transaction costs, liquidity and expected returns at the berlin stock exchange, 1892-1913
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Transaction costs, liquidity and expected returns at the Berlin Stock Exchange, 1892-1913
Carsten Burhop, Universität zu Köln Sergey Gelman, ICEF, Higher School of
Economics, Moscow
1st ILFE Workshop,
Moscow, September 18, 2010
2
Motivation
Explore effective transaction cost determinants & effects in a ‘friendly environment’: on an early call auction stock market over a long time span
3
Outline
1. Literature review
2. Historical background
3. Data & Methodology
4. Results
5. Conclusion
4
1. Literature Review I: liquidity & asset pricing
• Amihud (2002, JFM)– Positive risk premium for expected illiquidity– Inverse relation of returns and unexpected illiquidity shocks
• Eleswarapu/Reinganum (1993), Brennan and Subrahmanyam (1996) – Negative/insignificant risk premia
• Bekaert et al. (2007, RFS) – Dynamic interdependence of liquidity and returns on the market
level (whereby liquidity only weakly dependent);– Transaction cost adjustment + liquidity risk premium
• Goyenko et al. (2009, JFE)– Effective transaction cost measures capture liquidity (incl. price
impact)
5
1. Literature Review I: economic history
• Rajan & Zingales (2003): German pre-1913 stock market development higher than US
• Baltzer (2006): price differentials across stock exchanges negligible
• Gelman & Burhop (2008)– weak information efficiency on a rather high level– Efficiency worsens during crises 1901, 1913
• Gehrig & Fohlin (2006) – estimate effective transaction costs for Berlin stock
exchange in 1880, 1890, 1900, 1910. Find gradual decline.
– find inverse relationship to size
6
1. Contribution
• Transaction costs were on average low, but rather variable in time and cross-section
• Transaction costs are inversely influenced by size and previous year returns; are higher in crises
• There is a significant positive liquidity premium, which is more pronounced than market risk and size premia
7
2. Historical background I
• Berlin Stock Exchange (BSE) was the major German stock exchange since 1870-s
• Steadily increasing # of traded companies, around 1000 in 1913
• Trading 6 days per week, one price per day
• Call-auction mechanism with a specialist • Presence of informed insiders possible
8
Berlin Stock market performance
0
50
100
150
200
250
300
350
400
450
500
31
.12
.18
91
05
.05
.18
94
14
.09
.18
96
31
.01
.18
99
15
.06
.19
01
24
.10
.19
03
08
.03
.19
06
23
.07
.19
08
30
.11
.19
10
18
.04
.19
13
Daily Index Eube's market index Ronge's DAX-30
Leipziger Bank defaults
Balkan warBank run in US
9
German aggregate stock trading volume (in bln mark)
20
40
60
80
100
18
92
18
94
18
96
18
98
19
00
19
02
19
04
19
06
19
08
19
10
19
12
10
2. Historical background II
• Major crises with impact on efficiency:– Bankruptcy of Leipziger Bank 1901 – Balkan war fear 1913
• Fixed relative transaction costs:– Transaction tax: 0.01% up to 04/1894; 0.02% to
10/1900 and 0.03% until the end of the sample– Broker fee: official 0.05%; private 0.025%– Provisions for intermediaries: 0.1-0.33%– Total round-trip transaction cost: 0.252-0.82%– Tick size 0.05 Mark (by stock prices of 40 Mark and
above) less than 0.125%
11
3. Data• Daily stock prices for 27 stocks (hand-collected
from Berliner Börsenzeitung) 1892-1913, 6692 observations per company– Industries: banking, machinery, chemicals, mining,
textile, etc.– Requirement: listed during the whole period, <30%
zero returns• Trading volume is available only on annual basis
aggregated for all German exchanges! • Daily stock index values (from Gelman/Burhop 2008)• Annual values for market capitalization
– Heterogeneous: from 0.3 bln RM to 32.8 bln RM• Dividend amounts and dates
12
Descriptive statistics (selection)
Name Mean (ann.) Max. Min.
Std. Dev.
Skew-ness
Kur-tosis
zeros (1) Average MCap.
(mill M)
1 AG für Anilinfabrikation 0.0678 0.1257 -0.2270 0.0082 -3.85 126.25 0.1638 0.0008 2727
2 Allgemeine Elektricitätsgesellschaft 0.0336 0.0526 -0.0611 0.0065 -0.18 11.94 0.0807 0.0820 14997
5 Deutsche Bank 0.0294 0.0333 -0.0544 0.0042 -1.64 24.72 0.1001 -0.0119 32778 9 Deutsche Spiegelglas 0.0687 0.0921 -0.0838 0.0080 -0.30 18.32 0.1877 0.0716 643
10 Erdmannsdorfer Spinnerei 0.0001 0.1143 -0.0774 0.0106 0.62 13.70 0.2497 -0.0425 286
22 Schering 0.0162 0.0652 -0.0657 0.0083 0.17 10.17 0.1630 0.0610 1298 23 Schlesische Zinkhütten 0.0336 0.1079 -0.0853 0.0066 -0.52 33.99 0.2360 -0.0582 7947 26 Siemens Glas-Industrie 0.0287 0.0438 -0.0576 0.0058 -1.12 19.17 0.1966 -0.0273 2290
Value-weighted index 0.0687 0.0296 -0.0562 0.0032 -1.68 30.78 n/a 0.165 161344
13
3. Methodology I
• Measure of full transaction costs (fixed costs + price impact):– LOT (1999): information-based measure
* l * li,t i,t i i,t i
l * hi,t i i,t i
* h * hi,t i,t i i,t i
*i,t i m,t i,t
r r if r
r 0 if < r
r r if r
r r e
14
3. Methodology I
• Estimate with MLE
1 0
2
1, , , ,
1
S.T. 0, 0, 0, 0,
l h ll h it i i mt i i mt i i mti i i i it mt
i i i i
hit i i mt
i i
l hi i i i
r r r rL r r
r r
15
3. Methodology I
• Criticism of LOT measure– Zero returns may be due to noise trading– The measure is driven by the market return
volatility– Does not incorporate other factors than market
• Justification– Is the only available measure of the full
transaction costs and not only spreads– Widely used in recent financial literature, e.g.
Griffin et al. (2010, RFS); Lesmond (2005, JFE)
16
3. Methodology II: Determinants
• Cross-section and Panel estimation
• Dependent variable: annual effective TC (LOT measure) of a company
• Regressors:– Market cap (for size)– Previous year returns– Aggregate trading volume or Time dummies
17
3. Methodology III: impact on asset pricing
• Fama-MacBeth(1973) regression – monthly returns– factor loadings & firm characteristics
• Factor: market risk (our index as proxy)• Characteristics:
– Size– Daily return autocorrelation (momentum)– LOT transaction cost measure (for
illiquidity)
18
4. Results: annual transaction costsTABLE 2: ANNUAL AVERAGE OF TRANSACTION COSTS
Year LOT
1892 1.454
1893 1.584
1894 1.072
1895 0.925
1896 0.805
1897 0.814
1898 0.908
1899 0.878
1900 1.029
1901 1.678
1902 0.977
1903 0.848
1904 0.825
1905 0.696
1906 0.658
1907 0.775
1908 0.846
1909 0.731
1910 1.039
1911 0.713
1912 0.883
1913 1.124
Average 0.966
Own calculations based on daily returns for 27 stocks for the period 1892-1913.
Expressed in percent of share price, equally weighted averages. Two outliers were dropped.
19
4. Results: annual transaction costs
LOT
0
0.5
1
1.5
2
1892 1895 1898 1901 1904 1907 1910 1913
20
4. Transaction costs BSE 1892-1913: rolling window
-0.5
0
0.5
1
1.5
2
29.1
2.18
92
21.1
2.18
94
23.1
2.18
96
02.0
1.18
99
03.0
1.19
01
06.0
1.19
03
05.0
1.19
05
10.0
1.19
07
13.0
1.19
09
12.0
1.19
11
15.0
1.19
13
rollgknlot
21
4. Results: time series of transaction costs
• Transaction costs are low: average LOT-measure of 0.97%, – lower than for the upper decile of NYSE
(1.23%) in 1963-1990 (Lesmond et al. 1999)– better than any of the emerging stock markets
in 1990-s (Lesmond 2005)– But a bit above than DJIA costs of 0.6% 1970-
1980 (Goyenko et al. 2009)
• High variation: from 0.66% (1906) to 1.68% (1901)
22
Appendix 1: Average transaction costs of corporations, included in the investigation
Number Name Average
LOT measure
1 AG für Anilinfabrikation 0.943
2 Allgemeine Elektricitätsgesellschaft 0.520
3 Berlin-Anhaltinische Maschinenbau 0.902
4 Bochumer Bergwerk (Lit C) 3.164
5 Bank für Handel und Industrie 0.543
6 Deutsche Bank 0.384
7 Dresdner Bank 0.446
8 Deutsche Jute Spinnerei und Weberei 1.109
9 Deutsche Spiegelglas 1.097
10 Erdmannsdorfer Spinnerei 1.689
11 Gelsenkirchener Bergwerksgesellschaft 0.427
12 Gerresheimer Glashütten 1.284
13 Hallesche Maschinenfabriken 1.112
14 Harpener Bergbau AG 0.425
15 Kattowitzer AG für Bergbau und Eisen 0.667
16 Maschinenfabrik Kappel 1.239
17 Norddeutsche Wollkämmerei 1.135
18 Oberschlesische Portland-Cement AG 1.094
19 Rheinische Stahlwerke 0.781
20 Rositzer Zuckerfabrik 1.053
21 Schaaffhausen'scher Bankverein 0.572 22 Chemische Fabrik vormals Schering 1.001
23 Schlesische Zinkhütten 0.959
24 Schlesische Leinen-Industrie 1.183
25 Schultheiss Brauerei 0.684
26 Siemens Glas-Industrie 0.776
27 Stettiner Chamottewaren 0.905
23
4. Determinants of transaction costs: Cross-sectional results
Average LOT measure
0
2
4
5 7.5 10
1892
0.62 0.03
2 2
ˆ4.92 0.19 ln ,
ˆ0.64, 0,0.20
LOTi i i
i
S MC e
R e
ln(MCap)
24
4. Determinants of transaction costs: panel (1) FE (2) FE (3) FE (4) FE (5) RE (6) GMM
Constant 1.00***
(0.06)
0.96***
(0.05)
0.94***
(0.07)
1.79***
(0.19)
1.85***
(0.20)
Sit-1 0.44***
(0.01)
MCit/ MCit -3.12**
(1.57)
-2.59**
(1.19)
-2.59
(1.91)
-2.58
(1.59)
-4.29***
(0.73)
-0.28
(1.50)
lnPit-1 -0.25
(0.16)
-0.34**
(0.16)
-0.45***
(0.16)
-0.44***
(0.16)
-0.11***
(0.04)
lnTVt -0.20***
(0.05)
-0.20***
(0.05)
-0.22***
(0.01)
t1901 0.26***
(0.08)
t1913 0.25***
(0.07)
Time
effects
Y Y N N N N
R2 0.56 0.60 0.48 0.46 0.27
25
4. Determinants of transaction costs: panel (1) FE (2) FE (3) FE (4) FE (5) RE (6) GMM
Constant 1.00***
(0.06)
0.96***
(0.05)
0.94***
(0.07)
1.79***
(0.19)
1.85***
(0.20)
Sit-1 0.44***
(0.01)
MCit/ MCit -3.12**
(1.57)
-2.59**
(1.19)
-2.59
(1.91)
-2.58
(1.59)
-4.29***
(0.73)
-0.28
(1.50)
lnPit-1 -0.25
(0.16)
-0.34**
(0.16)
-0.45***
(0.16)
-0.44***
(0.16)
-0.11***
(0.04)
lnTVt -0.20***
(0.05)
-0.20***
(0.05)
-0.22***
(0.01)
t1901 0.26***
(0.08)
t1913 0.25***
(0.07)
Time
effects
Y Y N N N N
R2 0.56 0.60 0.48 0.46 0.27
26
4. Determinants of transaction costs: results
• Inverse relation with size – explains about 2/3 of transaction cost variation in
cross-section and 23% in a panel set-up– One std increase in share of m. cap. (0.05) leads to
0.125-0.2 decrease in transaction costs– significance vanishes in FE set-up if we include past
returns
• Inverse relationship with previous year returns explains about 10%– One std decrease in past returns (0.126) leads to
apprx 0.05 increase in LOT
27
4. Determinants of transaction costs: results
• Transaction costs are about 0.25 percentage points higher in crises years
• Transaction costs are inversely related to trade volume– One std increase in log trading volume (0.25)
induces 0.05 decrease in transaction costs
28
4. Effects of transaction costs on asset pricing
(1) (2) (3) (4)
Constant .0018
(.0014)
-.0024
(.0021)
.0024
(.0107)
.0034
(.0108)
Market beta -.0003
(.0019)
.0016
(.0020)
.0013
(.0021)
-.0001
(.0022)
Transaction cost
lagged TC
.3266**
(.1324)
.3068*
(.1773)
.3055*
(.1771)
Size S -.0002
(.0004)
-.0002
(.0004)
Momentum M .0105*
(.0058)
Average R2 0.07 0.12 0.16 0.20
# of cross-sections T 264 252 252 252
29
4. Asset pricing results
• We find support of Amihud (2002):– Lagged transaction costs increase expected
return– Contemporaneous TC – decrease returns
• CAPM doesn’t work• Size effect is absorbed by ex-ante
transaction cost measure• Momentum is positive with tendency to
significance
30
4. Asset pricing results
• Different specifications of liquidity risk do not yield significant results
31
5. Conclusion
• Transaction costs of the Berlin Stock Exchange were on average rather low as early as 1892-1913
• Size and past returns were negatively and crises were positively related to transaction costs
• Illiquidity was the primary concern of investors by asset pricing, levied a positive premium
32
Thank you for your attention
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