1. Are there gains from stock exchange integration? The Euronext evidence Jorge Padilla Marco Pagano 29 June 2006

2. 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. 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) Lisbon Amsterdam Brussels Paris Cash Trading integration May 2001 October 2001 November 2003 Brussels Paris Amsterdam Brussels Paris Chronology of integration of cash trading business

4. 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. 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. 6 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. 7 Specification (continued) 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. 8 User benefits: liquidity effects Volume – descriptive analysis 75.7%132.4% 176.8% 105.3% Growth in volume (number of shares traded), Euronext, 2000-2004

9. 9 User benefits: liquidity effects Volume

10. 10 User benefits: liquidity effects Volume  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. 11 User benefits: liquidity effects Volatility – descriptive analysis Evolution of volatility, Euronext indices, 2000-2004 -22.5%-43.1% -42.8% -50.5%

12. 12 User benefits: liquidity effects Volatility

13. 13 User benefits: liquidity effects Volatility  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. 14 User benefits: liquidity effects Bid-ask spreads – descriptive analysis Evolution of weighted average Bid-Ask spread, Euronext, 2000-2004 -26.8%-42% -51.3% -3.1%

15. 15 User benefits: liquidity effects Bid-ask spreads (Bloomberg)

16. 16 User benefits: liquidity effects Bid-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. 17 User benefits: liquidity effects Bid-ask spreads (Euronext)

18. 18 User benefits: liquidity effects Bid-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. 19 Paris Amsterdam 200220032004200220032004 200220032004 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. 20 Share of cross-border trade undertaken by Euronext members: % of total trades of members at each location Paris Amsterdam Brussels 200220032004200220032004 200220032004 Source: Euronext

21. 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.