Download Efficient Markets Lecture

MARKET EFFICIENCY
1.
The purpose of financial markets is to transfer funds
between lenders (savers) and borrowers (producers)
efficiently. “Efficiently” means funds that are supplied
yield the highest return to savers given their risk
preferences and fund the most profitable projects
given their risks, at the lowest cost.
2.
Perfect Markets
a. No frictions – no transactions costs, taxes,
indivisibilities, regulations, or unmarketable assets.
b. Perfect competition – price-takers
c. Information is costless and simultaneously available
to all
d. Individuals maximize expected utility.
3.
Market Efficiency is much less restrictive than market
perfection. An efficient market allocates capital
properly, given the costs of transactions, information
etc.
MARKET EFFICIENCY THREE FORMS
Weak form
•
past prices hold no information about future prices
•
can't beat buy/hold strategy
•
much evidence to support including correlation
tests, filter test - fail
Semi-strong form
•
all publicly available information is immediately
reflected in price.
•
subsumes weak form since price data is publicly
available
•
assumes rational investors seek information
impound quickly.
•
result - prices may rise or fall with few trades - few
chances to make money
•
quite a bit of information such as stock split and
earnings information is impounded quickly.
EXAMPLE: Yield curve misalignment in US. Treasury market takes 15 seconds to correct.
Strong Form
•
all relevant information reflected in stock prices
due to insiders, specialists
•
evidence shows announcements of important
information often anticipated beforehand.
•
implies outside investors should buy and hold
the market portfolio.
1. Rubenstein (1975) and Latham (1985) say that market
efficiency with respect to a piece of information means
that when the information is announced, prices don’t
change and no trades occur. Fama (1976) suggests
that trades can be made but prices do not change.
2. The value (expected utility) of an information structure 
(a set of messages m).
V() = m q(m)[ MAXa e p(e|m)U(a, e)] – V(0)
where q(m) = marginal probability of receiving a message m
p(e|m) = the probability of an event e, conditioned on
receiving message m.
U(a, e) = the utility of the action a, if an event e occurs
(the benefit function)
V(0) = the expected utility without the information
3. The MAX[.] part says that individuals choose among
possible actions in a way that their utility is maximized given
that message m is received.
Then, the maximized expected utility is weighted by the
probability of receiving each possible message and summed
over the messages.
Then compare this value to the expected utility without the
information to see if the information structure has value.
4. Fama (1976) formally defines an efficient capital market as
one where we have
m(P1t, … Pnt|mt-1) = (P1t, …, Pnt|t-1)
That is, the joint distribution of securities prices given the
subset m of information the market uses, is the same as the
joint distribution that would exist if all relevant information was
used.
This also implies that, net of costs, the utility value of the
gain from information structure m for individual I is zero.
V(i) = V(0)
Weak form =>  = past prices
Semi-strong form =>  = all publicly available information
Strong form =>  = all available information
MARKET EFFICIENCY PROPERTIES
•
MARKET IS NOT ALWAYS CORRECT - just unbiased
and usually close to correct
•
PRICE CHANGES ARE INDEPENDENT AND
RANDOM - prices adjust rapidly to new information
•
MUCH AVAILABLE INFORMATION
•
LIQUIDITY - PRICE CONTINUITY - Fed watches
•
LOW TRANSACTION COSTS
1.
It is difficult to prove market efficiency
•
Market variance is so large, superior investment
performance must be very large before it is
statistically significant.
•
Selection bias - those with profitable investment rules
do not reveal them, hence, we can't be sure that
some managers are profitable.
•
Luck - by chance
performance.
some
will
have
superior
QUESTION: Some stocks have very high returns and
others very low returns even after adjustment for risk.
Is this evidence of market inefficiency? No, because
some firms may do surprisingly well for some periods.
1. Efficiency implies that investors should
•
define risk level
•
hold a diversified portfolio that is a combination
of the market portfolio and risk free assets
•
minimize trading transaction costs
2.
Fully efficient markets reflect the full impact of all
information, not just some average of the information.
That is, if the true effect of the information implies a
price of 4 and some interpret the information properly
but others interpret the information to imply a price of
3, the price should still be 4. However, an averaging of
information would give a price between 3 and 4.
Nevertheless, the action of the market in aggregating
information can be illustrated by averaging.
Example: Guess the Number of Beans
3. The effect of asymmetric information on market efficiency is
often analyzed with a Trading Model. A Trading Model such
as Kyle (1985) in Econometrica includes
a. Assumptions about the existence of or proportion
of informed traders versus uninformed traders and
the costs of trades. Assumption about whether
trades are anonymous.
b. Requirements for equilibrium – zero expected net
excess profits after costs. Informed and uninformed
traders earn the same return after costs (assumes
that the informed have costs to gather information
and that they compete. If there is a single or noncompetitive group of privately-informed traders,
then they earn excess profits by trading at favorable
prices with uninformed traders. Uninformed traders’
losses equals informed traders’ gains and market
makers break even.)
c. For an interesting model, one needs to show that
both informed and uninformed traders will find it
rational to participate in the market, I.e., one does
not totally dominate the market.
STATISTICAL
PROPERTIES of STOCK
PRICES AND RETURNS IN
AN EFFICIENT MARKET
1.
A large and growing body of research shows that risk
and expected returns for stocks change over time. Many
studies explore the implications of these changing
distributions for testing market efficiency and measuring
performance.
2.
Earlier work assumed that risk and expected returns
were constant so efficiency would imply that there should
be no pattern in asset prices or returns.
3.
Theories of time series behavior of prices or returns.
A.
Fair Game – describes the error in the return
j,t+1 = rj,t+1 – E(rj,t+1 | t)
A Fair Game implies Unbiased Expectations
E[j,t+1 ] = E[ rj,t+1 – E(rj,t+1 | t)] = 0
This says that, on average, the actual return equals the
expected return.
One type of Fair Game is a Martingale which just assumes
E(rj,t+1 | t) = 0
expected return is zero
Another Fair Game is a Submartingale which assumes
E(rj,t+1 | t) > 0
expected return is positive
Stock returns are assumed to be submartingales so in order
to test for abnormal returns (return performance) for a stock or
a portfolio of stocks we need a model of
E(rj,t+1 | t)
such as the CAPM, APT or Fama-French. Using the CAPM
we have
j,t = rj,t – E(rj,t | t) = rj,t – [rf,t + (E(rm,t | mt) - rf,t )jt]
And so
E[j,t ] = E{ rj,t – [rf,t + (E(rm,t | mt) - rf,t )jt]} = 0
This says that the difference between the actual stock return
and the return predicted from the CAPM is zero on average
(Jensen’s alpha is zero). A test of market efficiency using the
submartingale is a joint test of efficiency and the CAPM (only
beta matters).
A joint test is problematic because if the data show E[j,t ] = 0,
this may be due to the fact that the CAPM is wrong and
markets are inefficient but the two offset one another. Thus,
such a result does not prove either efficiency or CAPM
individually, only in combination.
B. Random Walk is a stronger model. It assumes that the
whole distribution of returns conditional on an information
structure is no different than the unconditional distribution.
(r1,t+1, … rn,t+1) = (r1,t+1, …, rn,t+1|t)
This says that unconditional returns already fully impound all
information so conditioning on an information structure
provides no advantage.
All return observations must be independent and taken from
the same distribution because new information is always
anticipated and fully reflected in a fixed distribution.
Because recent studies show that return distributions change
over time, stock returns are not random walks.
4. One difference between a fair game and random walk:
A fair game can have correlated returns over time but a
random walk cannot.
Example: Suppose you have a series of returns on a portfolio
strategy that consists of buying stock X at the beginning of
period 1, then selling it at the end of period 1 and reinvesting
the money in stock Y at the beginning of period 2, and selling
it at the end of period 2 and reinvesting the money in stock X
at the beginning of period 3, and then selling it at the end of
period 3 and reinvesting the money in stock Y and so on. If
the mean returns of the stocks are Y = .10 and X = .15, what
type of pattern will we observe in the return series?
TECHNICAL ANALYSIS
•FUNDAMENTAL ANALYSIS – stock prices are determined
solely by the expected discounted present value of all
future cash flows based upon economy, industry, company
information.
•TECHNICAL ANALYSIS - use past price and trading
volume to predict future price.
•Efficiency argument for studying Technical Analysis Since market efficiency implies prices aggregate
all information, then for an uninformed investor,
prices may be used to infer what the market
knows.
•Technical Analysis is popular, perhaps because it is very
visual and intuitive - analysts use charts
DOW THEORY - BEST
KNOWN TECHNICAL
THEORY
•THREE TIME TRENDS
primary trend
intermediate trend
short term corrections - day to day
•TWO DIRECTIONAL TRENDS
bull trend - higher highs
bear trend - lower lows
1. Problems with Dow Theory
•Often late in identifying major trends
•Not much help for short term trader - or which stocks to buy.
Dow Jones Industrial Index
Dow Jones Transportation Index
4000
New highs made without making significant new lows
I
n
d
e
x
3000
2000
V
a
l
u
e
1000
0
82
83
84
85
86
87
88
89
90
91
Year
There is a primary bull trend from 1982 to 1994
92
93
94
Dow Jones Industrial Index
Dow Jones Transportation Index
3000
I
n
d
e
x
V
a
l
u
e
2000
1000
Index continues to make new lows without making new highs
0
90
91
Year
Within the primary bull trend there is an intermediate bear trend from mid-1989 to 1991
Dow Jones Industrial Index
Dow Jones Transportation Index
3000
I
n
d
e
x
2000
v
a
l
u
e
1000
3
5
6
7 10 11 12
13 14 17 18 19 20
21 24 25 26 27 28 31
Day in July 1989
Within the intermediate bear trend is a short-term bull trend
VOLUME ANALYSIS SUPPLY/DEMAND
•Large volume signals turning points followed by weak
volume.
• Volume goes with trend
Bull market
- prices up on high volume
-prices down on low volume
Bear market
-prices up on low volume
-prices down on high volume
BASIS FOR TECHNICAL
ANALYSIS
•
Supply-demand determine price
•
Both supply & demand are affected by rational
and irrational factors.
•
Prices move in trends - trends persist because
price adjustments to new information takes time
1. Supposed Advantages of Technical Analysis
•Aren't required to get good fundamental information and
process quickly, this is difficult.
•Just interpret price and volume movements to get
information indirectly, don’t care about what a company
does.
•No need to decipher financial statements that are biased.
2. Examples
•Short interest - signals latent demand - not supported
•Odd lot Theory - small investors trade incorrectly - not
supported
•Mutual Fund Cash Position - latent demand - actually a
concurrent indicator.
•Call / Put ratio - usually more calls - increase in puts is
bearish.
•Inside Information Indicators
- insider sell / buy ratio - since many companies
pay in shares - expect some to sell, if none sell bullish
- buy / sell differential by NYSE members
- short selling by specialists
•PRICE LEVELS
resistance levels
support levels
•PRICE FORMATIONS
hard to tell one from another
their use reflects individuals effort to see pattern
in randomness, tests show people see patterns
in random generated pictures general trends and
sideways movements
Weekly Hi-Lo Ranges for Dial Corp's Stock Price
25
D
24
i
a
l 23
S
t
o
c
k
P
r
i
c
e
near-term resistance
secondary resistance
22
21
20
near-term support
19
secondary support
18
1993
1994
1995
A technical analyst would recommend buying Dial's stock at $20 and selling it at $24
Websites for Technical
Analysis
1.
Futuresource.com – has examples of formations and
trendlines.
2. Prophetfinance.com – use Prophet JavaCharts for drawing
in trendlines – interactive.
3. Stockcharts – has MarketCarpets that give a visual
of how sectors are doing day-to-day.