
60
80
100
X Variable 1
c)
January 2006 to June 2007: correlation states a positive
relationship but adjusted R-square is not high and
coefficient is almost zero. Additionally zero can be found
in the 95% interval.
Regression Statistics
Multiple R
0.411360269
R Square
0.169217271
Adjusted R Square
Standard Error
Observations
Column 1
Column 2
Correlation Analysis
1
0.411360269
1
0.11729335
0.781142055
18
ANOVA
df
Regression
Residual
Total
Intercept
X Variable 1
SS
1.988553361
9.762926561
11.75147992
MS
1.988553361
0.61018291
F
Significance F
3.258946339 0.089885779
Coefficients Standard Error
109.1708897 0.486132068
0.005365259 0.002972022
t Stat
224.5704342
1.805255201
P-value
Lower 95%
2.01083E-29
108.140336
0.089885779 -0.000935146
1
16
17
Upper 95%
110.2014434
0.011665663
115
d)
July 2007 to December 2008: strong opposite correlation
analysis result. Adjusted R-square is as high as 78%. Zero
does not fall in the 95% interval.
Regression Statistics
Multiple R
0.891806566
R Square
0.795318951
Adjusted R Square
Standard Error
Observations
Column 1
Column 2
Correlation Analysis
1
-0.891806566
1
0.782526385
1.604708433
18
ANOVA
df
Regression
Residual
Total
Intercept
X Variable 1
SS
160.0943295
41.20142648
201.2957559
MS
160.0943295
2.575089155
Coefficients Standard Error
120.9328761 1.104136151
-0.033312224 0.004224855
t Stat
109.5271411
-7.884821024
1
16
17
F
Significance F
62.17040259 6.68998E-07
P-value
Lower 95%
Upper 95%
1.94687E-24 118.5922125 123.2735396
6.68998E-07 -0.042268514 -0.024355934
116
X Variable 1 Line Fit Plot
122
120
118
Y
Predicted Y
300
400
Y
116
114
112
110
108
106
0
100
200
500
X Variable 1
It is necessary to connect the above results with the below
correlation chart and the table associated with the bond-stock allocation
chart. The regression and correlation analysis suggests the strongest
negative correlation in 2005 and 2008 when bond performed the best and
in 2007 when stock market peaked during the bubble with growing
uncertainty. People tend to switch from stock investment swiftly to bond
investments. While in 2006 and 2009 (till April), although stock
outperformed remarkably, the two asset price levels exhibit a certain
degree of positive relationship. Such phenomenon implies obvious
risk-reversal characteristics during a bull run.
Table 1
T-bond v.s. Stock Allocation
117
RETURNS (%)
2003
2004
2005
2006
2007
2008
2009.4
100% Bond
-0.6
-3.8
14.1
2.1
-0.5
9.4
-0.1
80% Bond & 20% Stock
1.6
-6.1
9.6
27.8
19.0
-5.6
7.1
60% Bond & 40% Stock
3.7
-8.4
5.1
53.5
38.4
-20.5
14.3
40% Bond & 60% Stock
5.9
-10.8
0.6
79.1
57.8
-35.5
21.6
20% Bond & 80% Stock
8.1
-13.1
-3.8
104.8
77.2
-50.4
28.8
100% Stock
10.3
-15.4
-8.3
130.4
96.7
-65.4
36.1
The yearly Pearson correlation movement is illustrated in the below
curve. I can conclude that t-bonds have a strong negative correlation with
stocks. But this does not mean the increase of stock definitely lead to a
decrease of t-bonds. Their price correlation, both positive and negative,
appears to be extraordinary when t-bond and stock register above average
growth. Retail investors account for more than 72% of total accounts in
China, according to the China Securities Regulatory Commission (CSRC),
amongst the 139 million accounts in 2007. 51.3% of the total investment
capital comes from retail investors, 25.7% from investment funds, 0.8%
from social security funds, 2.5% from insurance companies, 1.4% from
securities companies and other institutional investors occupy 18.3%.
118
Assuming 2/3 of investment funds’ capital belongs to retail investors in
China, it may well be that 70% of the total investment capital in stock
market comes from them. Thus retail investors’ investing behavior could
essentially influence the stock market.
Chart 31
Price Correlation of T-bond Index and Shanghai
Composite
Correlation
1
0.5
0
-0.5
-1
2003
2004
2005
2006
2007
2008
2009.1- 4
The following table shows the t-bond issuance from 2003 to 2008. It
states that the central government did not heavily engage in the t-bond
issuance as a tool to affect the stock market. The yearly issuance growth
is generally stable excluding the special issuance in 2007. The greater
119
issuance in 2004 is corresponding to the largest t-bond index drop at the
same time. Besides aiming to cool down the overheated stock market by
reducing liquidity along with tight monetary policy, the main purpose of
the 2007 special t-bond issuance was to set up the state-owned investment
company China Investment Corporation as the People’s Bank of China is
not allowed to directly purchase (excluding open market operations) or do
exclusive sales of t-bond due to legal limitations. The registered capital
was set at USD 200 billion, according to the Ministry of Finance.
Agricultural Bank of China, in fact, purchased in total RMB 13’500
million t-bonds in 2007, then sold them to the People’s Bank of China in
exchange for the USD. Thus, only RMB 2’002 million t-bond flowed into
society, in which RMB 1’034 million t-bonds were sold in September,
RMB 705 million in November and the rest in December respectively.
The stock market peak began to descend in October 2007. This is also in
line with the extra t-bond supply. The one-year bear run stimulated
people’s appetite for t-bonds. Although the coupon was not significantly
higher than what time deposits offered, during the first issuance in 2008,
t-bonds were sold out within hours in banks across in China as people
expected interest rates to drop further.
Table 2
T-bond Issuance, in 100 million RMB
120
CATEGORY
2003
2004
2005
2006
2007
2008
Book-entry
3776
4366
5042
6533
6347
6665
Certificated
2505
2510
2000
1950
1600
1300
34
650
Savings
-
-
-
400
Special
-
-
-
-
Total
6280
6876
7042
8883
15502
23483
8615
Source: jrj.com
3.3.
Results – Taxation Policy
Profit per share after tax is the foundation of stock price. For listed
companies, cutting tax implies fewer costs and more profits, making
stock more valuable which in turn leads to higher stock prices
consequently. For the public, lower tax, broader tax reduction or
exemption range may increase income and in the mean time encourage
consumption and investment needs, as suggested by Keynesian
economics (instead of increasing savings which is a theory promoted by
Barro). Higher investment needs will thereafter result in more stock
purchases. In general, cutting tax benefits stock price. The 11th Five-Year
plan sets the goal of shifting from a production-based to a
121
consumption-based value-added tax (VAT) regime from 2006 to 2010. To
spark growth facing the current financial crisis after a 5-year pilot
program, China has implemented the reform under which companies no
longer need to pay VAT upon equipment purchases. Applicable from
January 1, 2009, this new taxation policy could save companies RMB 120
billion per year, according to the Ministry of Finance and the State
Administration of Taxation. The government wishes to encourage
enterprises to upgrade their technology base and increase the demand of
equipment on the back of this reform.
Adding to the domestic consumption stimulation measures besides
VAT deduction, from November 1, 2008, the government has reduced the
property deed-tax for first-time buyers from 1.5% to 1%, temporarily
waived land VAT and stamp duty on transactions of real estate.
Additionally the minimum mortgage down-payment has been reduced
from 30% to 20% for those who purchase for self-usage. These measures
has improved consumers’ buying-power, especially that of young people,
and also provoked transactions. A recent report of CB Richard Ellis’
China division suggested that psychological effect was important while
the national and local measures only reduced the cost of housing by 2% to
5%. The State Council’s support was seen as indicative of a policy shift
122
from dampening demand to reinvigorating the property market.
Whether real estate is in its recovery is of crucial importance as it is
one of the economy's most effective locomotives of growth. Property
drives about 17% to 18% of total steel demand and also takes shares of
cement output. For retail sector, real estate transactions drive sales of
home appliances (especially durable goods), furniture and other
household products. Some people are not yet entirely convinced by the
policy shift as they expect developers are likely to further reduce prices
due to over-supply in the some regional markets including Shanghai,
Beijing and Guangzhou. Even though, property transactions have been
rising in 2009 and land sales have resumed. Increasing amount of people
attending property fairs in various parts of China confirmed this sense of
surging demand. The rationale behind this is that buyers had been waiting
for eight or nine months for the bottom of the market to become apparent.
In many cities, people think this has now arrived. One of the most potent
forces in Chinese real estate in recent years has been the group-buying by
wealthy investors from Wenzhou. Recent surging sales in Wenzhou,
Suzhou and Hangzhou signal that Wenzhou businessmen are calling the
bottom of the market. In addition, due to the lower margin of projects, the
developers who survive the tumultuous 2009 may well stand to gain once
123
the market turns the corner. The financial difficulties faced by some
developers have been a corresponding increase in mergers and
acquisitions (M&A). Developers with lower gearing and strong balance
sheets are active buyers of properties from distressed developers. The
industrial consolidation and the recovering consumer confidence have
achieved nearly 70% outperformance of real estate index compared with
Shanghai Composite Index, from November 2008 to April 2009.
Chart 32 Real Estate Index vs Shanghai Composite Index, rebased daily
240
Real Estate Index
Shanghai
200
69.8%
160
120
80
Nov-08
Dec-08
Jan-09
Feb-09
Mar-09
Apr-09
Source: Bloomberg, stock.sohu.com
Among all kinds of taxes, stamp duty on share transaction is
probably related most closely to trading cost. Stamp duty was invented by
124
the Dutch in 1624 when the government was in financial trouble. Stamp
duty is easily raised and accepted by the public, thus it has been widely
put into practice all over the world. The original work in the literature on
stamp duty effect was conducted by Jackson and O’ Donnell (1985).
Their findings, based on quarterly data, suggest that every 1 percentage
point (ppt) stamp duty cut from 2% to 1% leads to an extreme 70%
increase in equity turnover.12 There are findings that higher stamp duty
tax has imposed negative effects on turnover. Ericsson and Lindgren
(1992) used international panel data and find that 1 ppt increase in stamp
duty tax causes a turnover decrease between 50 % and 70 %. Bond et. al
(2004) investigated stamp duty on share prices in the UK and find that the
announcements of cuts in stamp duty had a significant and positive effect
on the prices of more frequently traded shares compared to other shares.
Stamp duty is charged once per transaction. The Tobin tax
proposes such transaction taxation in order to discourage volatile
short-term trading13. However, Saporta and Kan (1997)’s research implies
the opposite. They examined the response of the equity market to
announcements of changes in stamp duty rates. They compared the prices
of two assets – American Depositary Receipts (ADRs) and their London
12
Stamp duty (the UK securities transaction tax on shares and debentures) was cut from 2% to 1% in
April 1984.
13
The Tobin tax was first suggested by and named after James Tobin (1974).
125
Stock Exchange-traded stocks – which are similar in all respects apart
from their treatment for stamp duty purposes. Their findings suggest that
stamp duty is capitalized in prices and it has no effect on volatility.
In general, when the market is overheated, the government intends
to raise stamp duty to cool down the market; while on the other hand,
when the equity market is in recession, government would reduce the
stamp duty to stimulate trading volume. The rate of stamp duty in China
has changed over the years. On June 28, 1990, China ordered sellers to
pay 0.6% of the total transaction turnover on the Shenzhen Stock
Exchange. This marked the first stamp duty on stock in Chinese history.
In that November, Shenzhen started to levy the same duty also on buyers.
These attempts triggered a slump in the Shenzhen market, forcing the
government to cut the duty in half to 0.3% in October 1991. At the same
time, Shanghai began to levy 0.3% stamp duty on both the buy and the
sell side. In 1996, China’ stock markets began a strong bull run. Despite
repeated official warnings of an overheated market, the Shanghai
Composite Index nearly tripled from early 1996 to early May 1997. On
May 10, 1997, the state lifted stamp duty from 0.3% to 0.5%, which
ended the bull run and led to a drop of more than 30% within half a year.
On June 12, 1998, the stamp duty was adjusted to 0.4%. Then on June 1,
126
1999, the government reduced the duty for B-shares to 0.3%. The B-share
index climbed above 50% within one month. On November 16, 2001,
Beijing decreased the duty to 0.2%. In January 2005, government lowered
the duty to 0.1% from 0.2% in order to boost stock prices during a market
slump lasting from 2001 to 2005. The bear run did not end until the
startup of stock reform. On top of a 130% jump in 2006 and a 62%
year-to-date rise of the Shanghai Composite Index, on May 30, 2007, the
stamp duty was increased to 0.3% from 0.1%, a move seen as a bid to
clamp down on the overheated market which unfortunately did not play
its role. The most recent move on stamp duty rate was on April 24, 2008,
when Beijing lowered it from 0.3% back to 0.1% aiming to tackle the
spreading of global financial crisis. From September 19, 2008, authorities
announced to levy stamp duty only on sales. I plot in the chart below the
stock market turnover from 1992 to 2008 (data from 1990 to 1991 not
available). Clearly turnover increased dramatically during the period
following the 0.3% cut in 1991 till mid 1997 and after the 0.1% cut in
January 2005 till mid 2007. The high turnover period from 2005 to 2007
however was also the result of the exogenous structural change caused by
stock reforms. Total trading dropped when stamp duty was increased to
0.5% during the period from mid 1997 to mid 1998 and from mid 2007 to
127
mid 2008. The two rate cuts from mid 1998 to early 2005 did not produce
obvious effects eventually as the total turnover basically flattened at the
end of this time window but two hills can still be observed in between.
Thus, the development of turnover visually confirms the theory that
stamp duty decrease has positive impact on stock market trading turnover
but not necessarily in the long run.
Chart 33
Turnover, in RMB billion
100,000
0.3%
0.5%
0.4%
0.2%
0.1%
0.3% 0.1%
10
1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Source: NBSC, turnover including A and B shares.
To gain some intuition, I draw below the velocity of turnover in the
period, in comparison with the Shanghai Composite Index. The market
turnover velocity is defined as the ratio of the value of shares traded
(turnover) divided by market capitalization. It is also referred to as
128
turnover rate or average holding period. A low turnover to market
capitalization suggests low liquidity. It can also be interpreted as that
investors expect the market will pick up. A declining velocity in a bull
market is a positive sign as it indicates that investors are holding on to
stocks. However in a volatile market, it means traders are stuck with deals
and therefore have little choice but to hold on to the stocks longer than
they would otherwise prefer. During the period from 1992 to mid 1997
following the first stamp duty cut in 1991, velocity is quite volatile but
finished by up 110%, twice that of the appreciation of the stock market.
This implies better liquidity and the fluctuation gears to that of the stock
market. In the implementation of the 0.5% stamp duty regime, turnover
decreased by about one third while stock market capitalization increased
11% and index retreated slightly by 0.4%. The change of stamp duty in
mid 1998 did not seem to produce the usual outcome in the longer-term.
In this time frame till the end of 2001, the stock market gained 44% along
with a doubled market capitalization contributed by 36% more listings,
while velocity increased slightly in between but dropped sharply after the
market correction caused by the Internet Bubble. The bear run from 2002
to early 2005 did not hold back the increase of velocity, indicating very
strong trading activities and better liquidity prior to the bull market which
129
was enhanced later by the 0.1 percentage cut. The velocity increased
further following the cut in 2008. This phenomenon suggests investors
intend to hold on to the stocks and even add investment in order to reach
a potential break-even.
Chart 34 Velocity of Turnover and Shanghai Composite Index
250%
6000
5000
200%
4000
150%
3000
100%
0.3%
0.5%
0.4%
0.2%
2000
0.3%
0.1%
0.1%
50%
1000
0%
0
92
93
94
95
96
97
98
99
00
01
Velocity
02
03
04
05
06
07
08
Shanghai
Source: NBSC, Bloomberg
If stamp duty change does not ultimately generate an influence on
the stock market, this impact observed must be strong on a short-term
basis. The table below summarizes the return of the Shanghai Composite
Index on the day when there was a stamp duty adjustment and the
following 30-day return after such change.
130
Table 3
Announcement Effects of Stamp Duty Changes, Shanghai
DATE
EVENT
DAY RETURN
30-DAY
RETURN
Oct 10, 1991
Decreased to 0.3% in
+1.0%
+22.3%
SZ, SH Started to levy
May 10, 1997
Increase to 0.5%
+2.3%
-13.1%
Jun 12, 1998
Decrease to 0.4%
+2.6%
+1.0%
Jun 1, 1999
Decrease to 0.3% for
+2.5%
+32.1%
B-share
Nov 16, 2001
Decrease to 0.2%
+1.6%
+3.3%
Jan 23, 2005
Decrease to 0.1%
+1.7%
+6.1%
May 30, 2007
Increase to 0.3%
-6.5%
-11.9%
Apr 24, 2008
Decrease to 0.1%
+9.3%
+5.9%
Source: Bloomberg, stock.sohu.com
The four charts below outline the stamp duty changes in the
corresponding dates of the Shanghai Composite Index, at 5-year intervals.
It graphically supports that stamp duty does impose effects, but such
impact exhibits more announcement effects – a short-term trigger, instead
of a long-term stimulation in China’s stock market.
131
132
10/1/00
7/1/00
4/1/00
1/1/00
10/1/99
7/1/99
500
4/1/99
1/1/99
10/1/98
7/1/98
0.3% to 0.5%
4/1/98
1/1/98
10/1/97
12/19/95
9/19/95
6/19/95
3/19/95
12/19/94
9/19/94
6/19/94
3/19/94
12/19/93
9/19/93
6/19/93
3/19/93
12/19/92
9/19/92
6/19/92
3/19/92
12/19/91
9/19/91
6/19/91
3/19/91
12/19/90
200
7/1/97
4/1/97
1/1/97
2000
10/1/96
7/1/96
4/1/96
1/1/96
Chart 35
Stamp Duty Changes
1800
1600
1400
1200
1000
800
600
400
0.3%
0
2500
0.5% to 0.4%
1500
1000
0.4% to 0.3%
for B-share
0
3/1/09
1/1/09
11/1/08
9/1/08
7/1/08
10/1/05
7/1/05
4/1/05
1/1/05
10/1/04
7/1/04
4/1/04
1/1/04
10/1/03
7/1/03
4/1/03
1/1/03
10/1/02
7/1/02
4/1/02
1/1/02
500
5/1/08
3/1/08
1/1/08
2000
11/1/07
9/1/07
7/1/07
5/1/07
3/1/07
1/1/07
11/1/06
9/1/06
10/1/01
7/1/01
4/1/01
1/1/01
1000
7/1/06
5/1/06
3/1/06
1/1/06
2500
2000
1500
0.4% to 0.2%
0.2% to 0.1%
0
7000
6000
5000
0.1% to 0.3%
4000
3000
1000
0.3% to 0.1%
0
Source: Bloomberg, stock.sohu.com
Among all sorts of taxes, stamp duty is one of the easiest to
133
administer, given that most transactions on the stock exchange are now
electronic and thus it can be deducted automatically. Compared with other
taxation, stamp duty is perhaps also the cheapest of all to collect. The
amount of revenue raised varies from year to year but was always below
5% of the government financial income. The chart below displays the
revenue weighting of stamp duty on stock transactions. The taxation
revenue on stamp duty reached two highs in 2000 and 2007, when stock
markets peaked while tax ratios were fairly low. The overall weighting in
fiscal revenue is not high. In developed economies, stamp duty on stock
transactions were abolished over time. OXERA estimated that stamp duty
raises the cost of capital by 0.72 to 0.87 percentage points14. China will
eventually follow this path. In connection with the stock market
performance, I may conclude that stamp duty taxation does not post
strong long-term impact on China’s stock market and this is likely to
continue to be the case.
14
OXERA, 2001, Impact of Stamp Duty on the Cost of Capital of UK Listed Companies, paper prepared
for the London Stock Exchange / The Hundred Group of Finance Directors.
134
Chart 36 Stamp Duty Weighting in Fiscal Revenue
% 4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
93 94 95 96 97 98 99 '00 '01 '02 '03 '04 '05 '06 '07 '08
Source: NBSC, CSRC
All in all, taxation policy has direct and obvious impact on stock
markets. Impact from stamp duty change is observed especially in a
shorter-term period compared with other tax changes which need to be
digested gradually by the market. I see Chinese government has reacted
generally at the right time on increasing or decreasing certain taxation for
the development of the market.
135
Chapter Four Overview of Policies
When the unusual movement of the stock market jeopardizes the
stabilization of financial conditions, the government promulgates policies
or releases information to guide the direction of the market. It is said, in a
healthy market, stock price presents the inherent value of a company,
while the reaction to the policy shall be based on the public expectation of
such policy’s effectiveness, and such effectiveness should be moderate.
The Chinese stock market was born in an economy in transition.
Stock exchanges were established in Shanghai and Shenzhen in
December 1990. The Shanghai Stock Exchange began operations on
December 19 while Shenzhen started seven months afterwards. The
‘Chinese Characteristics’ in some degree hindered the development of the
market, originating from communism. Government has a special role and
function, not only as a governor of the macro economy but also an
organizer and promoter. It could use compulsory system change and other
administrative methods to realize this goal.
As a young market, the incomplete structure and unprofessional
investors lead to low risk-resisting ability and instability. The market
136
could be excessively stagnant or overheated. In order to expedite the
development and ensure the necessary stability, the government began
with clear goals to direct the secondary market. In a planned economy, a
government’s experience of supervising the market would not prevent the
self-development of the market. Compelling system changes were
released during the course of maturation, which urged the speedy growth
of the stock market. Such changes barely address the role of compatibility
between social acceptance and inductive system change. However under
such conditions:
a)
Government policy change becomes an origin of risk
b) The powerful impact of policy largely restraints the formation
of price mechanisms and damages market efficiency
c)
The stock market is generally recognized as a money-making
tool by speculative investors.
Anyhow, despite these potential damages, the market would not be
able to reach its current state without those government interventions and
guidance.
4.1.
Methodology
With the development of econometric methods, economists began to
apply VAR (vector auto regression) models. A VAR model is a set of
137
linear dynamic equations where each variable is specified as a function of
an equal number of lags of itself and all other variables in a given system.
As a non-structured multiple equation model, which differs from
structural approach, a structural approach describes the relation between
variables based on economic theory which could not strictly describe the
dynamic relations between variables. Since the basic principles were put
forward by Sims (1980), the VAR model has been used extensively within
both closed and open economy environments.
To assess the impact on stock markets, event study has been largely
used as a common method in quantitative studies. The first event study
was conducted and published by Dolley in 1933, who examined nominal
price effects on stock splits. Dolley used a sample of 95 splits between
1921 and 1931 and concluded that share price increased in 70% of the
cases while declined in only 27% of the instances. Since then, this
methodology has been used and improved by Ashley (1962), Ball &
Brown (1968), Fama et al (1969) and Mayers & Copeland (1982).
Although there is no unique structure to perform an event study, there is a
general flow to conduct the analysis which consists of 7 steps (MacKinlay,
1997). Despite the improvements, there are several limitations on the
method, as the research is based on the assumptions of efficient markets
138
where stock reflects all relevant information, event shall be unanticipated
and there are no confounding factors. The primary criticism is aimed at
the last limitation, based on the fact that the methodology may capture
effects from other events which occur in the same event window.
Another methodology often used is case study. This qualitative
method is widely practiced to emphasize detailed contextual analysis
across a variety of disciplines. Robert K. Yin (1984) defines the case
study research method as an empirical inquiry that investigates a
contemporary phenomenon within its real life context, when the
boundaries between phenomenon and context are not clearly evident, and
in which multiple sources of evidence are used. Others criticize case
study on its limitation of cases offer no grounds for establishing reliability
and biases the findings.
In recent years, researchers start to show interest in a phenomenon
of time series, that autocorrelations decay slowly. Econometrics uses the
ARMA model to describe such phenomenon, which is called long
memory time series. Such time series characteristics are not only
discovered in finance but also observed in other fields by Hydrologist
Hurst (1951 and 1957), geophysicists Mandelbrot & Wallis (1968), and
meteorologists Mcleod & Hipel (1978). The most famous long memory
139
case is processed by Hurst. He used the yearly minimum water levels of
the Nile River from 1007 to 1206 and the persistence of river flows is
known as the Hurst Effect.
This chapter will summarize the major fluctuations in China’s stock
market in association with potential policy changes. I analyze then the
game between government and investors. To access whether government
policy has essential influence on stock markets or whether it is correlated
still to real economic growth, I utilize a VAR approach to test the
relationship between China’s GDP growth and the Shanghai Composite
Index performance. In stock reform section, I’ll use event and case
studies to assess the government policy impacts.
4.2.
Summary of Major Fluctuation and Policy
Changes
In China’s stock market, it is not difficult to find that most of the big
market movements were related to policy change.
Table 4
No.
Date
Major Market Fluctuations from 1992 to 2008
Days
%
1
116.2%
Main Cause
Category
1992
1
5.21
Stock
waived
price
limitation
Policy
140
2
8.10
2
-37.59%
New share issuance
NSI
3
9.7
2
-20.98%
New share issuance
NSI
4
9.11
1
12.0%
Control new share issuance
Policy
5
10.26
2
-19.90%
New share issuance
NSI
The first B-share of
6
11.23
4
83.31%
Shanghai Vacuum Electron
Policy
Devices Co. Ltd. (SVEC)
1993
7
2.22
3
-20.22%
NSI
State owned shares of
Lujiazui Finance and Trade
8
4.6
4
41.47%
transferred to private
Policy
investors with
compensation
Time deposit rate up
5.15
1
2.18%, lending rate up
Policy
0.82%
Government expressed
9
6.1
3
37.06%
importance of stock
Policy
markets
One-year time deposit rate
7.11
1
raised to 10.98% from
Policy
9.18%
New share issuance of
10
7.30
1
11.2%
Harbin
Pharma
led
to
Market
hostile trading
11
12.20
1
-20.2
Stock option regulation
Policy
1994
141
12
1.14
5
-13.59%
Government’s
financial
situation discussion (risk)
Policy
Four ‘NO’ policy (no new
issuance within half a year,
13
3.11
1
9.9%
no stock income tax, no
merger of non-tradable and
Policy
tradable shares, no stock
distribution)
14
4.13
6
-20.31%
Avoid state capital loss
Allow
15
8.1
1
33.5%
capital
Policy
raise,
Chinese and foreign joint
Policy
venture fund
16
9.26
5
-40.69%
Market rumors
17
10.26
1
-8.9%
18
12.15
1
-7.2%
National bond issuance
Lujiazui’s dividend below
expectation
Market
Market
1995
19
2.22
1
-9.9%
New bond issuance
20
5.18
1
31.0%
Stop t-bill future trading
Policy
new shares issuance scale
21
5.23
1
-16.4%
to be announced in the
NSI
second quarter
22
6.15
1
-7.6%
5.5 billion share issuance
quota
NSI
1996
23
4.30
1
-8.4%
24
10.30
1
-6.1%
Regulation
on
insider
holding of listed companies
Strengthening
of
Policy
Policy
142
supervision
25
12.2
1
9.9%
26
12.12
4
-27.26%
Market
Editorial on People’s Daily
Policy
Speeches of the presidents
27
12.18
1
7.8%
of Shanghai and Shenzhen
Policy
exchanges
1997
Rumor of the death of
28
2.18
1
-9.9%
29
2.19
1
7.7%
Death of Deng Xiaoping
30
5.8
1
-7.3%
Increase stamp duty
31
5.13
2
-8.2%
32
5.16
1
-8.3%
33
5.21
2
-11.3%
Deng Xiaoping
Policy
30 billion share issuance
quota
Four companies suspended
Forbid
state
owned
companies to trade stocks
NSI
Policy
Policy
Forbid certain cash inflows
34
6.6
1
-8.4%
from bank to the stock
Policy
market
35
6.10
2
-8.5%
36
6.13
1
7.7%
37
7.2
1
-9.9%
38
7.7
1
-7.2%
39
9.22
2
-13.5%
Rumor on processing
law-breaking institutions
Prosecute law-breaking
institutions
29 new listed companies
within two weeks
Policy
NSI
NSI
Depression
Market
1998
143
40
1.13
1
-9.2%
Asian financial crisis
Bank deposit reserve ratio
41
3.23
1
-0.6%
decreased from 13% to
8%
42
8.17
1
-8.5%
Policy
15
Flood
1999
43
5.19
1
4.9%
44
6.15
1
-7.5%
45
6.25
1
-6.7%
46
6.28
1
6.2%
Speech of Wen Jiabao
Policy
47
7.1
1
-7.7%
Securities Law in force
Policy
48
7.20
1
6.5%
Editorial of People’s Daily
Market
Market
Stated
49
9.9
1
6.6%
Policy
own
enterprises,
state controlled companies
and listed companies can
Policy
trade in secondary market
50
11.22
1
-0.3%
Bank deposit reserve ratio
reduced from 8% to 6%
Policy
2000
50% of NSI rationed to
51
2.14
1
9.0%
investors
in
secondary
Policy
market
52
5.9
2
-6.1%
Web trading regulation
Policy
53
9.5
2
-4.2%
Three party supervision
Policy
54
11.24
1
-3.6%
Market
2001
15
The bank reserve rate was fixed at 10% since 1985. It was increased by 2%
from 10% to 12% in 1987 and another 1% to 13% in 1988.
144
A
famous
share
manipulation
case
–
Guangdong Yi’an Group.
55
4.26
1
-2.4%
Insiders bought and sold
87.34% of the companies’
Policy
tradable shares, pushing
price from RMB 7.55 to
126.31
56
7.30
1
-5.27%
Reduce state owned stake
Guangxia
57
8.6
1
-3.91%
Policy
(Yinchuan)
Industry Co., Ltd faked
financial report
58
8.27
1
-3.61%
Reduce state owned stake
at market price
Regulates
59
10.10
2
-6.1%
stake
non-tradable
transfer,
forbids
over-the-counter
stake
Policy
auction
60
10.23
1
9.86%
61
11.7
1
-4.62%
1
6.35%
Stop reducing non-tradable
shares
Illegal
conduction
Policy
of
Hainan Seg Trust
2002
62
1.23
Deny the plan of reducing
non-tradable shares
Release
63
1.28
1
-6.33%
Reducing
Research
State
Policy
of
owned
Policy
Shares
145
Announcement: the above
64
1.31
1
6.81%
Research
focuses
on
Policy
investors’ interest
Policy maker suggests to
65
3.5
5
11.35%
legislate the reduction of
Policy
state owned shares
Commission charged by
66
4.5
1
-0.43%
securities
companies no
Policy
more than 3‰
Establishment of Securities
Companies with Foreign
67
6.6
1
4.05%
Equity Participation Rules;
Rules on the Establishment
of
Foreign-shared
Fund
Management Companies
Stop
implementation
of
Interim Measures of the
State
68
6.24
1
9.25%
Council
on
the
Management of Reducing
Held
State
Raising
Shares
Policy
and
Social
Security
bond
trading
Funds
69
10.10
1
-0.32%
Reduced
charge by 50%
Policy
Notice on Transferring
70
11.4
2
3.14%
Issues of Stated-owned and
corporate-owned Shares to
Policy
Foreign Investors
146
Interim
Provisions
Foreign
Exchange
Administration
71
11.28
2
4.02%
on
of
Domestic
Securities
Policy
Investment by Qualified
Foreign
Institutional
Investors
2003
72
1.14
1
5.81%
73
4.8
6
7.68%
Insititutional
investors’
trading
Fund companies buy in
Delisting
74
5.13
1
-3.04%
regulation
NSI
Market
warning
released.
58
Policy
companies warned
75
6.14
6
-3.54%
Central
Bank’s
new
housing loan system
Policy
CSRC released Interim
76
9.1
1
1.96%
Measures for the
Administration of Bonds of
Policy
Securities Companies
77
9.22
1
-0.7%
Bank deposit reserve ratio
up by 1% to 7%
Expectation
Policy
on
forthcoming policy from
78
10.10
1
2.54%
the Third Session of the
Sixteenth
Policy
Central
Committee
79
12.22
1
3.23%
CSRC’s Trial
Policy
147
Implementation Measures
for the Customer Asset
Management Business of
Securities Companies
2004
State Council’s Opinions
80
2.2
3
5.93%
on capital market’s reform
Policy
and stable development
81
3.25
1
-0.2%
82
4.27
1
-1.5%
Floating rate of re-lending
to financial institutions
Bank deposit reserve ratio
raised from 7% to 7.5%
Administration
83
7.1
1
3.00%
Policy
of
Securities Investment Fund
Management
Policy
Companies
Policy
Procedures
Executive meeting of State
84
9.14
5
16.1%
Council emphasizes the
implementation of the
Policy
above Opinions
Administration of Stock
85
10.25
2
2.42%
Investments by Insurance
Institutional Investors
Policy
Tentative Procedures
86
10.28
3
-2.80%
1
-1.29%
Deposit and lending rate
increased by 0.27%
Policy
2005
87
3.17
Housing loan increased by
Policy
148
0.18%
Notice of the CSRC on
88
4.29
1
-2.44%
Piloting the Share Reform
Policy
of Listed Companies
Administration
Buyback
89
6.6
1
2.05%
of
by
the
Listed
Companies of Their Public
Policy
Shares Procedures (Trial
Implementation)
Possible capital injection
RMB
140
billion
into
market including 60 billion
90
6.8
1
8.21%
to securities companies. In
addition, rumors about the
interest rate will remain
stable.
2006
Lending rate for financial
91
4.28
1
1.66%
institutions up 0.27% to
Policy
5.85%
CSRC forbids short-term
92
5.12
1
4.26%
investment on securities
Policy
companies
93
7.5
1
2.20%
94
8.15
1
1.59%
95
8.19
1
0.20%
Bank deposit reserve ratio
lifted to 8% from 7.5%
Bank deposit reserve ratio
up to 8.5%
One-year
deposit
and
Policy
Policy
Policy
149
lending rate up 0.27%
96
11.15
1
1.84%
1.15
1
4.7%
2.25
1
1.4%
3.18
1
2.9%
4.16
1
2.2%
4.30
1
2.2%
Bank deposit reserve ratio
up to 9%
Policy
2007
Bank deposit reserve ratio
raised to 9.5%
Bank deposit reserve ratio
increased to 10%
Interest rate up by 0.27%
Policy
Policy
Policy
Bank deposit reserve ratio
up half a percent to 10.5%
Bank deposit reserve ratio
up to 11%,
Policy
Policy
One-year deposit rate up
5.21
1
1.0%
0.27%, lending rate up
0.18%.
Bank
deposit
Policy
reserve ratio up to 11.5%
6.1
2
-10.91%
Stamp duty up to 0.3 ‰
nd
2
6.28
1
-4.03%
quarter
meeting
Monetary
Policy
of
Policy
Committee of the People’s
Bank of China
Measures of State-owned
7.9
1
2.69%
Share Transfer of Listed
Policy
Companies
Allowed investment ratio
7.17
1
1.94%
of A-share up to 10% for
Policy
insurance companies
150
Decrease tax on interest
7.23
1
3.81%
from 20% to 5% and
increase interest rate by
Policy
0.27%
7.30
1
2.20%
8.22
1
0.50%
9.6
1
1.6%
9.11
1
-4.51%
9.17
1
2.06%
10.15
1
2.2%
11.12
1
-2.4%
12.10
1
1.4%
12.21
1
1.15%
1
-2.6%
Bank deposit reserve ratio
up to 12%
Deposit rate up by 0.27%,
lending rate up by 0.18%
Bank deposit reserve ratio
up to 12.5%
RMB 200 billion special
government bond issuance
Interest rate up 0.27%
Policy
Policy
Policy
Policy
Policy
Bank deposit reserve ratio
up to 13%
Bank deposit reserve ratio
up to 13.5%
Bank deposit reserve ratio
up to 14.5%
Deposit rate up by 0.27%,
lending rate up by 0.18%
Policy
Policy
Policy
Policy
2008
1.17
Bank deposit reserve ratio
up to 15%
Announcement
1.21
2
-12.35%
Policy
that
Ping’an Insurance planning
to sell as much as 1.2
billion shares and RMB
151
41.2
billion
convertible
bond,
total
refinancing
amount
to
RMB
160
billion
1.28
1
-7.19%
Snow storm
Vice
president
central
2.25
1
-4.07%
of
the
bank said tight
monetary
unchanged,
policy
avoiding
Policy
inflation is still the primary
goal
3.19
1
2.5%
4.7
1
4.45%
Bank deposit reserve ratio
up to 15.5%
People’s Daily – investors’
interest shall be protected
People’s
4.14
1
-5.62%
Policy
government
Daily
needs
–
to
intervene and stop loss
4.17
1
-2.1%
4.24
1
9.29%
5.13
1
-1.8%
Bank deposit reserve ratio
up to 16%
Stamp duty down to 1‰
from 0.3 ‰
Bank deposit reserve ratio
up to 16.5%
Policy
Policy
Policy
Bank deposit reserve ratio
6.10
1
-7.7%
to be increased by 0.5%
twice to 17.5%, to be
implemented
Policy
respectively
152
from June 15 and 25, 08
Lending rate
9.16
1
-4.47%
0.27%,
bank
down
by
deposit
reserve ratio down 1% (2%
Policy
for earthquake region)
Sell-side stamp duty only;
State-owned
Assets
Supervision
and
Administration
Commission
9.19
2
17.23%
supports
SOEs to buy back shares;
Policy
Central Huijin Investment
Company
Ltd
(Huijin)
bought ICBC, Construction
Bank and Bank of China
shares
Interest
0.27%;
10.9
1
-0.84%
reserve
rate
bank
ratio
down
by
deposit
down
by
Policy
0.5%; temporarily abandon
tax on interest
10.30
1
2.55%
11.10
1
7.27%
Interest
1
1.05%
down
by
0.27%
RMB 4 trillion stimulus
plan
Interest
11.27
rate
rate
down
Policy
Policy
by
1.08%; large banks’ deposit
Policy
reserve ratio down by 1%
153
to 15%, small and middle
sized banks’ reserve ratio
down by 2% to 14%
Adding RMB 100 billion
government loan to banks;
12.3
1
4.01%
Huijin bought RMB 1.2
billion bank shares; further
Policy
policy released to promote
stock market
12.23
1
-4.55%
Interest
rate
0.27%
down
by
Policy
NSI represents for new share issuance. Data source：from 1992 to 2000, Shi
Daiming, ‘Study of Volatility and Efficiency of China’s Stock Market’ ，
P160-162，Southwestern University of Finance and Economics Press, Jan 2003;
from 2001 to 2002, Wu Xiaoqiu, ‘China’s Capital Market: Share right Splitting
and Liquidity Change’, P91, Renming University Press, Apr, 2004; from 2003 to
2004, data mainly comes from http://www.stock01.com. Bank reserve ratio
changes from website of People’s Bank of China.
4.3.
Game between Government and Investor
The inconsistence of government targets is the substantial origin of
intervention. On one hand, it hopes to bring forward a bull market, which
would help companies raise capital. On the other hand, the market should
not be overheated. Therefore, the preference of the government is
non-monotonic. It changes according to the market level, whereas
investors’ preference is changeless. Their only goal is to pursue the
154
possible largest bid-ask spread. The contradiction between government
and investor determines that the performance of the market is largely the
outcome of a game process, which can be demonstrated in a simple table
below.
Table 5
Payoff Matrix between Government and Investors
GOVERNMENT
Investors
Direct
Indirect
Intervention
Regulation
Reaction to Policy
a, e- c1
b, 0
Stock Valuation
b, e- c2
d, e
Say, e as (short-term) effectiveness of policy by direct interference,
c1 as the government’s cost when investors react to policy intervention, c2
as government regulating cost when investor insists on value investing
(meaning not responding to policy change). Naturally, c1 is smaller than c2.
When policy achieves its expected result, e-c1 would be bigger than zero.
However, governing cost grows if investors do not react to the policy
when c2 increases. This may lead to an invalidation of policy when e
minus c2 is a negative number. Based on the actual situation, assuming
direct intervention and indirect regulation are implemented, investor’s
dominant strategies would be either following the policy as the public or
155
stick to stock evaluation, as shown in the table. So variables a>d>b.
Obviously the game has two Nash equilibriums: government’s direct
intervention, investor follows; government’s indirect regulating, investor
does company evaluation.
A market dominated by policies represents the first equilibrium. In
the short-term, such allocation has the strongest Pareto optimality.
Government reconciles the contradiction by using policy intervention. It
is strong enough to change the direction of the market. Hence, the
decisive role of stock’s inherent value is overruled by the policy effect,
when investors can only follow herd instinct to realize profit. While from
a long-term perspective, frequent government interventions lead to a
misunderstanding that companies’ inherent strength does not matter.
Under such circumstance, investors give up the valuation of company
itself, but embrace policy-speculation as investment philosophy. Such an
idea strengthens itself after more and more interferences, which finally
replaces a rational investment. Every time when a positive signal comes
from the authorities, investors largely expect the increase of index and
money flows into the market. When the government signals a
cooling-down, investors sell off sharply. When the market is in continued
depression, people look to the government for a rescue plan. Once the
156
plan comes, they follow the tide and this causes high market volatility.
Undoubtedly, such situations increase the governing cost. Authorities
have to release stronger policy or interfere more frequently in order to
meet the target. Unfortunately such intense intervention can only enhance
the belief of people’s policy-following investment philosophy, where
people put their ‘rational’ expectation on policy above the company itself.
Once the policy does not meet such expectation, the government becomes
ineffective. This can be explained by Kahneman and Tversky’s heuristics
theory (1974). For instance, when an investor continuously observes the
policy changes, he would speculate that the government has intentions to
reverse such a policy in a later stage. So when a new policy comes, he
would expect it to be overturned down the road. This expectation leads to
a market under-reaction, forcing authorities to put forward a similar-kind
of regulation to enhance the functionality. However, investors know the
market will not keep climbing or dropping, their anticipation of policy
reverse strengthens. When such anticipation reaches a limit, we would
even witness markets to move in opposite directions.
4.4.
Results – Economic Growth v.s. Stock
Market
China’s stock market was relatively small compared to its GDP. The
157
stock market development of several countries shows that stock markets
grow slowly when the economy is in developing stage and the society has
not reached a certain level of wealth. Taiwan stock market was set up in
1962. In 1981, its market value accounts for only 11% of GDP, an annual
increase of less than 0.6%. The Japanese stock market was born in May
1878 under the name of the Tokyo Kabushiki Torihikijo, which initially
provided government bonds, gold and silver trading. It was closed down
during the Second World War between 1945 and 1949. After reopening in
1949, the market was renamed to the Tokyo Stock Exchange (TSE). Since
then the economy boomed till the year of 1981 before the bubble started,
its annual market capital to GDP ratio growth was not more than 1%, less
than 31% of the country’s GDP. In China, the tradable share capital to
GDP ratio kept the average of around 1% annual growth from 1991 to
2004 when it accounted for 9.11% of GDP. In 2005 after the start of stock
reforms, this ratio climbed to 17.6% in 2005 and 44% in 2006. Stock
market capitalization exceeded China’s 2006 GDP the first time on
August 9, 2007, according to the data from the China Securities Journal.
At the end of 2007, the overall capitalization of China’s stock market
reached 132.7% of its GDP.
Government policy is used to guide the macroeconomic activities in
158
a country, thus a ‘correctly’ implemented policy shall lead to a positive
development of its economy. The question is then, does China’s stock
market performance mirror the real economic growth? In order to answer
this question, I define two variables: GDP and the Shanghai Stock
Exchange Composite Index (Shanghai). GDP data used here is the
constant price year-on-year rate (source: Bloomberg). The growth rate
over the same period last year (%) is computed at constant price which is
all the final products of all resident units of a country during a certain
period of time. This is non-cumulative year on year percentage change on
GDP comparable price. Data sample is collected quarterly from Q1 1995
to Q1 2009, in a total of 57 observations.
Now I use Eviews to generate a non-restricted VAR model. Lag
intervals for endogenous defines the range of intervals. It instructs Eviews
to use the first through a certain lags of endogenous variables. Now I
need to define what the preferred lag length is. The below table exhibits
the model selection criteria for 10 lags. The lag selection criteria suggest
a model with either 1 or 7 lags. After considering SC, I use lag 1 for
evaluating VAR.
159
After the lag is set, I conduct the unit root test of variables in
all three regression forms: without constant and time trend, with constant,
and with constant and time trend. The stationarity or otherwise of a series
can strongly influence its behavior and properties. The first test does not
include intercept and trend. The augmented Dickey-Fuller (ADF)
t-statistic is at -1.065695. It is smaller than all critical values at 1%, 5%
and 10% significant levels. Therefore I can conclude to reject the null
hypothesis, meaning GDP series does not have a unit root problem and it
160
is stationary.
The second test includes intercept (constant). Again the ADF
t-statistic is smaller than all critical values. Therefore the null hypothesis
161
does not stand.
The following test includes both intercept and time trend. The results
are consistent with the two tests earlier. GDP series does not have a unit
root problem. Same tests have been done for variable Shanghai. The two
162
test results without time trend suggest stock index is stationary, while in
the test with intercept and time trend, therefore the null hypothesis is
rejected at 5% level.
The VAR estimate model is therefore defined and results are
163
generated as shown below. The model returns a very high adjusted
R-squared.
164
To analyze the appropriateness of the estimated VAR, I diagnose
the model with the following reports: AR Roots Graph, Granger Causality,
Normality Test, Impulse Response Function and Variance Decomposition.
a) AR Roots Graph. This reports inverse roots of the
characteristic AR polynomial. VAR model is stationary if all
roots have absolute value less than one and lie inside the unit
circle. There should be (number of variables) multiples
(number of lags of roots) visible on the graph. As seen from
the graph, in my model, all 4 roots lie on the unit cycle, so this
suggests that our model is stable.
165
b)
Granger Causality. Here I test whether GDP growth does
granger-cause stock market performance, or vice versa.
According to the below results, I can conclude that due to
fairly large p-values, both null hypotheses can not be rejected,
whereas a higher p-value of 0.6228 suggests GDP growth has
greater impact on stock market.
c)
Normality Test. This Reports the multivariate extensions of the
Jarque-Bera (JB) residual normality which compares the third
and fourth moments of the residuals to those from the normal
distribution. The null hypothesis is a joint hypothesis of the
skewness being zero and the excess kurtosis being zero. Any
deviation from this increases the JB statistics. Thus I reject the
hypothesis that residuals are normally distributed.
166
d) Impulse Response Function. This function traces the effect of
a one-time shock to one endogenous variable on the other
variable in the VAR. I generate below two graphs with two
orderings: left graph – impulse GDP and response Shanghai;
impulse Shanghai and response GDP. The impulse response
function of Shanghai to a shock of GDP shows a continuous
167
convergence toward zero after the first 7 periods.
e)
Variance Decomposition. This test decomposes variation in an
endogenous variable into the component shocks to the
endogenous variables. It gives information about the relative
importance of each random innovation in affecting the
variables in the VAR. The percentage of the forecast variance
due to each innovation, with each row adds up to 100. The
variance decomposition indicates that after increasing in the
first 15 periods, the percentage of the forecast error explained
by its own shocks stabilizes around 90% for the rest of the 35
period horizon. The result indicates that shocks to GDP have
little impact on stock market.
168
Based on the above results, I conclude that the real economic growth
and stock market are correlated and the economic growth to a higher
degree has ‘Granger Cause’ to the stock market performance but it does
not imply that the stock market is dependent on real economic growth.
4.4.
Event Study
The initial task is to define the event and the time period during
which the effects of the event will be examined. This is generally
recognized as an event window. In my study, I investigate what impact
government policy has on the stock market. So the event I choose is the
169
index movements and the time period is 1995 to 2008.
The second step is to determine selection criteria. There are two
main indexes in China: the Shanghai Stock Exchange Composite Index
(SSECI) and the Shenzhen Stock Exchange Composite Index (SZCI).
China launched the New Shanghai Composite Index (NSSECI, also
called G-share) on Dec 31, 2005. NSSECI consists of all companies
which completed stock reform, called G-shares. My study below is based
on the daily returns of SSECI. There are however several limitations by
choosing daily data in event study (Brown and Warner, 1985). The most
obvious limitation is normality. The daily return exhibits substantial
departures which are not observed in monthly data. The findings of Fama
(1976) suggest the distribution of daily returns is more fat-tailed than a
normal. The daily and monthly closes of the Shanghai Composite Index
from 1995 to 2008 generates the below results. The bigger standard
deviation (variance) of daily closes indicates the data are spread out over
a larger range of values, in line with Fama’s research. Nevertheless in
order to assess the particular policy effects on a single day basis, it is
necessary to use daily closes.
Mean
DAILY
MONTHLY
1759.601
1688.651
170
Standard Deviation
1047.252
990.788
The next step is the measurement of normal and abnormal
performance. The normal performance is the expected return without the
event taking place. In this case, abnormal performance is computed by
using the actual return minus the normal return. Thereafter, to calculate
abnormal return, one has to know the normal/expected return. There are
three common models to determine the expected return: constant
expected return (CER) model, market model16 and Capital Asset Pricing
Model (CAPM). As the name implies, CER model assumes the return is
fixed and the correlations between returns are constant through a certain
period of time. Although CER model is perhaps the simplest model,
Brown and Warner (1980, 1985) find it often yields results similar to
those of more sophisticated models. A market model, also called
single-index model, says stock return depends on the return of the market.
Such responsiveness can be measured by beta, a single factor, which
exhibits the relation by a stable linear. Modern Portfolio Theory
introduced by Harry Markowitz in 1952 inspired his student William
Sharpe to publish Capital Asset Pricing Model (CAPM), a comparatively
16
MacKinlay (1997)
171
more sophisticated reasoning to indicate the relationship between risk and
return and describe the pricing of assets and derivates. With CAPM,
Sharpe shared Nobel Memorial Prize in Economic Science with
Markowitz and Merton Miller. The general idea of CAPM is that
investors are compensated in two ways: the time value of money and risk.
The time value of money, represented by risk-free rate (Rf), compensates
the investors for the investment during a certain period of time. Normally
government bond rate is recognized as risk-free rate, as a state is believed
to be the lowest risk lender. Risk measure is represented by Beta (β). A
beta of one means the stock moves with the market, while a beta between
zero and one moves with the market but to a lesser degree (a conservative
investment); an aggressive stock then has a greater than one Beta; a
negative beta means thereafter a stock moves in the opposite direction as
the market. It can be calculated by covariance of a market’s return and a
certain stock’s return divided by variance of this market’s return. For
example, if one is interested in Abbott which is listed in the S&P 500,
Beta can be calculated by covariance of S&P500’s return and Abbott’s
return divided by variance of S&P 500’s return. Rm represents the
expected market return over the period, following the above example then
172
as S&P 500’s return. Rs represents the expected return of a certain stock
(or portfolio). The formula is known as:
Rs=Rf+β(Rm- Rf)
This formula can be shown further below as a linear graph with a
slope depending on β, as investors are only compensated by bearing
systematic risk, the degree to which stock changes in price relative to the
general stock market. CAPM believes if the expected return does not
meet the required return, one should not make such an investment.
However, the funny thing is, β is finally determined by a correlation
which is again calculated by several stocks’ Rs. Because of the
measurement of β and expected return, in practice, CAPM is said to be
more difficult to implement than Binormial Option Pricing Model 17 and
Black-Scholes Formula18.
Chart 37
Traditional CAPM
17
Binormial Option Pricing Model, developed by Cox in 1979, simplifies the evaluation under the
assumption of efficient market, shortened duration and price changes in a risk neutral view.
18
Mathematically more complicated but frequently used, Black-Scholes Formula, developed by Fisher
Black and Myron Scholes in 1973, looks into options from CAPM and hedging argument.
173
Return
β
Risk-free Rate of
Return
Rm- Rf
Burton (1998) reviewed CAPM and described it as: every
investment carries two risks: the risk of being in the market and the risk
specific to a company’s fortunes. Being in the market risk (β), called
systematic risk by Sharpe, cannot be diversified away by holding a
well-diversified portfolio, while the other risk, unsystematic risk, can be
diversified away by holding a basket of stocks which imitates the
movement of a certain market. Fama and French (1996) tried to separate
systematic risk from unsystematic risk by adding another two factors
beyond β. They observed that two particular types of stocks perform
better than the market: small-capitalized firms and those with high
book-to-price ratio (B/P), called ‘value’ stocks. This is called Three
174
Factor Model19. The usage of CAPM has been criticized by Fama and
French as it has sensitive restrictions such as assumption of no transaction
costs, taxes and unlimited borrow to a risk free rate. As the target is stock
index, Beta is set at 1. The risk free asset in this case is the government
bond. To assess the risk free rate, I use the average (mean) rate of
government bond from 1995 to 2008, which is 4%. Thus, all daily returns
larger than 4% are assumed to be abnormal.
The chart below exhibits an overview of the daily performance of
SSECI from 1995 to 2008. From the initial observation, we may see that
the market is more volatile in the period of 1995 to 1997, 1999 to early
2000, mid 2001 to mid 2002 and 2007 to 2008.
19
They observed that two particular types of stocks perform better than the market: small-caps, meaning
small-capitalized firms and those with high book-to-price ratio (B/P), called ‘value’ stocks. The two
factors they added into traditional CAPM formula can be reflected as Bs*SMB+Bv*HML. Bs and Bv.
SMB stands for ‘small (cap) minus big (cap)’, while HML for ‘high (B/P) minus low (B/P)’. On a rough
scale of 0 to 1, Bs equals one means it is a small-cap portfolio; equals zero means large-cap. Bv equals
one will be a portfolio with high B/P, while zero is low B/P. Standard calculation will have pre-defined
SMB and HML.
175
Chart 38
Daily Fluctuation of SSECI from 1995 to 2008
32%
30%
28%
26%
24%
22%
20%
18%
16%
14%
12%
10%
8%
6%
4%
2%
0%
-2%
-4%
-6%
-8%
-10%
-12%
-14%
-16%
5/19/08
The abnormal points returned can be summarized in the below table.
Table 6
Abnormal Points
YEAR
DATES EXHIBIT ABNORMAL POINTS
1995
2/6, 2/22, 2/24, 3/6, 4/27, 5/18-23, 5/25-26, 6/15, 7/7, 7/17,
10/25
1996
1/5, 3/4, 3/6, 4/26, 4/29-30, 5/17, 5/21, 6/5, 6/10, 6/18, 7/1,
7/16, 7/19, 9/20, 9/23,10/30, 11/1, 11/18, 11/21, 11/29, 12/2,
12/4, 12/13-19, 12/24
176
10/30/08
7/24/07
12/21/07
2/24/07
9/27/06
4/30/06
7/4/05
12/1/05
2/4/05
9/7/04
4/10/04
6/15/03
11/12/03
1/16/03
6/26/02
5/2/01
11/28/01
3/8/00
10/4/00
8/11/99
1/13/99
6/17/98
4/23/97
11/19/97
9/25/96
8/2/95
2/28/96
1/4/95
-18%
1997
2/18-19, 2/21, 3/21, 5/8-9, 5/14, 5/16, 5/22, 6/6, 6/20, 7/2-3,
7/7, 8/14, 9/22-24, 10/27-28
1998
1/13，3/27，7/20，8/17, 8/19,
1999
5/10, 5/19，6/14, 6/16, 6/28，7/1，7/6, 7/20，9/9
2000
1/6, 1/11, 2/14, 2/28, 3/16, 8/31, 10/27, 11/24
2001
1/15, 7/30, 9/18, 10/23, 11/7
2002
1/14, 1/17, 1/23, 1/28, 1/31, 5/27, 6/6, 6/24, 12/16
2003
1/14, 3/27, 9/15, 10/10, 11/20, 12/22
2004
1/5, 7/1, 8/4, 9/15, 11/10
2005
2/2, 6/8
2006
5/12, 6/7, 7/13, 12/11, 12/29
2007
1/15, 1/31, 2/2, 2/27, 4/19, 5/30, 6/4, 6/28, 7/5-6, 8/20, 9/11,
10/25, 11/8, 11/14, 11/22, 11/29
2008
1/21-22, 1/28, 2/4, 2/25, 3/24, 3/27-28, 4/1, 4/7, 4/9, 4/23-24,
4/30, 5/7, 5/20, 6/10, 6/18-19, 6/27, 7/7, 8/8, 8/11, 8/18, 8/20,
9/16, 9/19-22, 10/6, 10/27, 11/10, 11/18-19, 12/3, 12/23
Except the points on Jan 13 and Aug 17, 1998 which were created by
177
the Asian financial crisis and the enormous flood in China, almost all
other abnormal points were created directly or indirectly by government
policy changes (please refer to the policy summary table). Within them, 3
market
fluctuations
were
not
directly
corresponding
to
the
policy/announcement releases but were indirectly caused by the rumors
before or after the policy/announcements.
Table 7
Abnormals caused by Market Rumors
Date
SSECI(%)
SZCI(%)
5/19/1999
4.85
4.99
7/20/1999
6.46
8.35
1/23/2002
6.35
7.13
The extreme volatility can be observed from May 18 to May 23,
1995 which resulted from ‘327 t-bill scandal’ happened in February 1995
and eventually led to the collapse of the whole T-bond futures market and
the bankruptcy of the country's largest brokerage company. This
manipulation case caused RMB 6 billion loss in a single day. It was
widely compared to the Barings Bank scandal which took place in the
same month of 1995. After a 3-month hot debate inside the government,
t-bill future trading was suspended from May 18 by the CSRC. Due to the
suspension of t-bill future trading, enormous amounts of capital poured
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into the stock market which led to an index increase of almost 48% in the
next 3 trading days. On May 22, the State Council announced the new
share issuance scale to be released in the second quarter. This stopped the
3-day blowout and started a bear run.
What can also be concluded from the results is that the abnormals
were generally created by discreet policy incidents, only a few were
caused by sequential policy changes such as the trading commission
change on April 5, 2002 followed by another adjustment on October 10 in
the same year (except the interest rate adjustment on March 27, 1998). If
the government would mainly use sequential policies to regulate the stock
market, market’s correlation to macro economy may be more obvious.
4.5.
Stock Reform
The regulation published in May 1992 formally defined four equity
ownership structures in China: state share, legal person share, public
share and foreign share. Both state share and legal person share are
categorized as non-tradable shares. Public share is also known as
individual share, which is issued for company employees or external
people. Different from other industrialized countries, the primary reason
for creating the stock market in China was to allow SOEs to raise capital
179
from Chinese households and from foreign entities. The biggest barrier,
according to many experts, is the state share, created by the government
for starting up the stock exchange market. The origin of state shares,
recalled by Liu Hongru, the ex-chairman of the CSRC, was old
communism thinking under the principle of public ownership: all those
countries which have stock holding systems and stock exchange markets
have to privatize properties. As China is a communist state, this cannot be
the path. What was agreed at that time was that the companies which
changed to the stake holding system must keep 60% state shares. This has
created a historical problem which substantially decreases the self-control
of the market as investors cannot thoroughly evaluate a company by its
stock price.
According to Chinese law, tradable and non-tradable shares entitle
the same rights such as the rights to dividend, voting etc, except for
liquidity. This liquidity issue causes a price differential. Meanwhile, it
costs more to obtain tradable shares than non-tradable shares, as the
valuation of the latter is based on the net asset value of listed companies.
Additionally, the demand of tradable shares is relatively higher, since the
pricing mechanisms for these two categories are different. In exchange
for liquidity, the shareholders of non-tradable shares shall pay
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consideration to those own tradable shares as the additional liquidity
generated by non-tradable shares will cause dilution of the company
shares in the market. In order to maintain the stability of share price, the
Measures for the Administration of Full Circulation Reform of Listed
Companies has enforced a 12-month hard lock-up on non-tradable shares
which are converted into tradable shares.
4.5.1.
Share Structure
The features of concentrated ownership structure appear to be
monitoring the management and expropriation of minority external
shareholders. A concentrated external shareholder shall have higher
interest to monitor the management closely. This can decrease agency
conflict. The earliest research on corporate ownership may be traced to
Berle and Means (1932). They believe a concentrated power has a
positive linear relation to the company performance as a dispersed
ownership arises a free rider problem. This theory has been supported by
the research of Shleifer and Vishny (1986) who found out the
management intends to be less opportunistic in existence of a large
external shareholder. Agrawal and Mandelker (1990) provided empirical
evidence on the above finding and further proved that large shareholding
has positive monitoring effect and leads to better performance. Despite
181
the above literature, there are a number of criticisms on the structure of
large shareholder. Leech and Leahy (1991) analyzed the result of the
separation of ownership and control power on British companies. They
found
a
significant
negative
relationship
between
ownership
concentration and the firm’s value and profitability. Shleifer and Vishny
(1997) argued that in some countries, agency conflicts come from the
disharmony between major and minority shareholders instead of the
dispute between managers and shareholders. Large investors can be
effective in solving agency problem but due to the inconsistency of
interests between large and minority shareholders, concentrated
ownership may also inefficiently redistribute or expropriate wealth from
other investors to themselves.
SOEs in China, as a matter of fact, have the characteristics of
concentrated ownership and state share. Research of the effects of state
share in corporations can be seen in both positive and negative terms.
Government’s positive role has been described as a helping-hand model
where it corrects market failure and companies gain from their close ties
to government. Shareholders’ benefit from their connection to the
government is not only observed in developing countries but also in
developed countries. The legal protection is less strong in economies
182
during transition. David’s (1996) finding on the research of ambiguous
property rights in China proved that state shareholding can prevent
malicious violation of government. Additionally, Johnson et. al (2006)
reported that Malaysian firms with political connections increased in
value after the imposition of capital controls. Sapienza (2004) found that
Italian state-owned banks charge lower interest rates compared to
privately owned banks after controlling, and their lending behaviors at the
local level are related to electoral strength of the political party affiliated
with the bank’s top management. Faccio et al (2004) analyzed a sample of
357 companies from 35 countries and their matching peers over the
period of 1997 to 2001 and concluded that firms with political
connections are also more likely to receive bailouts when they face
financial distress than firms without such connections.
While on the other hand, as advocated by Shleifer and Vishny, the
negative role of government, presented by holding state share, is the
grabbing hand.20 Besides its commercial target, companies with major
state shareholders have a political goal, which leads to heavy political
interference and distorts the best allocation of resources, according to
Shleifer and Vishny (1994). In China, SOEs’ initial principal is public, an
20
The book ‘The Grabbing Hand’, by Andrei Shleifer and Robert Vishny, published by Harvard
University Press in 1998.
183
abstract
disability
subject.
State-owned
asset
supervisors
and
administrators, such as local government and commissions, can not
directly benefit from the quality improvement and profitability of SOEs,
they lack of incentives to control and supervise the management. The
weak domination of government over management results in the insider
control problem. In addition, due to the illiquidity of state shares and
limitation on transfer, the regulators can not do the proper assessment of
the management and the lesser possibility of take-over enhances the
insider issue. He (1998) found that the bigger shareholding of state share
in China, the worse the insider problem is. The theory of incomplete
contracts suggests that the greater power one party has over the other, the
less creditability the agreement is. Government, which has the biggest
domination power, leads to its low creditability. This decreases the
incentives of managers and employees. Furthermore, as the law-makers
for the market, government acts also as a shareholder. The conflicting
roles as both judge and player cause abuse of power and damages market
rule.
Legal person ownership is the second largest identity in most of the
SOEs. It was created by authorities to aid the transition from state-owned
to private-owned. This ownership category is a mixture of various
184
domestic institutions, composed of private companies, SOEs and
non-bank financial institutions such as investment funds and securities
companies. Researchers in China generally believe legal person
shareholding has positive influence to the company profitability, as the
purpose of such investment is profit seeking. Additionally, it does not
have the political objectives as state shareholders so they have relatively
more freedom than state shareholders in deciding profit allocation and
strategy implementation. Due to its illiquidity, the only way to benefit
from this ownership is dividend. As such, they are not only motivated to
pursue the profit maximization but also have the ability to effectively
monitor the management. Unlike the representatives of state shareholders
who are appointed by the government, representatives of legal person
shareholders are elected to the board of directors and the supervisory
board. So in practice, legal person shareholders increase the alignment of
interests between managers and shareholders.
As for the public shareholding, the common view is that it has
passive supervision function on the company. Due to the limitation of
individual wealth, public shareholders normally have only a small
percentage of shares. The good of active supervision is divided by all
shareholders but the responsibility for the bad is not borne alone.
185
Therefore, the public shareholders have strong incentive to free ride.
4.5.2.
Consideration/Compensation Plan
No matter whether tradable shares or non-tradable shares, the prices
should be related to the performance of the company itself, the price
discrepancy between the two categories arises mainly from their liquidity
status. Once non-tradable shares are floating, they bear the same
characteristics as tradable shares. Liquidity enables securities to undergo
a high volume of trading without significant change in price. As known
from all financial books, stock’s inherent value comes from its future
return. Such theory has a hypothesis which assumes the investor must
hold the stock till the future return is claimed. However, a stock has also a
marketability which enables investors to trade. Imagining two stocks
which have the same future returns and risk, investors would intend to
pay a higher price for the marketability/liquidity right which enables them
to enter and exit at any time. How to evaluate such liquidity rights
determines
a
company’s
consideration/compensation
plan
when
processing the reform.
Theoretically, we may consider the floating of non-tradable shares as
if an investor purchases non-tradable shares and its put option. This put
option can be used to price the liquidity right of non-tradable shares. Such
186
option can be calculated by option pricing models such as the
Black-Scholes model. In practice, the net asset per share can be used to
evaluate non-tradable shares. Another often used method is reasonable
P/E ratio. This methodology takes the average P/E ratio of the companies
of the same industry in the developed market as the reasonable ratio.
Based on a company’s earnings per share in the previous year, one can get
a reasonable price after non-tradable shares become floating, then comes
up with a compensation plan after taking the costs of holding tradable
shares into account. This approach however assumes the value of tradable
shares remains the same.
Below is a summary of the consideration practices adopted by listed
companies in China:
a) Shares Transfer
Non-tradable shareholders agree to give away and transfer certain
amount of non-tradable shares to the holders of tradable shares, to receive
the right to trade the non-tradable shares.
b) Cash Payment
Holders of non-tradable shares will pay consideration in cash to the
holders of tradable shares.
c) Recapitalization of Retained Earnings
187
A listed company will capitalize its retained earnings and issue new
equity shares. The holders of non-tradable shares will pay the holders of
tradable shares the new equity shares they received as consideration.
d) Unilateral Reverse Shares Split by Non-tradable Shareholders
The overall number of non-tradable shares is reduced and the share
ownership percentage of the owners of tradable shares will increase
proportionally. This method of consideration achieves a similar result as
type a.
e) Buying Tradable Shares at a Fixed Price
Controlling shareholders of non-tradable shares agree to purchase
certain tradable shares at an agreed fixed price from tradable
shareholders.
f) Issuing Put Warrants by holders of non-tradable shares
Holders of non-tradable shares transfer the put warrants to holders of
tradable shares at no cost as consideration to receive the right to convert
their holdings.
g) Combination of the above methods
The combination of practice ‘a’ and any forgoing methods are most
popular and widely adopted.
4.5.3.
The Development of Stock Reform
188
From 1993 to 2002, the government had made several attempts to
implement stock reform but the results were disappointing. Many had
feared the huge supply of non-tradable shares would outstrip demand
leading to a collapse of the market.
a)
In the January of 1993, China tried to trade state shares.
Shanghai Jiafeng (600606), the first guinea pig of the program, traded its
state shares suddenly in the market. The market price was around 12 yuan,
but the earnings per book were worth only 1.63 yuan. The result was a
disappointing response of the market with only 23’908 shares being sold.
b)
The highlight of the Chinese financial market was the share
buybacks in Shanghai stock market in 1999. In April, Yunnan Yuntianhua
(600096) proposed to buyback 200 million state shares. On October 19,
Shenergy (600642) announced a buyback plan of 1 billion shares. Ten
days later, Tsingtao Brew (600600) announced to take back 200 million H
shares. The buyback pushed the individual stocks up but didn’t turn the
bear run around.
c)
The next try was publicly announced as ‘a reduction of state
shares’ in October 1999, to adjust the state capital structure. The principle
was the price of the entitled right must be bigger than its book value but
smaller than 10x P/E. This principle was generally accepted by the market
189
with great enthusiasm. On November 29, 10 potential companies were
announced, in which 9 of them were the top movers. When two
companies Jialing Industrial (600877) and Guizhou Tyre (000589) were
finalized as pilots, share prices climbed 4.61% and 5.07% respectively
after announcement. Goodness doesn’t last long. On Dec 13, the market
changed the attitude dramatically because both companies chose to sell at
the top limit of 10x P/E. Till the end of the rights offer, Jialing sold
81.99% of its state shares, while Guizhou Tyre made only 75.29%. The
unpleasant results left the story unfinished.
d)
In April, 2000, transferable warrants of SOE state shares were
traded in the market. The difference between normal right and a
transferable warrant is that the latter can be transferred to other investors.
For example, when SOE entitles a right for its state shareholder to buy
additional shares, the state shareholder can trade this right on the market.
This special right was created between 1994 and 1997 but cannot be
traded until 2000. CSRC announced that such warrants can be traded on
the market according to their issuing dates, meaning that if a company
issued such warrants at different times, the earlier one would be tradable
first in the market than the latter one. There are around 168 firms in
Shanghai and Shenzhen which issued this kind of right, accounting for
190
3.3 billion shares or 3.96 percent of A-share markets.
e)
On June 12, 2001, the State Council announced a new
reduction plan: IPOs include a slice of state shares equivalent to 10% of
the total offering. The return from state shares goes to the local social
security fund. For example, if a SOE has 400 million value of state shares.
The company now issues 110 million shares IPO at 10 yuan, in total 1.1
billion yuan. 1 billion capital raised by the IPO belongs to the company;
100 million goes to local security fund, meaning that state shares reduced
to 290 million shares. From Jul 25 to Sep 30, 15 firms practiced this new
regulation, including Fiberhome Telecom (600498) and Kweichow
Moutai (600519). The market fell. This supposed-to-be win-win plan
surprised the government with a 30% drop of SSECI in the next four
months.
f)
January 26, 2002, the CSRC published on its website the
systematical result of reducing state shares and proposed a scheme named
‘discount placement’. The program proposes a public bid of a portion of
state shares. The final price of the bid is set to be the accepted standard.
Then according to the price difference between this final bid price and the
market price, shareholders get compensated by entitling rights or shares.
The Shanghai and Shenzhen indexes responded with a nearly 7 percent
191
slump, although the scheme was only under discussion. On January 28,
CSRC held a conference and stopped this scheme. Markets reacted
positively on the cancelling of this plan.
On January 31, 2004, China released ‘Some Opinions of the State
Council on Promoting the Reform, Opening and Steady Growth of
Capital Markets’. The regulation presented authorities’ intention to effect
stock circulation reform in a ‘proactive, reliable and orderly’ manner. On
April 29, 2005, the CSRC promulgated ‘Notice of the China Securities
Regulatory Commission on Piloting the Share-trading Reform of Listed
Companies’, announcing the start of a pilot program. On May 9, the first
trading day after the one-week Labor Day holiday, four pilot companies
were announced: Tongfang (600100), Sany Heavy Industry (600031),
Shanghai Zi Jiang (600210) and Jinniu Energy (000937). This was a
threshold of the new stock reform. These four companies come from
different industries. Sany and Zi Jiang are private enterprises, while the
other two are SOEs. From an ownership point of view, the four
companies have relatively simple shareholding structure. The biggest
shareholders in Tongfang, Sanyi and Jinniu hold more than 50% stake,
namely 50.4%, 72.4% and 74.5% respectively, while the largest
shareholder Zijiang Holdings has a comparatively lower stake, 36.8% of
192
Zi Jiang. All of the four only have A shares, no issuance of B or H shares.
The Shanghai and Shenzhen markets retreated 2.4% and 3.3% on May 9
trading day.
4.5.4.
Case Studies
Did the pilot program launched in 2005 work as hoped? Does the
government finally manage to proceed with the stock reform? Here I’d
like to conduct case studies on Sany after the pilot program
On May 9, the board passed the proposal that every 10 tradable
shares entitle 3 shares and RMB 8 in cash. Based on the last trading day,
Sany has 240 million shares including 60 million tradable/liquid shares.
Total market value is RMB 4.7 billion. This means, to keep the equity
unchanged, the non-tradable shareholders shall pay 18 million shares and
RMB 48 million to tradable shareholders. On May 11, share price of Sany
was up 10%, reaching the daily limit. On May 14, Sany corrected the
2004 annual distribution and corporate action plan from 10-share
receiving 5-share and RMB 1 to 10-share receiving 10-share and RMB 2.
The new plan increased company equity and cash dividend. On May 25,
after the road show and long discussion with investors, Sany agreed to
increase the share entitlement by 0.5 shares. On June 10, 2005, the
adjusted share reform plan of Sany was successfully passed by tradable
193
shareholders. Thereafter the tradable shareholders shall receive 21 million
shares, 3 million shares more.
With regard to the most concerning issue – reducing shareholding
by large non-tradable shareholders, Sany announced that non-tradable
shareholders will not sell shares within 24 months after the first trading
day of share reform implementation, and the market price of any
continuing 5 trading days shall be above or equal to RMB 19.
The graph below demonstrates the stock performance of Sany
compared with the Shanghai New Composite Index since 2006. By
eyeballing the graphs below, we may observe that the peaks and troughs
align almost in the same places and the upturns and downturns coincide.
At least two styled facts or regularities can be found: persistence and
co-movements. After stock reform, the performance of Sany has
obviously outperformed the index.
Chart 39
Sany v.s. SSECI (rebased)
194
1,950
1,800
S any
1,650
Shanghai
1,500
1,350
1,200
1,050
900
750
600
450
300
150
Source: Bloomberg
On June 19, 2005, China announced 42 more companies which
would go through the stock reform. Till July 20, these 42 companies
released the reform plan. By August 19, all 46 companies including the 4
pilot firms finished the execution of the reform. On the evening of August
23, the CSRC, the State Asset Commission, the Ministry of Finance, the
Ministry of Commerce and the People’s Bank of China jointly
promulgated ‘Guiding Opinions on Share-trading Reform of Listed
Companies’. The documentation believes vital progress has been made in
the various reforms and the pilot work has been completed smoothly. As
policy expectation and market expectation on the reform are becoming
195
12/19/08
10/24/08
8/21/08
6/26/08
4/28/08
2/29/08
12/26/07
10/31/07
8/29/07
7/4/07
5/9/07
3/7/07
12/29/06
11/3/06
9/1/06
7/7/06
5/12/06
3/10/06
1/4/06
0
increasingly stable, it has laid a solid foundation and created good
conditions for overall steady and positive shifting of the reform. On
September 4, the CSRC published and implemented ‘Measures for the
Administration of the Share-trading Reform of Listed Companies’. This
marks the comprehensive launch of stock reform. On September 12, the
first batch of 40 companies entered the reform. Afterwards, one batch was
brought forward each week.
The share reform has inspired creativity and improved corporate
quality. Started in 2005, companies have applied more combinations of
share, warrant, right, and share or cash dividend, buyback and etc. As an
unavoidable path to the marketization of stock markets, stock reform has
been an important page of China’s stock market development. The
policies released and implemented during the period are undoubtedly
necessary and helpful in the execution of the reform.
4.4.
Multi-level
and
Functional
Financial
Market
China did not legally define the existence of most financial
instruments. Old Securities Law applied a single product transaction
principle, namely only spot transactions are allowed and forbid any
option, future or credit trading of any kind. Such an environment plus the
196
old ownership structure provided big institutional investors the
opportunities to manipulate the market, as smaller investors can only do
one-side trading, meaning only buy low and sell high. Such single
directional market plus high retail investor dominance often led to higher
volatility, frequently witnessed in stock markets of emerging markets.
Even in existence of the daily movement limit (10%), the volatility in
China’s stock market is still higher than those of developed markets. It
was the earliest hit by the sell-off in 2007 compared to what developed
markets experienced and exhibited a steeper stock market decline. It was
also the earliest to welcome relief. In order to diversify risks and reduce
volatility, securities credit trading is in discussion.
The original financing service provided by securities companies in
China was overdraft, where securities companies keep collateral from the
clients. A contract between two parties defines the maximum overdraft
amount, interest rate, liquidation and etc. Due to gradually closer
monitoring by the authorities, financial institutions’ overdraft services
become more and more undercover. Presently, securities companies and
fund managers can do inter-bank borrowing and stock Lombard loans.
Banks’ credit thus enters the stock market through a covered channel. It’s
hard for authorities to monitor and regulate. Additionally, credit trading
197
will largely increase brokerage operational revenues which came only
from trading commissions before. Securities credit trading also offers
diversified investment opportunities. It is prepared for different risk
preferences. Investors can hedge their investment and lower risks.
Commercial banks, insurance companies and securities companies can
take the opportunity to allocate resources in a more efficient way.
Securities credit business also connects the capital and money market.
The earliest securities credit trading can be traced back to the year
of 1607, when people did such trading on the shares of Dutch East India
Company21. United States started to regulate securities credit trading after
the Securities Act of 1933 and the Securities Exchange Act of 1934.
Based on these two Acts, Japan enacted Securities Exchange Law in 1948
and started securities borrowing trading in 1951. Securities lending
business appeared in 1954 followed by the setup of its first securities
finance company. From 1962 to 1989, Taiwan’s securities lending and
borrowing business was done through banks which acted as agent due to
its small scale. Only after 1990 when the ‘Operational Regulations for
Securities Firms Handling Margin Purchases and Short Sales of
Securities’ was implemented, the modern securities credit trading
21
Dutch name ‘Vereenigde Oost-Indische Compagnie’,
198
business in Taiwan started. With regard to the service provider, there are
currently two models which widely adopted in the world. One is
recognized as a distributed/marketized model, represented by the USA for
instance, meaning securities companies may offer such business with
their own capital and securities. The risk is borne by the service provider.
Authorities only perform a supervisory function. On the other hand, some
countries such as Japan and Korea apply a concentrated/specialized
model which allows only specific companies to do such business.
Nowadays, there are three companies in Japan conducting the business,
namely Japan Securities Finance Co., Ltd, Osaka Securities Finance Co.,
Ltd and Chubu Securities Finance Co., Ltd. Korea Securities Finance
Corporation is the only authorized institution engaged in this business in
Korea.
Earlier in mid 2006, the CSRC promulgated ‘Measures for the
Administration of Pilot Securities Lending and Borrowing Business of
Securities Companies’. This has been regarded as a milestone in China’s
securities trading history. In August 2006, the Shanghai and Shenzhen
stock exchanges implemented the rules for securities credit trading. The
rules detailed the lending/borrowing period, collateral requirement, loan
to value ratio, maximum lending/borrowing limit on a single stock and
199
target securities. Due to several reasons the business has not been
officially opened for the next two years. In April 2008, the CSRC released
‘Regulation on the Supervision and Administration of Securities
Companies’ which officially includes securities lending and borrowing
business in securities companies’ business range. Later in October 2008,
the CSRC permitted securities firms to use their own capital and
securities to experiment with margin trading. The initial margin is set at
50% of the purchase price when buying eligible securities or 50% of the
proceeds upon a short sale. The launch of securities credit trading is
expected during the course of 2009.
The revised Securities Law (on October 27, 2005) made some
breakthroughs in securities transactions. First of all, Article 39 defines
that ‘all stocks, corporate bonds or any other securities that have been
publicly issued according to law shall be listed in a stock exchange as
legally established or in any other places for securities transaction as
approved by the State Council. This leaves room for the setup of a
multi-level
capital
market
as
the
earlier
regulation
forbids
over-the-counter (OTC) transactions. In addition, Article 40 suggests
securities regulatory authorities may adopt trading in different means, not
only centralized transactions. And Article 42 reads ‘securities transaction
200
shall be carried out in the form of spot goods as well as any other form as
prescribed by the State Council’, which builds the legal basis for
derivatives products.
Securities market not only finances different types of companies in
different stages, but also protects investors’ interests. A mature market has
diversified trading systems which serves unique financing needs and risk
preferences. A prominent problem in China was that the direct finance
proportion is too low and indirect finance was mainly provided by banks.
The average financing ratio of loan accounts for an average of about 80%
of the total transactions in the last eight years, compared with less than
4% from corporate bonds (see Table 8 below). The bond market is
underdeveloped when compared with its gross GDP and the size of its
corporate sector. China started to accelerate development of the corporate
bond market in 2006 to reduce companies’ reliance on bank loans and
improve the central bank’s ability to manage the economy. Selling
corporate bills allows companies to make better checks on investor
perceptions of risk and meanwhile government will not lose ownership
control of some giant corporations. In addition, developing the bond
market helps to diversify the risk in the financial system and act as a
catalyst for reform of the state-owned commercial sector. The ongoing
201
financial crisis has also urged the structural change in European corporate
finance, when European companies have been able to issue some of the
largest bonds seen in certain sectors in 2009 and euro-denominated bonds
were sold during the first quarter than at any other time, according to
Société Générale.
Table 8
Non-Financial Institutions’ Financing Activities
In %
2008
2007
2006
2005
2004
2003
2002
2001
Loan
83.1
78.7
82.0
78.1
87.9
85.1
80.2
75.9
Stock Market
6.1
13.1
5.6
6.0
5.2
3.9
4.0
7.0
Gov-Bond
1.7
3.6
6.7
9.5
10.8
10.0
14.4
15.7
Corp-Bond
9.1
4.6
5.7
6.4
1.1
1.0
1.4
0.9
Source: China Monetary Policy Report, 2001 to 2008. 2007 government bond
data excludes the special bond issuance of RMB 1550 billion. Corporate bond
includes corporate bond, short-term financing bill and mid-term paper.
Chart below illustrates the above table more vividly, excluding
corporate bonds. The over concentration of financial assets in banks
accumulates big financial risks. To ensure capital security, banks act with
characteristics of cis-periodicity, meaning they expand credit activity
when economy booms and decrease loan lending when economy shrinks.
This holds back the development of commercial banks and hinders the
conduction of central bank’s monetary policy as their lending terms do
202
not change upon an accommodative policy. In addition, the five banks,
Bank of China, Agricultural Bank of China, China Construction Bank,
Industrial and Commercial Bank of China and Bank of Communications
dominate the market. Such large banks intend to lend more to big and
middle sized enterprises.
Chart 40 Non-Financial Institutions’ Financing Structure
Stock Market,
6.1
Government
Bond, 1.7
Loan, 83.1
Therefore, it is necessary to enrich the financial market and
build a multi-level capital market. Main board market generally has
higher listing requirements on corporate size, operational and profit
stability. Such regulations limit the development of smaller companies.
Second board market allows SMEs to raise funds. In China, SMEs
accounts for 99% of the total number of companies and they weight about
60% of GDP at the end of 2005. The 11th Five Year Plan has emphasized
the importance of SMEs and intends to increase the weight of GDP
203
contribution to 65% with supportive policies, a 1% annual growth.
Worldwide there are two popular types of second board markets:
a)
Attached to the main board: This type of second board
market has the same trading system as the main board and
probably also the same supervision standard and
management. The only difference is the listing standards.
In practice, companies are listed firstly in the second board
and then upgraded to the main board when they meet
certain requirement, such as Britain’s AIM, or they are
listed parallel to the main board, such as Hong Kong’s
Growth Enterprise Market (GEM).
b)
Independently running: This type of second board market
has a unique trading system and listing requirements. The
typical success examples are Japan’s JASDAQ, Taiwan’s
ROSE/TAISDAQ and USA’s NASDAQ which contains
also main board and growth enterprise market. On the
contrary, Germany’s Neuer Market is a failure. Neuer
Market was open in March 1997 but closed down in June
2003. In the peak time, Neuer Market had more than 300
listed companies. However, after the year of 2000, due to
204
the bursting
of the Internet
bubble,
low listing
requirements and false financial data led to the failure.
Table 9
Comparison of Capital Market Levels
USA
Level
NYSE, Dow Jones
1
BRITAIN
CHINA
London Stock
Shanghai,
Exchange
Shenzhen
(official list such
as FTSE
companies)
Level
NASDAQ
2
Alternative
GEM Launched
Investment
on May 1, 2009,
Market (AIM),
Shenzhen SMEs
OFEX
Market
Level
Over-the-counter
Regional Capital
Agency Share
3
Bulletin Board
Market
Transfer System
(OTCBB), the Pink
(Old STAQS and
Sheets,
NET)
Regional
OTC Market
Level
Private Equity (PE)
PE/VC
PE/VC
(fast
205
4
/Venture Capital
growing market)
(VC)
Since 1998, China has been considering the launch of second board
market. China’s stock market is immature and lacks regulation. To
promote the setup of second board market step-by-step and additionally
due to the fact of SMEs’ economic importance, Shenzhen launched SMEs
market in May 2004.
In 2007, China highlighted the plan to continue the construction of a
multi-level financial market. The data from Zero2IPO shows the IPO
listing in Shenzhen SMEs market has been the primary exit channel by
private equity and venture capital investors. On March 31, 2009, the
CSRC promulgated ‘Administrative Measures for Initial Public Offerings
and Listing on the Second Board’, which announced the second board
market, also called GEM, is launched on May 1, 2009 though the first
company may only be listed as early as August.
Table 10 IPO Listing as Exit for Private Equity and Venture Capital
LISTING
LOCATION
2007
Transactions
2006
%
Transactions
%
206
SZ SMEs
42
42.0%
16
53.3%
NASDAQ
27
27.0%
7
23.3%
NYSE
11
11.0%
0
0.0%
HK MB*
11
11.0%
1
3.3%
HK GEM
3
3.0%
1
3.3%
Korea GEM
2
2.0%
0
0.0%
Tokyo
2
2.0%
0
0.0%
SSECI
1
1.0%
0
0.0%
Singapore
1
1.0%
4
13.3%
SESDAQ*
0
0.0%
1
3.3%
In Total
100
100%
30
100%
Mothers
MB
MB stands for main board market. SESDAQ stands for Stock Exchange of
Singapore Dealing and Automated Quotation Systems
In addition, Shanghai Stock Exchange is presently examining a
proposal which allows foreign qualified multi-nationals to sell A-shares
or depository receipts and the government has already begun the
development of an international board. The plan was initiated as early as
207
2007 but was shelved over fears of a stock glut. As the market stabilizes,
government hopes that the listing of foreign companies would soak up
excess liquidity and avoid possible equity-market bubbles in the future.
On the other hand, listing of foreign companies would also help to diverse
domestic investors’ risk. Although attempts to make the Yuan an
international currency still face difficulties, government has elaborated
the plan of its international status by 2020. The international status of the
Yuan has been improving in recent years, due to the country's currency
swap with trading partners and the trial of international trade settlement in
Yuan. According to the National Development and Reform Commission,
since mid-December 2008, the government has signed currency swap
contracts worth 650 billion Yuan (USD 95.6 billion) with Hong Kong, the
Republic of Korea, Malaysia, Belarus, Indonesia and Argentina.
Authorities also draw the roadmap to build Shanghai as a global shipping
hub able to allocate international shipping resources by the year of 2020,
drawing from the experience of existing international financial centers –
Hong Kong, London and New York. The Shanghai port was ranked the
world's second for handling 28 million standard containers in 2008. As
one of the major policy breakthroughs, this plan will open up China's
high-end shipping and financing services as the government will allow
208
major domestic shipping companies to set up financial leasing firms and
encourage such firms to trade and issue bonds on the Shanghai-based
inter-bank market.
To enhance the IPO exit framework, a comprehensive market entry
supervision system is necessary. The restriction on market entry could
create rent-seeking phenomenon and corruption (Grossman and Kim,
1995). Additionally, an uncertain, mean and opportunistic supervision
system may cause high costs which is much larger than the short-term
benefit (Sachs, Woo and Yang, 2003). Two kinds of offerings are widely
used – best efforts offering and firm commitment offering. In a best
efforts offering the underwriter, the bank or brokerage firm hired to sell
the shares, does its best to sell the issuing company’s shares. But it does
not guarantee the sale amount nor buy the share outright. The more
common practice is firm commitment, where the issuer and underwriter
agree upon a share sale amount and the underwriter guarantees its
commitment by purchasing the securities themselves if the amount is not
fulfilled.
There are three kinds of IPO sales: fixed price, auction and
book building. Fixed price IPO is the traditional way, where the issuer
and underwriter do research on the likely market value of the issuing
company, agree on an issue price and determine how many shares will be
209
offered based on the capital the company wants to raise. The subscribers
then may fill in application forms and subscribe at such a price. However,
investors may not necessarily be allocated all the shares they committed
to buy. An auction based IPO requires all investors to declare their
committed price and quantity within a time limit. After the bid closure,
the underwriter accumulates all commitments starting from highest offers.
The price when the accumulated subscription reaches the authorized
amount is the issuing price. All offers above such price win the bid. The
investors then buy the shares either at their bid prices (discriminatory
auction) or all purchase at the same price (uniform price auction). A book
building is a process of price discovery. In the pre-selling period, the
issuer and the underwriter (also called book runner here) perform a road
show to collect investors’ opinion and in the mean time also disclose
information on issuing company. Within a price band, investors present
their offering price and quantity. The underwriter thereafter evaluates all
offers and sets the final price. Under such a mechanism, the underwriter
controls the allotment of stocks.
The stock issuance policy in China had restricted requirements, such
as an IPO must have a price to earning (P/E) ratio less than 20 times;
raised capital must not be more than double the net assets etc. In recent
210
years, the government has been making efforts to marketize its stock
selling mechanism. From 1990 to early 2000, IPO applications were
examined and approved by the Stock Issuance Examination and
Verification Committee of the CSRC. In August 1999, the CSRC allowed
underwriters and their clients to set their own IPO prices instead of a
fixed one set at a P/E ratio between 12 and 15. In the period of March
2000 and November 2001, the CSRC eased the limitation on IPO price.
The average IPO P/E during this time was more than 20. But the P/E
requirement was re-enforced later due to a bear market starting from the
second half of 2001. In addition, from March 2001, IPO applications shall
be processed and recommended by securities companies, then brought to
the CSRC for approval. Many IPOs have been approved in this way but
in absence of securities companies’ supervision after listing, many of
them encountered problems. As such, from February 2004, Beijing
launched a whole-new so-called sponsor system. To avoid faked-financial
IPO applicants, the underwriter and the client were bundled together. IPO
applicants must be recommended and pledged by a sponsor and sponsor
institution. After listing, they keep their responsibility of supervising the
listed company. In case of a listing fraud or a financial loss immediately
after listing, the sponsor and sponsor institution business will be ceased
211
temporarily or even dismissed. To strengthen market supervision and to
relax government influence, authorities abolished the requirement that
intended raised capital must be less than 2 times its net assets. Such
capital can be decided by the shareholders. At the end of 2004, the CSRC
promulgated
‘Circular
on
Several
Issues concerning the Trial
Implementation of the Price Inquiry System for Initial Public Offerings’.
The price inquiry system has been changed from administrative pricing to
marketized pricing starting from 2005. The Circular defines which
subjects of price inquiry can be conducted by securities investment fund
manager, securities company, trust investment company, finance company,
insurance company, QFIIs and other CSRC approbatory institutional
investors. The implementation of ‘Administration Measures of Securities
Issuance and Underwriting’ since September 2006 means it is not
necessary for all companies to go through the two-phase price inquiry.
For those to be listed on the main board, the inquiry shall be divided into
two phases – the initial inquiry and the accumulated bidding inquiry. For
those to be listed in Shenzhen SMEs Board, the IPO price can be
determined by initial inquiry only.
Chart 41 IPO Issuance Policy Change22
22
Issuance quotas are RMB 5 billion, 5.5 billion, 15 billion and 30 billion in the years of 1993, 1994,
1996 and 1997 respectively.
212
Policy
Less than
65% of total
equity
Less than
65% of total
equity
Less than
65% of total
equity
Less than
65% of total
equity
Less than
65% of total
equity
Less than 2x
net asset
Less than 2x
net asset
Decided by
shareholders
Fixed IPO
price
12-15x PE
Booking
building and
fixed price
(Aug 1999)
Booking
building and
fixed price
Less than
20x PE
Less than
20x PE
Less than
20x PE
Less than
20x PE
Issuance
quota
limitation
Issuance
quota
limitation
Issuance
quota
Security
company
recommends
Security
company
recommends
Security
company
recommends
Sponsor
system
Sponsor
system
Examination
and approval
system
Examination
and approval
system
Approval
system
Approval
system
Approval
system
Approval
system
Approval
system
Approval
system
1993
1997
Mar 2000
Mar 2001
Nov 2001
Jul 2003
Feb 2004
May 2006
On one side, authorities must provide an easy issuance standard,
allowing companies to raise capital. On the other side, in order to attract
investors and maintain social stability, they need to provide necessary
legal protection. The two contrary goals frequently lead to two
consequences: ease standard causes market downturn, while higher
standards may result in a shrinking of the financing function. Therefore,
the policy has been swinging between the two. The later regulations have
been improved by eliminating the problems encountered in the earlier
stages. The CSRC has pledged to improve fairness and transparency of
the IPO review process. In order to increase transparency, the CSRC has
started to reveal, on its website, the names of participating members that
213
vote on each IPO application. Presently the government is working on a
new issuance regulation. The current IPO practice in China is primary
offerings – sale of new shares. One key discussion now is secondary
market offerings (also called existing securities sale in Hong Kong).
There are two kinds of secondary offerings, or called follow-on offerings.
One is a secondary offering during IPO, where an offering is from
shareholders of the company. Another is the secondary offering after IPO,
where existing shareholders reduce their holdings. Secondary offering is
commonly used. It not only improves the financing power and capital
liquidity but also is a way for existing shareholders to transfer equity.
Secondary offering has been widely implemented in USA IPOs. Brau, Li
and Shi (2007) studied a sample of 4’219 IPO cases from 1980 to 2001.
Among them, there are 1’830 secondary offerings, 43.4% of the total.
Arik Den Dor analyzed 4’316 IPO cases from 1980 to 1997 and
concluded that combined primary and secondary offerings IPOs are 1’899
cases, 44% of all. A report shows that in 16’958 IPO cases from 1999 to
2003 in 38 countries, IPOs which are classified as primary offering
occupy 76.2%; IPOs which file only secondary offerings are 1.7%; the
rest 22.1% IPOs combine primary and secondary offerings.23
23
Source Internet, finance.ifeng.com, reported March 14, 2009,
http://finance.ifeng.com/stock/zqyw/20090314/444955.shtml
214
Third board or officially named agency share transfer system in
China, is the over the counter bulletin board. It is the service which a
transfer agent provides to holding companies to transfer their shares. The
third board in China allows delisted companies and the companies traded
in old Securities Trading Automated Quotation System (STAQS)24 and
National Electric Trading System (NETS) to trade their shares. The first
company was traded on July 16, 2001 on the third board in China. The
system reform of the third board is in process and the expansion is
planned in June 2009. The third board is defined differently in other
countries. For example, in the USA, third board refers to listed
companies’ OTC trading. In Britain, third board serves companies which
do not qualify listing requirements of either main board or Unlisted
Securities Market (USM). Third board in Britain was merged into USM
in late 1990 while USM was replaced by AIM in 1995.
Level 4, where I refer to PE/VC/M&A transactions, has grown to be
one of the most important financing channels in China. According to Van
Hedge Fund Advisors, there were only 1373 PE companies worldwide in
1988 with assets under management (AUM) of less than USD 42 billion.
24
STAQS was created by Stock Exchange Executive Council (SEEC) and started running in late 1990.
The idea was to link the stock exchange in order to build a NASDAQ-liked trading system. On July 1,
1992, State Council authorized STAQS to list and trade legal person (LP) shares. However, CSRC banned
new LP share listing in May 1993 due to the concern of diminution of public ownership. Trading in both
STAQS and NETS were stopped in September 1999 as the old Securities Law defines listed companies’
share can only be legally traded in stock exchange market.
215
Till the end of 2003, there were more than 8000 PE companies with total
AUM of more than USD 1 trillion. Statistics research of Intelligence Ltd.
Show that at the end of 2007, the AUM of PE companies had jumped to
more than USD 2 trillion. With the current credit crunch roiling the
worldwide financial markets, PE/VC/M&A firms in the USA and Europe
find increasing difficult to fund their projects. Though also affected by the
global financial crisis, PE/VC continues to grow in China. Such growth is
fueled by several factors:
a)
The improving quality and competitiveness of Chinese
companies. In a mature market, companies face the same
market environment. Their quality and competitiveness
depends on themselves, not directly the responsibility of the
authorities, except in the case of criminality. During a
transition period, capital markets have not been well regulated
and supervised and some companies’ operations do not accord
100% with the rules. This can seriously affect investors’
confidence and restrict the very development of capital markets
themselves. The past experience in China has proved that it is
not enough to rely solely on the companies themselves to
enhance their quality due to some elements such as system,
216
mechanism and environment etc; they also need the
government and related authorities’ supervision and support.
On October 19, 2005, ‘the Opinions of the CSRC on Improving
the Quality of Listed Companies’ (the Opinions) has been
approved and forwarded by the State Council. The Opinions
require local government at various levels to assume
responsibility for handling risks of listed companies and may
keep custody of those which are in crisis and may exert
significant influence on social stability. Furthermore, the
Opinions emphasize that the key of improving quality lies in
the board of directors, board of supervisors and the
management who should be honest and diligent and committed
to improving the company’s competitiveness and capacity to
make profits. Companies shall establish and enhance internal
control systems, improve operational transparency and further
stimulate and restrict senior management and its employees.
On the other hand, the authorities underline that they respect
and maintain the independence of listed companies.
b) The tight lending policies of Chinese banks, especially to
SMEs. SMEs enhance competition and often have a positive
217
impact on innovation and productivity. They usually are more
productive than large firms but their development is widely
constrained by lack of finance. Chart 40 illustrates the extreme
weight
of commercial
bank
lending
in
non-financial
institutions. Financing difficulty for SMEs is a worldwide issue.
Direct financing of SMEs is not easy to implement as big
enterprises have large economies of scale, stability of
employment and are better positioned for competition. Each
country normally has its own definition of SMEs, which can be
divided according to quantitative or qualitative methods.
Currently more than 80% of the countries worldwide define
SMEs based on quantitative criteria, such as number of
employees, registered capital and sale volume. In the USA,
SMEs get financing in several means, in which 45% from the
savings of owners, 13% from friends, 29% from commercial
banks and investment companies, 4% from securities financing
and only about 1% from government support25. Due to higher
operational risk and lower credit than big enterprises, the Small
Business Administration (SBA) was set up in the USA. It
25
Data from China Property Right Exchange, data ID EE-C02130010203.
218
provides guarantee for those SMEs which meet criteria and
promises to pay back not less than 90% of loan in case of
default. Secondly, the SBA may examine and authorize the
founding of a SME investment company, which can obtain
favorable lending support from the federal government. In
Europe, the funding requirements are similar to the USA26. In
Japan, companies like Japan Finance Corporation for Small
and Medium Enterprises, Shoko Chukin Bank, National Life
Finance Corporation and credit guarantee corporations provide
financial supports whereas SME consulting companies act as
interactive dialog. Learning from the experience from the
developed countries and based on its own unique situation, the
China Bank Regulatory Commission (CBRC) has urged state
owned big and medium sized banks to set up a special unit to
serve the unique needs of SMEs by the end of the second
quarter of 2009. Such department must apply six mechanisms,
namely independent accounting, independent
bad loan
accounting system, an independent constraint and motivation,
special training, quick decision-making and black list system.
26
According to ‘A Comparison of SMEs in Europe and in the USA’, the study of European Capital
Market Institute.
219
Credit system needs to be adapted in order to implement SME
financing. As an additional attempt, the People’s Bank of China
will legalize private lending, estimated at about RMB 2 trillion
a year, in bid to ease rural credit. Inter-company cooperation is
also needed to improve the financing situation (such as
Alibaba’s B2B which bundles SMEs’ loan application together
as a bank guarantee).
c)
Optimism of Chinese economic growth and increasing
prosperity of ultra wealthy and middle class. In the first quarter
of 2009, China saw a GDP growth of 6.1% and CPI decreased
0.6%. Despite the credit crunch, China is expected to see
growth compared with the USA or Europe. The 2009 Hurun
Wealth Report released on April 15, 2009 shows that China has
825’000 individuals with personal wealth of more than RMB
10 million. Given a comparatively more conservative
investment approach, Chinese have been less exposed to the
global financial crisis. The Hurun Report also suggests 82% of
the wealthy confirm their lifestyle has not been affected. The
RMB 4-trillion stimulus plan has begun to reinstall confidence
in the higher end of Chinese real estate. As an example, Li-Ka
220
Shing’s Cheung Kong Property Developers first phase
development at La Grande Villas close to Beijing’s
International Exhibition Center which comprises luxury houses
priced at between USD 750’000 to USD 2 million, sold out its
entire stock of housing units over 48 hours in the second
weekend of May 2009.
d) The financing capacity of PE/VC/M&A is far larger than the
stock market (see the chart below). Such development is only
sustainable under a fair and reliable legislative environment.
The amended Company Law and Securities Law in 2005 have
provided an important operational frame for China’s capital
market. The new legislation reduces government intervention
and mandatory requirements and enhances the protection of
shareholders. The QFII and QDII regulations exhibit
government’s tendency to internationalize its financial market.
The recent promulgated Guidelines on Risk Management of
Loans Extended by Commercial Banks for Mergers and
Acquisitions represent a remarkable step in development and
modernization of capital market. It marks an end to the
prohibition of acquisition finance promulgated under the
221
General Rules on Lending issued in 1996. Under the
Guidelines, domestic commercial banks can engage in M&A
activities by asset acquisition and merger, debt restructuring,
purchase of existing equity interests, subscription of new
capital and etc.
Chart 42 Capital Raised by Stock Market and PE/VC/M&A
6,000
Stock Market
PE/VC/M&A
5,000
4,000
3,000
2,000
1,000
0
2002
2003
2004
2005
2006
2007
Source: NBSC, Zero2IPO. Stock market data include A, B, H, N shares and
right issues.
e)
Stock reform and the development of a multi-level market
increase exit possibilities. The research conducted by
Zero2IPO shows the clarity of ownership structure in SOEs can
significantly increase the PE investment of domestic investors.
222
The graphs below show the exit preference and the impact of
stock reform for foreign and domestic investors. We can see
from the chart that M&A and share transfer have in total a
higher exit preference than domestic IPO listing which is
completely not the channel preferred by foreign investors. The
main reason is that main board listing in Shanghai and
Shenzhen requires long waiting periods and the listing
requirement is too high especially for growing SMEs. Stock
reform clears up the ownership structure of SOEs and enables
the trading of illiquid stakes. In addition, the current
development of the second and third board markets brings
more exit options. In 2007, 94 companies out of 242 which
were listed were supported by PE/VC. Out of these 94
companies, 33 were listed domestically, increased from 10 in
2006. The research of Zero2IPO suggests in the first quarter of
2009, there were 4 exits of PE investments, in which three of
them chose IPO. The domestic IPO listing starts to become the
mainstream of exit.
Chart 43 Exit Preference of Foreign and Domestic Investors
223
Management Acquisition
Domestic IPO
M&A
Share Transfer
IPO Abroad
0%
10%
20%
Foreign Investors
30% 40%
50%
60%
70%
Domestic Investors
Chart 44 Stock Reform’s Impact on Foreign and Domestic Investors
17.70%
2.90% 2.90%
17.70%
58.80%
Great er impact on domestic investors
Great er impact on foreign investors
Hard to say
No comments
Great er short-term impact on domestic investors but larger long-term impact on
224
Source: Zero2IPO
f)
First large scale investment by foreign and domestic PE/VC
investors. The graph below exhibits the CAGR growth of 25%.
Chart 45 10-year PE/VC Investment Scale in China, in USD million
4,500
4,000
3,500
3,000
2,500
2,000
1,500
1,000
500
0
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Source: Zero2IPO
g) Government’s supportive policies have contributed to the
growth of PE/VC despite the slowdown owing to credit crunch.
The 11th Five Year Plan (2006 to 2010) encourages the
development of clean technology27. From 2006 to 2008, the
27
Cleantech includes 9 first-grade industries, which are new energy, water/sewage treatment,
air/environmental protection, new materials, environment-friendly waste treatment, energy facilities,
energy reserves, new agriculture and building energy conservation.
225
investment in clean tech market saw an annual growth of 67%,
in which investment in new energy field accounts for 69.8%,
according to Zero2IPO. This investment pattern is similar to
those of Europe and North America. In addition to the national
plans and policies, local governments also stimulate the private
equity transactions. Chongqing, for example, promulgated
local policy which compensates rent costs and applies
favorable taxation rate for PE investors. On April 30, 2009,
China’s Ministry of Finance and the State Administration of
Taxation released new M&A tax rules which present a more
comprehensive set to address the issue of tax treatment and
illustrate ways for internal restructurings.
226
Conclusion
Although more economic research has been done in the past 25
years than ever before, the economists whose names are most frequently
referenced today, such as Adam Smith, John Maynard Keynes and
Hyman Minsky, are from earlier generations. Despite the numerous
non-government intervention theories, the history has reiterated that
people look for state’s assistance when facing crisis. As an emerging
economy, market can not regulate itself without government intervention
in China. It can be concluded that monetary, fiscal and other policies have
significant influences on China’s stock market, but neither of them could
exert their roles exclusively. Policies interact with each other and the
combination puts forward a tentative sign of green shoots.
In the past, China adopted directional policies and public
expectation was irrational. The special share structure has imposed lots of
negative influences. Government had failed in the past in promoting the
efficiency and profitability of SOEs through bank lending which led to
huge bad loans. Learning by doing policies promulgated later have made
a breakthrough. The successful transition of 736 SOEs’ ownership
structure owes to the last reform attempt authorities conduct. Shanghai
New Composite Index (also called G-share index) outperformed
Shanghai benchmark index since its launch, suggesting growing
confidence in SOEs’ clearer share structure and improving corporate
governance.
In order to develop the economy, the government adopted an
export-oriented strategy when facing limited domestic demand due to its
227
low domestic prosperity and large population base. Such policies have
successfully made China the world manufacturing house and contributed
to its economic growth remarkably. With the growing domestic wealth
and facing the global financial crisis, the government swiftly pushed out
the inland consumption stimulation package, together with insurance and
healthcare improvement plans. Despite some complaints from the
National Audit Office (NAO) regarding the regional delays of financing
the stimulus plan, NAO admits there is no serious abuse of funding due to
the increasing transparency measures taken against government official
corruption.
Since the 1970s, economists have been engaged in the research that
macroeconomics should have microeconomic foundations, meaning the
big policy issues should be grounded in the study of individual behavior.
However, there could not be a single theory of all human behavior. Herd
instinct, asset mis-pricing and grossly imperfect information have led the
history. Government’s policy is generated along with the evolution of
individual beliefs and the advance of human knowledge. Thus the
economic understanding requires an amalgam of logic and intuitions and
a wide knowledge of facts. Regulations cannot prevent financial crises
altogether but they can minimize the devastation.
Government’s guidance has created the rapid growth of China’s
stock market and the stock exchange in Shanghai generated the world's
seventh and Asia's second largest turnover in 2008. Shanghai beats
benchmarks in the world's five other biggest markets UK’s FTSE, Hong
Kong’s HSI, Japan’s Nikkei, France’s CAC and America’s S&P 500 by at
least 39% in the period since the bankruptcy of Lehman Brothers on
September 15, 2008 till the first quarter of 2009. Looking at the 20-year
development of China’s stock market, government accelerates when the
228
economy falters and steps on the brakes when it threatens to overheat
whereas policy adjustments take place incrementally. The active
responses and growing maturity of the Chinese government have proved
its success on the market overall despite some failures along the way. The
‘invisible hand’ of free markets needs to be balanced by the ‘visible hand’
of good governance.
229
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Curriculum Vitae
CONTACT INFORMATION
Name:
WANG Liya, LL.M.
Address:
Rieterstrasse 11, 8002 Zurich
E-mail:
[email protected]
EMPLOYMENT HISTORY
07/2008 – Current: Harcourt Investment Consulting AG
Product Management
07/2004 – 06/2008: HSZ Group (Zurich, Switzerland)
Marketing
01/2003 – 12/2003: Beijing Grand Prospect Trading Ltd. (Beijing,
China)
Assistant CEO, Researcher
01/2002 – 04/2002: Commercial Court, Futian District of Shenzhen
(Shenzhen, China)
Clerk, Legal Enforcement and Consulting
07/1999 – 09/1999: Intellectual Property Court, Haidian District of
Beijing (Beijing, China)
Clerk, Legal Enforcement and Consulting
EDUCATION
242
10/2003 – 06/2009: University of St. Gallen (St. Gallen, Switzerland)
Candidate of Ph.D. in Economics and Management
Asia Research Center
Ex-Vice President of Chinesischer Studentenverein
HSG (Student Union)
10/2002 – 08/2003: Utrecht University (Utrecht, the Netherlands)
LL.M. in Law and Economics, DELTA Scholarship
Thesis: The Consequence of Network Economy for
Competition and Competition Policy
09/1998 – 07/2002: Changchun University of Science and Technology
(Changchun, China)
LL.B. in Economic Law with High Honor,
First-class Scholarships
Thesis: E-Business and Law
“Outstanding Graduate in Jilin Province” Award;
“Outstanding Leadership” Award and etc.
Second Prize in the “National College Student
English Contest”
LANGUAGE SKILLS
Chinese: Native
243
English: Fluent
German: Good
CERTIFICATES
Microsoft Certificates: MCP, MCP+I, MCSE, MCDBA
IELTS; TEM 8 (Test of English Major Band 8); Band 6 English Test
244