Download Macroeconomic Effects

Macroeconomic Effects
Petr Strejc
Petra Burdejová
Statistics of Financial Markets I
School of Business and Economics
Humboldt–Universität zu Berlin
http://www.wiwi.hu-berlin.de
Goal
Goal:
Investigate macroeconomic effects on different stock markets
(like Asia, West Europe, East Europe, Latin America, US).
We decided for:
S&P 500 index for America
PX index for Czech Republic
Hang Seng for Hong Kong
And use two approaches:
Investigating correlation
Regression
Macroeconomic Effects
1-1
S&P 500 for America
2-1
S&P 500 for America
å most commonly used benchmark for U.S. market
represents cca. 70%
å published since 1957
å contains 500 common stocks
(chosen by commitee, not the largest)
å market-value weighted (stocks with higher market cap have
greater effect)
å since 2005 is float weighted (only number of shares available
for public trading is used in calculation )
Macroeconomic Effects
S&P 500 for America
Data:
taken quarterly 1973 Q1 - 2010 Q3
USS&P
USGDP
USFX
USM1
USM2
USCPI
USOIL
USun
index S&P 500
The Gross Domestic Product for USA
The nominal effective exchange rate of US dollar
Money supply M1 for USA
Money supply M2 for USA
Consumer price index for USA
Price of oil USD/barrel
Unemployment rate
Macroeconomic Effects
2-2
S&P 500 for America
2-3
Data:
S&P 5OO
US GDP
1500
12 000
1000
10 000
500
8000
20
20
40
60
80
100
120
40
60
1500
150
1000
100
500
40
60
Macroeconomic Effects
80
100
120
140
100
120
140
US M1
200
20
80
140
US CPI
100
120
140
20
40
60
80
S&P 500 for America
2-4
Data:
US M2
USDother currencies
8000
120
6000
110
4000
100
2000
20
20
40
60
80
100
120
40
60
80
100
120
140
120
140
140
oil price
US unemployment
10
60
9
8
40
7
6
20
5
20
40
60
Macroeconomic Effects
80
100
120
140
20
40
60
80
100
S&P 500 for America
2-5
S&P500 and other:
US GDP
US CPI
USDother currencies
1500
1500
1500
1000
1000
1000
500
500
500
8000
10 000
12 000
100
150
100
200
110
120
Their correlation depending on shift:
0.8
0.8
0.04
0.02
0.6
0.6
-20
0.4
0.4
-10
10
-0.02
0.2
0.2
-0.04
-20
-10
10
Macroeconomic Effects
20
-20
-10
10
20
-0.06
20
S&P 500 for America
2-6
S&P500 and other:
US M1
US M2
1500
1500
1000
1000
500
500
500
1000
1500
2000
4000
6000
8000
Their correlation depending on shift:
-20
-10
Macroeconomic Effects
0.8
0.8
0.6
0.6
0.4
0.4
0.2
0.2
10
20
-20
-10
10
20
S&P 500 for America
2-7
S&P500 and other:
US unemployment
oil price
1500
1500
1000
1000
500
500
5
6
7
8
9
10
10
20
30
40
50
60
70
Their correlation depending on shift:
-20
-10
10
0.6
20
-0.1
0.5
-0.2
0.4
-0.3
0.3
-0.4
0.2
-0.5
0.1
-0.6
-20
Macroeconomic Effects
-10
10
20
S&P 500 for America
2-8
Fisher’s z-transformation
ρ - true correlation coefficient
r - sample correlation coefficient
n - sample size
Assumptions:
- normality
- ρ is not close to 1 or -1
- n ≥ 10(asymptotic test)
√
1+r
n−3
log
2
1−r
ρ = 0 ⇒ T ∼ N(0, 1)
T =
Macroeconomic Effects
S&P 500 for America
2-9
Differences in % for S&P500 and other:
US CPI
US GDP
-0.02
USDother currencies
0.2
0.2
0.2
0.1
0.1
0.1
-0.01
0.01
0.02
0.03
0.04
-0.01
0.01
0.02
-0.05
0.03
0.05
-0.1
-0.1
-0.1
-0.2
-0.2
-0.2
0.10
Their correlation depending on shift:
0.3
0.15
0.1
0.10
0.2
0.05
-20
0.1
-10
10
-0.1
20
-20
-10
10
-0.05
-20
-10
10
-0.1
20
-0.2
-0.10
-0.15
Macroeconomic Effects
20
S&P 500 for America
2-10
Differences in % for S&P500 and other:
US M1
US M2
0.2
0.2
0.1
0.1
-0.02
0.02
0.04
0.06
0.01
-0.1
-0.1
-0.2
-0.2
0.02
0.03
0.04
Their correlation depending on shift:
0.20
0.15
0.15
0.10
0.10
0.05
0.05
-20
-20
-10
10
-0.05
Macroeconomic Effects
-10
10
20
-0.05
-0.10
-0.10
-0.15
-0.15
20
S&P 500 for America
2-11
Differences in % for S&P500 and other:
US unemployment
oil price
0.2
0.2
0.1
0.1
-0.05
0.05
0.10
-0.4
0.15
-0.2
0.2
-0.1
-0.1
-0.2
-0.2
0.4
Their correlation depending on shift:
0.2
0.1
0.1
-20
-10
10
20
-20
-10
10
-0.1
-0.1
-0.2
-0.3
Macroeconomic Effects
-0.2
20
Hang Seng
3-1
Hang Seng index
å published since 1969
å contains 45 common stocks
(represents cca 60-70%)
å market-value weighted
å float weighted
å 12.Nov.’10 speculations that China is preparing to raise
interest rates to curb inflation ⇒ the biggest dropp in last 4
months
Macroeconomic Effects
Hang Seng
Data:
taken quarterly 1991 Q1 - 2010 Q3
HKindex index S&P 500
HKGDP The Gross Domestic Product for Hong Kong
HKFX The nominal effective exchange rate of Hong Kong
dollar
HKCPI Consumer price index for Hong Kong
HKun Unemployment rate
Due to lack of data we didn’t use money supply.
Macroeconomic Effects
3-2
Hang Seng
3-3
Data:
Hang Seng Index
HK CPI
HK GDP
30 000
400 000
110
25 000
350 000
20 000
100
15 000
300 000
90
10 000
250 000
80
5000
20
40
60
80
20
40
60
20
80
40
HK unemployment
HKDother currencies
8
105
6
100
4
95
90
2
20
40
60
80
20
Macroeconomic Effects
40
60
80
60
80
Hang Seng
3-4
Differences in % for HSI and other:
HK GDP
HK CPI
0.4
0.4
0.2
0.2
-0.02
0.02
0.04
0.06
-0.03
-0.02
-0.01
0.01
-0.2
-0.2
-0.4
-0.4
0.02
0.03
0.04
Their correlation depending on shift:
0.4
0.3
0.2
0.2
0.1
0.1
-20
-10
10
-0.1
20
-20
-10
10
-0.1
-0.2
-0.3
Macroeconomic Effects
-0.2
20
Hang Seng
3-5
Differences in % for HSI and other:
HK unemployment
HKDother currencies
-0.04
0.4
0.4
0.2
0.2
-0.02
0.02
0.04
-0.2
0.06
-0.1
0.1
-0.2
-0.2
-0.4
-0.4
0.2
0.3
0.4
Their correlation depending on shift:
0.3
0.2
0.2
0.1
0.1
-20
-20
-10
10
20
-10
10
-0.1
-0.1
-0.2
-0.2
-0.3
-0.3
Macroeconomic Effects
20
PX index
PX index
å official index of Prague stock exchange
å market-value weighted
å published since 1994 (successor of PX 50)
å in 1998 historical bottom (consequence of fin.crisis)
å next big fall in Sep.2001
å in 2004 Czech.Rep. accessed EU, contiuous rising
å in 2006 fell again (due to elections)
Macroeconomic Effects
4-1
PX index
4-2
Data:
taken quarterly 1997 Q1 - 2010 Q3
CZPX PX index
CZGDP The Gross Domestic Product for Czech.Rep.
CZFX The nominal effective exchange rate of Czech koruna
USCPI Consumer price index for Czech. Rep.
USun Unemployment rate
Due to lack of data we didn’t use money supply.
Macroeconomic Effects
PX index
4-3
Data:
PX
CZ CPI
CZ GDP
900 000
110
1500
800 000
100
700 000
1000
90
600 000
10
20
30
40
10
50
20
30
40
10
50
20
CZ unemployment
CZKother currencies
11
120
10
110
9
8
100
7
90
6
80
5
10
Macroeconomic Effects
20
30
40
50
10
20
30
40
50
30
40
50
PX index
4-4
Differences in % for PX and other:
CZ GDP
CZ CPI
0.3
0.3
0.2
0.2
0.1
-0.01
0.1
0.01
0.02
0.03
0.04
-0.01
0.01
-0.1
-0.1
-0.2
-0.2
-0.3
-0.3
0.02
0.03
0.04
Their correlation depending on shift:
0.4
0.2
0.1
0.2
-20
-20
-10
10
20
-10
10
-0.1
-0.2
-0.2
-0.3
Macroeconomic Effects
20
PX index
4-5
Differences in % for PX and other:
CZ unemployment
CZKother currencies
0.3
0.3
0.2
0.2
0.1
0.1
-0.05
-0.1
0.05
0.1
-0.1
-0.1
-0.2
-0.2
-0.3
-0.3
0.2
0.3
Their correlation depending on shift:
0.3
0.2
0.2
0.1
0.1
-20
-20
-10
10
-0.1
-10
10
20
-0.1
-0.2
-0.2
-0.3
Macroeconomic Effects
20
PX index - Regression
PX index - Regression
We tried linear regression model.
1st step Using differences
⇒ a lot of complication, no convenient results
2nd step Original dataset
Check all assumptions for linear models!
Macroeconomic Effects
5-1
PX index - Regression
Basic model
PXt = β0 + β1 GDPt + β2 CPIt + β3 UNEMt + β4 FXt + t
We get final model:
PXt = 0.003925GDPt − 19.71924CPIt + t
t = 1.2243t−1 − 0.3526t−2 + ut
R-squared 0.958600
Durbin-Watson stat: 2.056786
Jarque-Bera for residuals: p-value 0.5647
Breusch-Godfrey Serial Correlation LM Test: p-value 0.17
White test: p-value 0.047
Macroeconomic Effects
5-2
PX index - Regression
5-3
Model with shifted values
PXt
= β0 + β1 GDPt + β2 CPIt + β3 UNEMt + β4 FXt + β5 GDPt−1
+β6 CPIt−1 + β7 UNEMt−1 + β8 FXt−1 + β9 PXt−1 + t
We get final model:
PXt
= 1812.448 + 0.003945GDPt + 12.37455FXt + 0.6455PXt−1 +
−45.877CPIt−1 + 44.4UNEMt−1 − 14.076FXt−1 + t−1
R-squared 0.977177
Durbin-Watson stat: 1.909336
Jarque-Bera for residuals: p-value 0.3146
Breusch-Godfrey Serial Correlation LM Test: p-value 0.787
White test: p-value 0.764
Macroeconomic Effects
Hang Seng index - Regression
HSI index - Regression
Again tried linear regression model.
1st step Using differences
⇒ no convenient results
2nd step Original dataset
+ variable time
Check all assumptions for linear models!
We had to solve problem with non-normaliy of residuals.
Macroeconomic Effects
6-1
Hang Seng index - Regression
6-2
Basic model
HSIt = β0 + β1 GDPt + β2 CPIt + β3 UNEMt + β4 FXt + t
log HSIt = β0 +β1 log GDPt +β2 CPIt +β3 UNEMt +β4 FXt +β5 t +t
Jargue-Bera:0.71 but autocorrelation
We get final model:
log HSIt = −37.065 + 3.649 log GDPt + 0.0144CPIt − 0.0209t + t
t = 0.58t−1 + ut
R-squared 0.922409
Durbin-Watson stat: 2.163092
Jarque-Bera for residuals: p-value 0.2689
Breusch-Godfrey Serial Correlation LM Test: p-value 0.234
White test: p-value 0.269
Macroeconomic Effects
Hang Seng index - Regression
6-3
Model with shifted values (without time)
log HSIt
= β0 + β1 log GDPt + β2 CPIt + β3 UNEMt + β4 FXt +
+β5 log GDPt−1 + β6 CPIt−1 + β7 UNEMt−1 +
+β8 FXt−1 + β9 log HSIt−1 + t
log HSIt
= −4.7039 + 4.0345 log GDPt − 0.1164UNEMt +
+0.0096CPIt + 0.09895UNEMt−1 − 3.3354 log GDPt−1 +
+0.4675 log HSIt−1 + t
R-squared 0.931961
Durbin-Watson stat: 2.256551
Jarque-Bera for residuals: p-value 0.9237
Breusch-Godfrey Serial Correlation LM Test: p-value 0.1086
White test: p-value 0.1995
Macroeconomic Effects
Hang Seng index - Regression
6-4
Model with shifted values (with time)
log HSIt
= β0 + β1 log GDPt + β2 CPIt + β3 UNEMt + β4 FXt +
+β5 log GDPt−1 + β6 CPIt−1 + β7 UNEMt−1 +
+β8 FXt−1 + β9 t + t
log HSIt
= −60.306 + 5.5329 log GDPt + 0.0154CPIt +
+0.0765UNEMt−1 − 0.0353t
t
= 0.3938t−1 + 0.2621t−2 + ut
R-squared 0.919853
Durbin-Watson stat: 2.059433
Jarque-Bera for residuals: p-value 0.8247
Breusch-Godfrey Serial Correlation LM Test: p-value 0.2797
White test: p-value 0.7399
Macroeconomic Effects
S&P - Regression
7-1
S&P index - Regression
Again tried linear regression model.
1st step Using differences
⇒ no convenient results
2nd step Original dataset
+ variable time
Check all assumptions for linear models!
We were not able to solve a problem with non-normaliy of residuals.
Macroeconomic Effects
S&P - Regression
7-2
Basic model:
S&Pt
= β0 + β1 GDPt + β2 CPIt + β3 UNEMt + β4 FXt +
+β5 log OILt + β6 M1t + β7 M2t + β8 t + t
We get:
S&Pt
t
= −1495.851 + 0.3528GDPt + 1.5877OILt − 13.584t + t
= 0.95t−1 + ut
R-squared 0.990502
Durbin-Watson stat: 1.86992
Autocorrelation X
Normality of residuals
Homoskedasticity
#
Macroeconomic Effects
#
S&P - Regression
7-3
Other results:
Trying to solve non-normality of residuals we get:
log S&Pt
t
= −21.76 + 3.0627 log GDPt + t
= 0.9345t−1 + ut
R-squared 0.99528
Durbin-Watson stat: 1.8502
Autocorrelation X
Normality of residuals
Homoskedasticity X
#
Macroeconomic Effects
S&P - Regression
7-4
Other results:
One of models with shifted values:
S&Pt
= −59.9065 + 0.4036GDPt − 0.3943GDPt−1
+0.93S&Pt−1 + t
But a lot of problems..
R-squared 0.990069
Durbin-Watson stat: 1.872328
Autocorrelation X
Normality of residuals
Homoskedasticity
#
Macroeconomic Effects
#
Publications about this thema
8-1
Conclusions from different papers:
Sariannidis N., Giannarakis G., Litinas N., Konteos G., (2009)
GARCH: Examination of Macroec. Effects on U.S. stock market
monthly data for the period January, 2000 to January, 2008
changes in returns in crude oil prices affect negatively the U.S.
stock market (with a month delay)
changes in returns of the 10 year bond value affect it positively
(with a month delay)
exchange rate volatility affects negatively the returns of the
U.S. stock market
Macroeconomic Effects
Publications about this thema
8-2
Conclusions from different papers:
Shanken (1990)
nominal T-bill yields are negatively correlated with future stock
returns
Joseph (2002, U.K.)
exchange rate changes have less impact than interest rate
changes on stock returns
Elyasiani and Mansur (1998)
long-term interest rate has a negative impact on the bank
stock returns on the U.S. market
Kling (1985)
crude oil price increases and stock market have a negative
relationship
Macroeconomic Effects
Publications about this thema
8-3
Conclusions from different papers:
Huang et al. (1996)
oil futures returns and oil company returns are correlated
there is no significant correlation with return of stock market
such as the S&P 500
Maghyereh (2004)
investigating 22 emerging markets
oil price changes do not affect the stock returns
Jorion (1990)
relationship between stock returns and exchange rate
movements is hardly significant
Bartram (2004)
between stock returns and exchange rate movements is
non-linear
-Macroeconomic Effects
-
Sources
Data sources:
www.finance.yahoo.com > S&P index, HSI index
http://ftp.pse.cz/Info.bas/Cz/PX.csv
USA data
http://research.eco5.com > America
Hong Kong data
http://www.censtatd.gov.hk/
> hong kong statistics > statistical tables
Czech data
www.cnb.cz > ARAD statistics
www.cszo.cz
http://portal.mpsv.cz/sz/stat/nz/casoverady
Macroeconomic Effects
9-1
Sources
9-2
Other sources:
http://www.pse.cz/
http://www.fool.com/school/indices/sp500.htm
http://www.hsi.com.hk/HSI-Net/
www.wikipedia.com and www.wikipedia.cz > S&P, HSI, PX
Sariannidis N., Litinas N., Konteos G., Giannarakis G. (2009):
A GARCH Examination of Macroeconomic Effects on U.S. stock
market, unpublished.
[email protected] , [email protected]
Presentation and source codes can be found:
www.petra.traceit.org > HU Berlin > SFM I.
Macroeconomic Effects