Are there gains from stock exchange integration?The Euronext evidence

Jorge PadillaMarco Pagano

29 June 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

The creation of Euronext

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

Why it may yield valuable evidence

This experiment allows us to:

– Evaluate the cost savings achieved through the integration process;

– Investigate the pass-through of those savings via reduced fees;

– Identify other sources of direct user benefits, especially via the impact on liquidity and, hence, on the implicit trading costs faced by the users of the exchange.

5

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

6

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

7

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.

8

User benefits: liquidity effectsVolume – descriptive analysis

01

002

003

00

05

10

15

20

01

002

003

00

05

01

001

50

01 Jul 00 01 Jan 02 01 Jul 03 01 Jan 05 01 Jul 00 01 Jan 02 01 Jul 03 01 Jan 05

AEX BEL20

CAC40 PSI

Source: Bloomberg

Volume (Millions of shares traded)

75.7% 132.4%

176.8% 105.3%

Growth in volume (number of shares traded), Euronext, 2000-2004

9

User benefits: 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 Yes

Economic events dummies Yes Yes Yes Yes Yes Yes

Observations 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

10

User benefits: 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.

11

User benefits: liquidity effectsVolatility – descriptive analysis

Evolution of volatility, Euronext indices, 2000-2004

0.1

.2.3

.4

0.2

.4

0.2

.4

0.1

.2.3

01 Jul 00 01 Jan 02 01 Jul 03 01 Jan 05 01 Jul 00 01 Jan 02 01 Jul 03 01 Jan 05

AEX BEL20

CAC40 PSI

Source: Bloomberg

Volatility 20 days

-22.5% -43.1%

-42.8% -50.5%

12

User benefits: 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 Yes

Economic events dummies Yes Yes Yes Yes

Observations 111,793 111,793 111,793 111,793

R- squared 0.314 0.442 0.33 0.443

Robust p values in brackets* significant at 10%; * * significant at 5%; * * * significant at 1%Source: Bloomberg

13

User benefits: 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.

14

User benefits: liquidity effectsBid-ask spreads – descriptive analysis

Evolution of weighted average Bid-Ask spread, Euronext, 2000-2004

.05

.1.1

5.2

0.2

.4.6

.1.2

.3

.2.4

.6.8

01 Jan 00 01 Jan 01 01 Jan 02 01 Jan 03 01 Jan 04 01 Jan 05 01 Jan 00 01 Jan 01 01 Jan 02 01 Jan 03 01 Jan 04 01 Jan 05

AEX BEL20

CAC 40 PSI20

Source: Euronext

Weighted Average Bid-Ask Spread

-26.8% -42%

-51.3% -3.1%

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User benefits: liquidity effectsBid-ask spreads (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 Yes

Economic events dummies Yes Yes

Observations 127,082 127,082

R- squared 0.38 0.387

Robust p values in brackets

Source: Bloomberg

* significant at 10%; * * significant at 5%; * * * significant at 1%

16

User benefits: 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.

17

User benefits: liquidity effectsBid-ask spreads (Euronext)

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 Yes

Economic events dummies Yes Yes

Observations 1,316 1313

R- squared 0.482 0.674

Robust p values in brackets

Source: Euronext

* significant at 10%; * * significant at 5%; * * * significant at 1%

18

User benefits: liquidity effectsBid-ask spreads (Euronext - 2)

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.

19

3%

25%20%

5%

36%40%

7%

46%

58%

0%

10%

20%

30%

40%

50%

60%

70%

Paris

Amsterdam

2002 2003 2004 2002 2003 2004 2002 2003 2004

Share of trades achieved by non-local members: % of total trades at each location

Source: Euronext

169% 100% 280%Growth in number

of cross-border trades, 2002-2004

Brussels

20

Share of cross-border trade undertaken by Euronext members: % of total trades of members at each location

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

Source: Euronext

21

Conclusions

The evidence shows:

– 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.