Trading Behaviour, Price Discovery and Volatility in Competing Market Microstructures
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Trading Behaviour, Price Discovery and Volatility in Competing Market Microstructures Andrew Ellul London School of Economics and Political Science Submitted in partial fulfilment of the requirements of the degree of Doctor in Philosophy University of London June 2001 UMI Number: U613334 All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. Dissertation Publishing UMI U613334 Published by ProQuest LLC 2014. Copyright in the Dissertation held by the Author. Microform Edition © ProQuest LLC. All rights reserved. This work is protected against unauthorized copying under Title 17, United States Code. ProQuest LLC 789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, Ml 48106-1346 bt> I SSb L%bL H S 3 - h Trading Behaviour, Price Discovery and Volatility in Competing Market Microstructures Thesis Abstract The first chapter investigates the price and volatility impacts produced by block trades in an inter-market environment with different microstructures. A sample of European cross-traded securities is employed to investigate whether large trades executed on the foreign market (London Stock Exchange's SEAQ-I market) produce any impacts on the securities' home markets and analyse whether different market microstructures matter. The price impact in the home markets is detected before the large trade is~executed on SEAQ-I and proceeds in a protracted fashion, implying that substantial pre- and post-positioning is undertaken by London market makers through the home markets. The new equilibrium price on the home market is reached before the trade information is published on SEAQ-I. Large trades are also found to cause higher price volatility in auction trading systems than in a hybrid market microstructure. The second and third chapters analyse the formation of quoted and effective spreads and their components in three different market microstructures. The results show that quoted and effective spreads generated by a hybrid system (Deutsche Bdrse's IBIS system) are lower than those generated by both the pure auction system (Paris Bourse's CAC system) and the dealership system (London Stock Exchange SEAQ market). Traders on a hybrid mechanism face the lowest costs and this result holds even when we control for (a) the level of market concentration in liquidity provision, and (b) company-specific news. However, the adverse selection component of the spread is significantly higher in an auction trading system compared to both the dealership and the hybrid trading system. This fifth chapter investigates (a) whether, in a hybrid trading mechanism, voluntary market makers provide a higher level of price stabilisation than limit order traders even if they do not have any obligation to keep orderly markets, (b) the strategic interactions between the limit order book and market makers, and (c) the behaviour of the order flow at times of price uncertainty. We analyse these issues using high frequency data from the London Stock Exchange which has adopted a hybrid market microstructure. We find that prices on the dealership system track the security's true value more efficiently. The dealership system can transact higher volumes with lower price volatility. This evidence suggests that market makers provide price stabilisation, even if they have no binding obligation to do so, thus improving the market's quality. In terms of trading behaviour, we find that in a hybrid trading mechanism, traders are not encouraged to provide liquidity on the order book through limit orders as price uncertainty increases. Instead orders migrate to the dealership system for execution. Acknowledgments My first debt of gratitude goes to John Board, for his comments and suggestions together with his patience in listening to my research ideas and questions. Indeed, his assistance and encouragement date back to the period when I was a student reading for the MSc in Accounting and Finance. I have also learnt a huge deal from the feedback and ideas provided by Marco Pagano and David Webb, both of whom have been unsparing with their time. During the course of my PhD I have benefitted enormously from com ments made by various academics and market participants whom I have met in seminars, conferences or other academic activities. In particular, I would like to thank Utpal Bhattacharya, Geoffrey Booth, Margaret Bray, Vicente Cunat, Frank de Jong, Ian Domowitz, Larry Harris, Craig Holden, Jan P. Krahnen, Hung Neng Lai, Ananth Madhavan, Jose Marin, Narayan Naik, Theo Nijman, Bob Nobay, Richard Payne, Rafael Repullo, Enrique Sentana, Hyun Song Shin, Erik Thyssen, Alan Timmerman, Ian Tonks, Pradeep Ya- dav and Stephen Wells. All of them contributed with valuable ideas and much appreciated criticism. I have presented most of this work in various seminars in different Univer sities, Business Schools and Associations’ Annual Meetings. These occasions generated substantial feedback which led to subsequent improvements in my work. In view of this, I would like to show my gratitude to participants in seminars at CEMFI, London Business School, Kelley School of Business, Fi nancial Markets Group lunchtime seminars, Said Business School, City Busi ness School, Bocconi University, Pennyslvania State University, Michigan State University, Italian Exchange, Tilburg University, University of Am sterdam, University of Frankfurt, Pompeu Fabra University, York Univer sity, Warwick University and Scottish Institute for Research in Investment and Finance (University of Stratchylde). I have also presented papers based on some of the Chapters at the Annual Meetings of the European Finance Association (Helsinki and London), the Financial Management Association (Barcelona and Edinburgh) and LACEA (Rio de Janeiro). This work would not have been possible without the supply of high fre quency data from different Exchanges. I would like to thank Luca Filippa (Italian Exchange), Thorsten Ludecke and Hartmut Schmidt (German Ex change), Matthew Leighton (London Stock Exchange) and Bernard Perrot (Bourse de Paris) for making data sets available. Finally I would like to thank all my colleagues and friends in the Depart ment of Accounting and Finance and in the Financial Markets Group (FMG) for their encouragement and for entertaining my ideas for more than four years. I will always cherish the friendship of FMG students and researchers, such as Max Bruche, Andrea Caggese, Vicente Cunat, Robert Kosowski, Raoul Minetti and Alex Muermann. I will also remember the support given to me by a handful of good friends, like George Abela, Joseph Attard, David Fabri, Elena Ivleva, Carla Musella, Carlo, Paola and Guido Pagano and Lino Spiteri. I would also like to thank the administrative staff in the Department of Accounting and Finance, especially Mary Comben and Dorothy Richards, and the staff at the FMG. Finally, I would like to thank my family, especially my mother, for their constant support throughout the years. Without their understanding it would have been much harder to start and finish the work presented here. Contents C h ap ter 1. Introduction 10 1.1 Large Trades’ Impacts Across Ma rk e ts ........................................ 15 1.1.1 Major R esults ..................................................................... 17 1.1.2 Contribution to Literature ................................................ 18 1.2 Market Frictions ........................................................................... 19 1.2.1 Major R esults ......................................................................... 22 1.2.2 Contribution to Literature ....................................................24 1.3 Price Efficiency in a Hybrid M arket ................................................ 24 1.3.1 Major R esults ......................................................................... 27 1.3.2 Contribution to Literature ....................................................28 1.4 Conclusion ........................................................................................... 29 Chapter 2.1nter-market Impacts Generated by Large Trades 31 2.1 Introduction ........................................................................................ 31 2.2 Literature Review ...............................................................................35 2.2.1 Large Trades ......................................................................... 35 2.2.2 SEAQ-I: Impact and E v o lu tio n .......................................... 37 2.2.3 Fragmentation of Order F l o w ............................................. 40 2.3 Institutional Background and Hypotheses ........................................ 44 2.3.1 Hypotheses T e s te d ................................................................50 2.4 Data and Methodology ......................................................................56 2.4.1 D a ta .........................................................................................56 2.4.2 Methodology ......................................................................... 58 2.4.3 Changes From Established T echniques ..............................59 2.4.4 Trade Clustering and Filtering R ules .................................61 2.5 Results..................................................................................................70