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Efficiency gains from the integration of exchanges: Lessons from Euronext’s “natural experiment”. Dr. A. Jorge Padilla LECG Europe www.lecgcp.com. Leuven, 7 November 2006. The theory. The integration of exchanges produces a number of significant efficiency gains: Cost savings - PowerPoint PPT Presentation
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Efficiency gains from the integration of exchanges:Lessons from Euronext’s “natural experiment”
Dr. A. Jorge Padilla
LECG Europewww.lecgcp.com
Leuven, 7 November 2006
2
The theory
The integration of exchanges produces a number of significant efficiency gains:
Cost savings– Eliminates the duplication of costly infrastructure …– … which may lead to a reduction in trading fees– … and brokerage fees
Direct user benefits– Savings on operating and capital costs– Trading more diversified portfolios– Increased cross-border trading …– … leading to increases in liquidity, as reflected by lower bid-ask
spreads, greater volume and lower volatility
3
Euronext’s natural experiment
Integration between the French, Belgian, Dutch and Portuguese stock exchanges to form Euronext (September 2000 – 2003)
“Before and after” analysis on costs and user benefits …
… controlling for confounding factors (i.e., time-variant effects that have nothing to do with integration)
LisbonAmsterdamBrussels Paris
CashTrading integration
May 2001
October2001
November2003
BrusselsParis
AmsterdamBrusselsParis
Chronology of integration of cash trading business
4
Euronext’s natural experiment
This experiment makes it possible to:– Evaluate the cost savings achieved through the integration process; – Investigate the pass-through of those savings; – Identify other sources of direct user benefits, and – Test the impact of integration on liquidity and, hence, on the implicit
trading costs faced by the users of the exchange.
5
Cost savings
Significant reduction in operating costs:– Overall, the total annual costs of Euronext’s continental operations fell by
137 million euros (25%) between 2001 and 2004. – IT cost savings: Euronext’s total continental IT costs fell by 29% between 2001
and 2004. – Headcount reductions: Euronext reduced the staffing levels of its continental
operations by 24% between 2001 and 2004.
0
20
40
60
80
100
120
140
160
2001 2002 2003 2004
m€
Development CAPEXInternet IT costsOffice automation IT costsIT running costs
143127 128
103
0
20
40
60
80
100
120
140
160
2001 2002 2003 2004
m€
Development CAPEXInternet IT costsOffice automation IT costsIT running costs
143127 128
103
Evolution of continental IT costs following Euronext integration
13381218
11101012
0
200
400
600
800
1000
1200
1400
1600
2001 2002 2003 2004
Euronext continental staff numbers 2001-2004
6
Trading fees
The evidence shows that the average trading fee charged in Paris fell by about 30% (in real terms) in the period from December 1999 to December 2004.
Average trading fees also fell in Brussels and Amsterdam.
– From January 2002 to December 2004, the average trading fee in Brussels fell by 30%.
– From January 2001 to December 2004, the average trading fee in Amsterdam fell approximately 45%.
11.
21.
41.
6E
uros
Source:Euronext
December 1999-December 2004
Paris
Our econometric results show that those fee reductions were to a large extent the result of the creation of Euronext
7
Direct user benefits
Improved access: – Integration has allowed Euronext members directly to access all the different
Euronext markets – The process of integration has expanded the set of securities accessible to
a Euronext member. – Investors now benefit from greater inter-broker competition.
9% 8%
20%
14% 15%
33%
24%
36%
18%
0%
5%
10%
15%
20%
25%
30%
35%
40%
Paris
Amsterdam
Brussels
2002 2003 2004 2002 2003 2004 2002 2003 2004
Share of cross-border trade undertaken by Euronext members (% of total trades of
members at each location)
8
Direct user benefits
Members have benefited also from reduced internal operating costs.
Increased liquidity– Lower bid-ask spreads;– Greater volume; – Lower volatility.
9
Panel data estimation We aim to estimate the impact of integration on liquidity. In order to do so, we have estimated a panel data model that relates liquidity measures with Euronext integration dummies. Liquidity is measured by:
- Volume: the higher the liquidity, the higher the volume.- Bid-ask spread: the higher the liquidity, the lower the spread.- Volatility: the higher the liquidity, the lower the volatility.
Therefore, we have tested whether Euronext integration had a positive impact on volumes and a negative impact on bid-ask spreads, and volatilities. In this analysis, we assumed that Euronext integration took place in the following dates:
- 21-May-2001: Brussels and Paris trading- 29-Oct-2001: Amsterdam, Brussels and Paris trading- 7-Nov-2003: Lisbon, Amsterdam, Brussels and Paris trading
10
itiititity Control nIntegratio
• Liquidity (volume, bid-ask spread and volatility) of security i in period t, or
• A dummy variable that takes the value of 1 if the security i is traded in an integrated market in period t and 0 otherwise.
• Alternatively, we define three different dummies in order to differentiate the impact of each integrated market:
1.“Integration Brussels” takes the value of 1 if if the security i is traded in the (at-least) integrated market Paris – Brussels in period t and 0 otherwise.
2.“Integration Amsterdam” takes the value of 1 if if the security i is traded in the (at-least) integrated market Paris – Brussels – Amsterdam in period t and 0 otherwise.
3.“Integration Lisbon” takes the value of 1 if if the security i is traded in the fully integrated market (Paris, Brussels, Amsterdam and Lisbon) in period t and 0 otherwise.
Methodology: specification
11
Specification (continued)
itiititity Control nIntegratio
• Monthly dummies.
• Dummies related to relevant economic events (similar to the ones used in the first stage).
• A deterministic time trend.
• Other controls (depend on data availability):
- In the volume regression: the volume of an index traded in non-integrated markets (FTSE 100 and DAX).
- In the volatility regression: the volatility of the index of the own market to net out covariance risk.
• Fixed effects to control for differences across securities.
• This control is specially important when using data at the security level. Panel data models allow to include a fixed effect per security, therefore, netting out differences across securities.
12
Direct user benefits
Lower bid-ask spreads – The bid-ask spreads of the securities included in the main Paris index fell as
a result of the creation of Euronext: approx 40%.– The analysis also shows that integration led to a reduction of the bid-ask
spreads of the securities in the main indices of Brussels (25%-30%) and Amsterdam (approx. 10%)
0.1
.2.3
CAC 40
Source:Euronext
3rd January 2000-28th February 2005
Weighted Average Spread
13
Liquidity effectsBid-ask spreads (Bloomberg)
Our main findings, using Bloomberg data, are:
– In general, Euronext integration had a negative, and statistically significant, impact on bid-ask spread.
– Our results show that Brussels, Amsterdam and Lisbon integration had a similar impact on the bid-ask spreads, as measured by Bloomberg.
SPREAD (1) (2)
Integration - 0.0010* * *[0.000]
Integration Brussels - 0.001* * *[0.000]
Integration Amsterdam - 0.000* * *[0.001]
Integration Lisbon - 0.001* * *[0.000]
Constant 0.002* * * 0.001* * *[0.000] [0.000]
Monthly dummies Yes YesEconomic events dummies Yes YesObservations 127,082 127,082R- squared 0.38 0.387Robust p values in brackets
Source: Bloomberg
* significant at 10%; * * significant at 5%; * * * significant at 1%
14
Liquidity effectsBid-ask spreads (Euronext)
Our main findings, using Euronext data, are:
– In general, Euronext integration had a negative, and statistically significant, impact on bid-ask spread.
– Our results show that Brussels, Amsterdam and Lisbon integration had a similar impact on the bid-ask spreads, as measured by Bloomberg.
WEIGHTED SPREAD (Paris market) (1) (2)
Integration - 0.054* * *[0.000]
Integration Brussels - 0.029* * *[0.000]
Integration Amsterdam - 0.007* *[0.012]
Integration Lisbon - 0.050* * *[0.000]
Constant 0.166* * * 0.170* * *[0.000] [0.000]
Monthly dummies Yes YesEconomic events dummies Yes YesObservations 1,316 1313R- squared 0.482 0.674Robust p values in brackets
Source: Euronext
* significant at 10%; * * significant at 5%; * * * significant at 1%
15
Direct user benefits
Greater volume – Trading volume in Paris, Brussels, and Amsterdam increased as a result of
the creation of Euronext. – According to our estimations, the creation of Euronext led to an increase in
the traded volume of the main securities listed on the Paris, Brussels and Amsterdam exchanges of approximately 40%.
010
020
030
0
020
4060
050
100
150
020
040
060
0
03 Ja
n 00
12 Ap
r 00
21 Jul
0029
Oct
0006
Feb 0
117
May
0125 A
ug 01
03 D
ec 01
13 Mar
0221
Jun 0
229
Sep 0
207
Jan 03
17 Apr
0326
Jul 0
303
Nov
0311
Feb 0
421
May
0429 A
ug 04
07 D
ec 04
03 Ja
n 00
12 Apr
0021 J
ul 00
29 O
ct 00
06 Fe
b 01
17 M
ay 01
25 Aug
0103 D
ec 01
13 M
ar 02
21 Ju
n 02
29 Sep 0
207 J
an 03
17 Apr
0326
Jul 0
303
Nov
0 311
Feb 04
21 May
0429
Aug
0407
Dec
04
Amsterdam Brussels
Lisbon Paris
Source:Bloomberg
3rd January 2000-31st December 2004
Volume (Millions of shares traded)
16
Liquidity effectsVolume
Ln VOLUME (1) (2) (3) (4) (5) (6)
Integration 0.227* * * 0.144* * * 0.120* * *[0.000] [0.000] [0.000]
Integration Brussels 0.301* * * 0.269* * * 0.240* * *[0.000] [0.000] [0.000]
Integration Amsterdam 0.249* * * 0.233* * * 0.244* * *[0.000] [0.000] [0.000]
Integration Lisbon 0.216* * * 0.340* * * 0.408* * *[0.000] [0.000] [0.000]
Volume FTSE100 0.511* * * 0.542* * *[0.000] [0.000]
Volume DAX 0.402* * * 0.465* * *[0.000] [0.000]
Trend 0.000* * * - 0.000* * * - 0.000* * * - 0.000* * * - 0.001* * * - 0.001* * *[0.000] [0.000] [0.000] [0.000] [0.000] [0.000]
Constant 15.531* * * 4.976* * * 8.472* * * 15.672* * * 4.503* * * 7.524* * *[0.000] [0.000] [0.000] [0.000] [0.000] [0.000]
Monthly dummies Yes Yes Yes Yes Yes YesEconomic events dummies Yes Yes Yes Yes Yes YesObservations 127,286 125,422 126,431 127,286 125,422 126,431R- squared 0.848 0.857 0.857 0.85 0.86 0.861Robust p values in brackets* significant at 10%; * * significant at 5%; * * * significant at 1%Source: Bloomberg
17
Liquidity effectsVolume Our main findings are:
– Euronext integration had a positive, and statistically significant, impact on volume (defined as number of shares traded).
– These results are robust to different specifications of the panel data model, in particular when including the volume of an index traded in non-integrated markets (FTSE 100 and DAX) as control variables.
– Results are also robust when defining volume in levels, except that the integration of Brussels is no longer statistically significant.
18
Direct user benefits
Lower volatility – The volatility of the large-cap securities traded in Paris, Brussels, Amsterdam
and Lisbon fell as a result of the creation of Euronext. – The reduction in volatility following integration was between 9% and 18% of
the initial levels
0.1
.2.3
.4
0.2
.4
0.1
.2.3
0.2
.4
Amsterdam Brussels
Lisbon Paris
Source:Bloomberg
3rd January 2000-31st December 2004
Historical 20 days Volatility
19
Liquidity effectsVolatility
VOLATILITY 20 days (1) (2) (3) (4)Own Integration 0.072* * * - 0.004* * *
[0.000] [0.001]Integration Brussels 0.002 0.002
[0.272] [0.222]Integration Amsterdam 0.032* * * - 0.017* * *
[0.000] [0.000]Integration Lisbon - 0.083* * * - 0.019* * *
[0.000] [0.000]Volatility 20 days INDEX 1.002* * * 0.987* * *
[0.000] [0.000]Trend - 0.000* * * - 0.000* * * - 0.000* * * - 0.000* * *
[0.000] [0.000] [0.000] [0.000]Constant 0.237* * * 0.105* * * 0.219* * * 0.106* * *
[0.000] [0.000] [0.000] [0.000]Monthly dummies Yes Yes Yes YesEconomic events dummies Yes Yes Yes YesObservations 111,793 111,793 111,793 111,793R- squared 0.314 0.442 0.33 0.443Robust p values in brackets* significant at 10%; * * significant at 5%; * * * significant at 1%Source: Bloomberg
20
Liquidity effectsVolatility Our main findings are:
– In general, Euronext integration had a negative, and statistically significant, impact on volatility (defined as 20-days volatility) when including the volatility of the index of the own market as a control variable.
– Our results show that Amsterdam and Lisbon integration had the highest (negative) impact on volatility, while Brussels integration had no statistically significant impact on volatility.
21
Conclusions
The results of the natural experiment show:– Significant cost savings were achieved as a result of the integration
process; – Those savings were passed on in part to users; – Users also enjoyed other benefits: access to more securities, increased
brokerage competition, lower transaction costs and, perhaps, most importantly increased liquidity.
– The integration of the Amsterdam, Brussels, Lisbon and Paris exchanges in a single platform resulted in a significant increase in liquidity.
Jorge Padilla LECG Jpadilla@lecg.comwww.lecgcp.com
Leuven, 7 November 2006
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