Market Microstructure E-Book

• Herausgeber: John Wiley & Sons
• Kategorie: Fachliteratur
• Serie: Wiley Finance Series
• Sprache: Englisch

Seitenzahl: 364

Veröffentlichungsjahr: 2012

Beschreibung

The latest cutting-edge research on market microstructure

Based on the December 2010 conference on market microstructure, organized with the help of the Institut Louis Bachelier, this guide brings together the leading thinkers to discuss this important field of modern finance. It provides readers with vital insight on the origin of the well-known anomalous "stylized facts" in financial prices series, namely heavy tails, volatility, and clustering, and illustrates their impact on the organization of markets, execution costs, price impact, organization liquidity in electronic markets, and other issues raised by high-frequency trading. World-class contributors cover topics including analysis of high-frequency data, statistics of high-frequency data, market impact, and optimal trading. This is a must-have guide for practitioners and academics in quantitative finance.

Leseprobe

Contents

Cover

Series

Title Page

Copyright

Introduction

About the Editors

Part I: Economic Microstructure Theory

1: Algorithmic Trading: Issues and Preliminary Evidence

1.1 INTRODUCTION

1.2 WHAT IS ALGORITHMIC TRADING?

1.3 MARKET STRUCTURE AND ALGORITHMIC TRADING

1.4 COSTS AND BENEFITS OF ALGORITHMIC TRADING

1.5 EMPIRICAL EVIDENCE

1.6 CONCLUSIONS

1.7 APPENDIX

ACKNOWLEDGMENT

2: Order Choice and Information in Limit Order Markets

2.1 INTRODUCTION

2.2 ORDER CHOICE WITH SYMMETRIC INFORMATION

2.3 ORDER CHOICE WITH ASYMMETRIC INFORMATION

2.4 THE INFORMATION CONTENT OF ORDERS

2.5 QUESTIONS FOR FUTURE RESEARCH

Part II: High Frequency Data Modeling

3: Some Recent Results on High Frequency Correlation

3.1 INTRODUCTION

3.2 DATA DESCRIPTION

3.3 MULTIVARIATE EVENT TIME

3.4 HIGH FREQUENCY LEAD/LAG

3.5 INTRADAY SEASONALITY OF CORRELATION

3.6 CONCLUSION

ACKNOWLEDGMENT

4: Statistical Inference for Volatility and Related Limit Theorems

4.1 INTRODUCTION

4.2 QLA FOR AN ERGODIC DIFFUSION PROCESS

4.3 QLA FOR VOLATILITY IN THE FINITE TIME-HORIZON

4.4 NONSYNCHRONOUS COVARIANCE ESTIMATION

4.5 YUIMA II FOR STATISTICAL ANALYSIS AND SIMULATION FOR STOCHASTIC DIFFERENTIAL EQUATIONS

4.6 HIGHER ORDER ASYMPTOTICS AND FINANCE

ACKNOWLEDGMENTS

Part III: Market Impact

5: Models for the Impact of All Order Book Events

5.1 INTRODUCTION

5.2 A SHORT SUMMARY OF MARKET ORDER IMPACT MODELS

5.3 MANY-EVENT IMPACT MODELS

5.4 MODEL CALIBRATION AND EMPIRICAL TESTS

5.5 CONCLUSION

APPENDIX

ACKNOWLEDGMENTS

6: Limit Order Flow, Market Impact, and Optimal Order Sizes: Evidence from NASDAQ TotalView-ITCH Data

6.1 INTRODUCTION

6.2 MARKET ENVIRONMENT AND DATA

6.3 MAJOR ORDER FLOW AND ORDER BOOK CHARACTERISTICS

6.4 AN ECONOMETRIC MODEL FOR THE MARKET IMPACT OF LIMIT ORDERS

6.5 MARKET IMPACT AT NASDAQ

6.6 OPTIMAL ORDER SIZE

6.7 CONCLUSIONS

ACKNOWLEDGMENT

Part IV: Optimal Trading

Introduction: Trading and Market Micro-structure

An on-going increase of computer-driven trading

Early academic answers and old practices

New practical needs and academic recent advances

7: Collective Portfolio Optimization in Brokerage Data: The Role of Transaction Cost Structure

7.1 INTRODUCTION

7.2 DESCRIPTION OF THE DATA

7.3 RESULTS

7.4 THE INFLUENCE OF TRANSACTION COSTS ON TRADING BEHAVIOR FROM OPTIMAL MEAN-VARIANCE PORTFOLIOS

7.5 DISCUSSION AND OUTLOOK

ACKNOWLEDGMENTS

8: Optimal Execution of Portfolio Transactions with Short-Term Alpha

8.1 INTRODUCTION

8.2 SHORT-TERM ALPHA DECAY AND HIDDEN ORDER ARBITRAGE THEORY

8.3 TOTAL COST DEFINITION AND CONSTRAINTS

8.4 TOTAL COST OPTIMIZATION

8.5 CONCLUSIONS

PROVISO

Combined References

Index

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Library of Congress Cataloging-in-Publication Data:

Market microstructure : confronting many viewpoints / edited by Frédéric Abergel … [et al.]. p. cm. – (The Wiley finance series) Includes bibliographical references and index. ISBN 978-1-119-95277-0 (cloth) 1. Securities. 2. Securities – Prices. 3. Stock exchanges. 4. Microfinance. I. Abergel, Frédéric. HG4521.M319 2012 332.64′2 – dc23 2012002916

A catalogue record for this book is available from the British Library.

ISBN 978-1-119-95241-1 (hardback) ISBN 978-1-119-95277-0 (ebk) ISBN 978-1-119-95278-7 (ebk)     ISBN 978-1-119-95279-4 (ebk)

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Introduction

The accumulation of high frequency market data in recent years has revealed many surprising results. These results are interesting both from theoretical and practical standpoints. The mechanism of price formation is at the very heart of economics; it is also of paramount importance to understand the origin of the well-known anomalous ‘stylized facts’ in financial price series (heavy tails, volatility clustering, etc.). These issues are of obvious importance for practical purposes (organisation of markets, execution costs, price impact, etc.). This activity is also crucial to help the regulators, concerned with the organisation of liquidity in electronic markets and the issues raised by ‘high frequency trading’.

Correspondingly, this problem has been vigorously investigated by at least five different communities (economics, financial mathematics, econometrics, computer science and econo-physics), scattered in academic institutions, banks and hedge funds, with at present limited overlap and sometimes lack of visibility. On the other hand, due to the gigantic amount of available data, precise quantitative theories can now be accurately tested.

At the time where this conference series started in 2010, the interest for market microstructure had finally reached a stage where the interest for the theoretical breakthroughs of the pioneers in the field had become comparable to its practical importance for market practitioners. Thanks to the development of high frequency trading, market microstructure is now, not only a subject of theoretical modelling and simulation but, more interestingly maybe, a real practical field where a better model can make a big difference.

The organisers of the conference thought that it would be extremely fruitful to confront the ideas that have blossomed in those different communities in the past decade. In order to foster this confrontation and ease communication, we have gathered researchers from these different communities, including professionals, and ask them to give introductory tutorials, reviewing both their recent activity and the problems that, in their eyes, are most relevant to address in the near future.

Our aim in setting up this friendly, knowledge-oriented confrontation has been to examine and compare possibly very different views on the nature of the mechanisms relevant to describe and understand what one can actually observe when scrutinising the tick-by-tick behaviour of markets. Such important questions as the interplay between liquidity taking and providing, the existence and characterisation of various types of market impact, the statistical tools designed to handle well the ‘tick’ effect, the ‘best-execution’ and other algorithmic trading strategies, or the question of market design and organisation … have been studied in-depth by the speakers at the conference, and their contributions to this present volume will help shed a new light, or, rather, new lights, on the market microstructure viewed as an object for scientific study as well as a wealth of information for price discovery and trading.

Frédéric AbergelJean-Philippe BouchaudThierry FoucaultCharles-Albert Lehalle andMathieu Rosenbaum

About the Editors

Frédéric Abergel

After graduating from École Normale Supérieure in 1985 and completing a PhD in Mathematics in 1986, Frédéric Abergel started an academic career as a researcher with the CNRS. He spent ten years in the Mathematics Department of the University of Orsay Paris XI, where he obtained his habilitation degree in 1992. He then switched to the capital markets industry and became a ‘quant’ (quantitative analyst). During the second part of his career, Frédéric Abergel has worked for trading floors in various financial institutions, mainly in the derivatives sector, developing pricing and hedging models. In July 2007, he decided to return to Academia, where he now holds the BNP Paribas Chair of Quantitative Finance at École Centrale Paris. His research focuses on the study of empirical properties and mathematical model of market microstructure, high frequency data and algorithmic trading.

Jean-Philippe Bouchaud

Jean-Philippe Bouchaud graduated from the École Normale Supérieure in Paris, where he also obtained his PhD in physics. He was then appointed by the CNRS until 1992. After a year spent in the Cavendish Laboratory (Cambridge), he joined the Service de Physique de l'État Condensé (CEA-Saclay), where he worked on the dynamics of glassy systems and on granular media. He became interested in economics and theoretical finance in 1991. His work in finance includes extreme risk models, agent based simulations, market microstructure and price formation. He has been very critical about the standard concepts and models used in economics and in the financial industry (market efficiency, Black-Scholes models, etc.) He founded the company Science & Finance in 1994 that merged with Capital Fund Management (CFM) in 2000. He is now the President and Head of Research at CFM and professor at Ecole Polytechnique since 2008. He was awarded the IBM young scientist prize in 1990 and the C.N.R.S. Silver Medal in 1996. He has published over 250 scientific papers and several books in physics and in finance.

Thierry Foucault

Thierry Foucault is Professor of Finance at HEC, Paris, where he received his PhD in Finance in 1994. He is a research fellow of the Centre for Economic Policy (CEPR). He has taught in various institutions such as Carnegie Mellon University, the École Polytechnique Fédérale de Lausanne, Oxford (Said Business School), Pompeu Fabra University (Spain), the Tinbergen Institute and the School of Banking and Finance at UNSW. His research focuses on the determinants of financial markets liquidity and the industrial organisation of the securities industry. His work has been published in top-tier scientific journals, including The Journal of Finance, The Journal of Financial Economics and The Review of Financial Studies. He serves on the scientific committees of the Autorité des Marchés Financiers, the Research Foundation of the Banque de France, the Group of Economic Advisors of the Committee of Economic and Markets Analysis of the European Securities and Markets Authority (ESMA) and on the executive committee of the European Finance Association (EFA). He acts as co-editor of the Review of Finance since 2009 and is an Associate Editor of The Review of Asset Pricing Studies. For his research, he received awards from the Europlace Institute of Finance in 2005 and 2009, the annual research prize of the HEC Foundation in 2006 and 2009, and the Analysis Group award for the best paper on Financial Markets and Institutions presented at the 2009 Western Finance Association meetings.

Charles-Albert Lehalle

Currently Head of Quantitative Research at CA Cheuvreux, Charles-Albert Lehalle is an international expert in optimal trading. He published papers in international journals about the use of stochastic control and stochastic algorithms to optimise a trading flow with respect to flexible contraints. He also authored papers on post-trade analysis, market impact estimates and modelling the dynamics of limit order books. Charles-Albert Lehalle lectures at ‘Paris 6 (El Karoui) Master of Finance’ (École Polytechnique, ESSEC, École Normale Supérieure) and MASEF/ENSAE, and gives master classes in the Certificate in Quantitative Finance in London. With a PhD in applied mathematics, his core fields are stochastic processes, information theory and nonlinear control.

Mathieu Rosenbaum

Mathieu Rosenbaum obtained his PhD from Université Paris-Est in 2007. He is now Professor at Université Pierre et Marie Curie (Paris 6) and École Polytechnique and is a member of the CREST (Center of Research in Economics and Statistics). His research mainly focuses on statistical finance problems, such as market microstructure modeling or designing statistical procedures for high frequency data. Also, he has research collaborations with several financial institutions, in particular BNP-Paribas since 2004.

Part I

Economic Microstructure Theory

1

Algorithmic Trading: Issues and Preliminary Evidence

Thierry Foucault

1.1 INTRODUCTION

In 1971, while the organization of trading on the NYSE had not changed much since its creation in 1792, Fischer Black (1971) was asking whether trading could be automated and whether the specialist's judgement could be replaced by that of a computer (the specialist is a market-maker designated to post bid and ask quotes for stocks listed on the NYSE). Forty years later, market forces have given a positive reponse to these questions.

Computerization of trading in financial markets began in the early 1970s with the introduction of the NYSE's “designated order turnaround” (DOT) system that routed orders electronically to the floor of the NYSE. It was then followed with the development of program trading, the automation of index arbitrage in the 1980s, and the introduction of fully computerized matching engines (e.g., the CAC trading system in France in 1986 or the Electronic Communication Networks in the US in the 1990s). In recent years, this evolution accelerated with traders using computers to implement a wide variety of trading strategies, e.g., market-making, at a very fine time scale (the millisecond).

The growing importance of these “high frequency traders” (HFTs) has raised various questions about the effects of algorithmic trading on financial markets. These questions are hotly debated among practitioners, regulators, and in the media. There is no agreement on the effects of HFTs.1 As an example consider these rather opposite views of the HFTs' role by two Princeton economists, Paul Krugman and Burton Malkiel. Krugman has a rather dim view of HFTs:

High-frequency trading probably degrades the stock market's function, because it's a kind of tax on investors who lack access to those superfast computers – which means that the money Goldman spends on those computers has a negative effect on national wealth. As the great Stanford economist Kenneth Arrow put it in 1973, speculation based on private information imposes a “double social loss”: it uses up resources and undermines markets. (Paul Krugman, “Rewarding Bad Actors”, New York Times, 2 August 2009).

In contrast, for Malkiel, high frequency traders have a more positive function: