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[Brunnermeier]Asset Pricing Under Asymmetric Information “This book develops the conceptual foundations required for the analysis of markets with asymmetric information, and uses them to provide a clear survey and synthesis of the theoretical literature on bubbles, market microstructure, crashes, and herding in financial markets. The book is not only useful to the beginner who requires a guide through the rapidly developing literature, but provides insight and perspective that the expert will also appreciate.” Michael Brennan Irwin and Goldyne Hearsh Professor of Banking and Finance at the University of California, Los Angeles, and Professor of Finance at the London Business School President of the American Finance Association, 1989 “This book provides an excellent account of how bubbles and crashes and various other phenomena can occur. Traditional asset pricing theories have assumed symmetric information. Including asymmetric information radically alters the results that are obtained. The author takes a com- plex subject and presents it in a clear and concise manner. I strongly recommend it for anybody seriously interested in the theory of asset pricing.” Franklin Allen Nippon Life Professor of Finance and Economics at the Wharton School, University of Pennsylvania President of the American Finance Association, 2000 “This timely book provides an invaluable map for students and researchers navigating the literature on market microstructure, and more generally, on equilibrium with asymmetric information. It will become highly recommended reading for graduate courses in the economics of uncertainty and in financial economics.” Hyun Song Shin Professor of Finance at the London School of Economics www.rasabourse.com This page intentionally left blank www.rasabourse.com Asset Pricing under Asymmetric Information Bubbles, Crashes, Technical Analysis, and Herding MARKUS K. BRUNNERMEIER 3 www.rasabourse.com OXFORD UNIVERSITY PRBSS Great Clarendon Street, Oxford 0x2 6DP Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide in Oxford New York Auckland Bangkok Buenos Aires Cape Town Chennai Dar es Salaam Delhi Hong Kong Istanbul Karachi Kolkata Kuala Lumpur Madrid Melbourne Mexico City Mumbai Nairobi Sao Paulo Shanghai Taipei Tokyo Toronto Oxford is a registered trade mark of Oxford University Press in the UK and in certain other countries Published in the United States by Oxford University Press Inc., New York © Markus K. Brunnermeier 2001 The moral rights of the author have been asserted Database right Oxford University Press (maker) First published 2001 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, without the prior permission in writing of Oxford University Press, or as expressly permitted by law, or under terms agreed with the appropriate reprographics rights organization. Enquiries concerning reproduction outside the scope of the above should be sent to the Rights Department, Oxford University Press, at the address above You must not circulate this book in any other binding or cover and you must impose this same condition on any acquirer British Library Cataloguing in Publication Data Data available Library of Congress Cataloging in Publication Data Brunnermeier, Markus Konrad. Asset pricing under asymmetric information: bubbles, crashes, technical analysis, and herding / Markus K. Brunnermeier. p. cm Includes bibliographical references and index. 1. Stock—Prices 2. Capital assets pricing model. 3. information theory in economics. I. Title HG4636 .878 2000 332.63'222-dc21 00-064994 ISBN 0-19-829698-3 3579 10 864 Typeset by Newgen Imaging Systems (P) Ltd., Chennai, India Printed in Great Britain on acid-free paper by TJ. International Ltd., Padstow, Cornwall www.rasabourse.com To Smita www.rasabourse.com This page intentionally left blank www.rasabourse.com CONTENTS List of figures ix Preface xi 1. Information, Equilibrium, and Efficiency Concepts 1 1.1. Modeling Information 2 1.2. Rational Expectations Equilibrium and Bayesian Nash Equilibrium 14 1.2.1. Rational Expectations Equilibrium 14 1.2.2. Bayesian Nash Equilibrium 16 1.3. Allocative and Informational Efficiency 21 2. No-Trade Theorems, Competitive Asset Pricing, Bubbles 30 2.1. No-Trade Theorems 30 2.2. Competitive Asset Prices and Market Completeness 37 2.2.1. Static Two-Period Models 38 2.2.2. Dynamic Models – Complete Equitization versus Dynamic Completeness 44 2.3 Bubbles 47 2.3.1. Growth Bubbles under Symmetric Information 48 2.3.2. Information Bubbles 55 3. Classification of Market Microstructure Models 60 3.1. Simultaneous Demand Schedule Models 65 3.1.1. Competitive REE 65 3.1.2. Strategic Share Auctions 72 3.2. Sequential Move Models 79 3.2.1. Screening Models a` la Glosten 79 3.2.2. Sequential Trade Models a` la Glosten and Milgrom 87 3.2.3. Kyle-Models and Signaling Models 93 4. Dynamic Trading Models, Technical Analysis, and the Role of Trading Volume 98 4.1. Technical Analysis – Inferring Information from Past Prices 99 4.1.1. Technical Analysis – Evaluating New Information 100 4.1.2. Technical Analysis about Fundamental Value 103 www.rasabourse.com viii Contents 4.2. Serial Correlation Induced by Learning and the Infinite Regress Problem 113 4.3. Competitive Multiperiod Models 117 4.4. Inferring Information from Trading Volume in a Competitive Market Order Model 130 4.5. Strategic Multiperiod Market Order Models with a Market Maker 136 5. Herding and Informational Cascades 147 5.1. Herding due to Payoff Externalities 147 5.2. Herding due to Information Externalities 148 5.2.1. Exogenous Sequencing 149 5.2.2. Endogenous Sequencing, Real Options, and Strategic Delay 153 5.3. Reputational Herding and Anti-herding in Reputational Principal–Agent Models 157 5.3.1. Exogenous Sequencing 158 5.3.2. Endogenous Sequencing 163 6. Herding in Finance, Stock Market Crashes, Frenzies, and Bank Runs 165 6.1. Stock Market Crashes 166 6.1.1. Crashes in Competitive REE Models 168 6.1.2. Crashes in Sequential Trade Models 177 6.1.3. Crashes and Frenzies in Auctions and War of Attrition Games 184 6.2. Keynes’ Beauty Contest, Investigative Herding, and Limits of Arbitrage 190 6.2.1. Unwinding due to Short Horizons 192 6.2.2. Unwinding due to Risk Aversion in Incomplete Markets Settings 198 6.2.3. Unwinding due to Principal–Agent Problems 204 6.3. Firms’ Short-Termism 211 6.4. Bank Runs and Financial Crisis 213 References 221 Index 233 www.rasabourse.com LIST OF FIGURES 1.1 Inference problem from price changes 28 2.1 Illustration of common knowledge events 32 2.2 Illustration of Aumann’s agreement theorem 33 3.1 Average market price schedules under uniform and discriminatory pricing 85 3.2 Tree diagram of the trading probabilities 89 6.1 Price crash in a multiple equilibrium setting 174 6.2 Frenzy in an auction 188 www.rasabourse.com This page intentionally left blank www.rasabourse.com PREFACE Motivation A vast number of assets changes hands every day. Whether these assets are stocks, bonds, currencies, derivatives, real estate, or just somebody’s house around the corner, there are common features driving the market price of these assets. For example, asset prices fluctuate more wildly than the prices of ordinary consumption goods. We observe emerging and bursting bubbles, bullish markets, and stock market crashes. Another distinguishing feature of assets is that they entail uncertain payments, most of which occur far in the future. The price of assets is driven by expectations about these future payoffs. New informa- tion causes market participants to re-evaluate their expectations. For example, news about a company’s future earning prospects changes the investors’ expected value of stocks or bonds, while news of a coun- try’s economic prospects affects currency exchange rates. Depending on their information, market participants buy or sell the asset. In short, their information affects their trading activity and, thus, the asset price. Information flow is, however, not just a one-way street. Traders who do not receive a piece of new information are still con- scious of the fact that the actions of other traders are driven by their information set. Therefore, uninformed traders can infer part of the other traders’ information from the current movement of an asset’s price. They might be able to learn even more by taking the whole price history into account. This leads us to the question of the extent to which technical or chart analysis is helpful in predicting the future price path. There are many additional questions that fascinate both profession- als and laymen. Why do bubbles develop and crashes occur? Why is the trading volume in terms of assets so much higher than real economic activity? Can people’s herding behavior be simply attributed to irrational panic? Going beyond positive theory, some normative policy issues also arise. What are the early warning signals indicating that a different policy should be adopted? Can a different design of exchanges and other financial institutions reduce the risk of crashes and bubbles? www.rasabourse.com xii Preface If financial crises and large swings in asset prices only affect the nom- inal side of the economy, there would not be much to worry about. However, as illustrated by the recent experiences of the Southeast Asian tiger economies, stock market and currency turmoil can easily turn into full-fledged economic crises. The unravelling of financial markets can spill over and affect the real side of economies. Therefore, a good understanding of price processes is needed to help us foresee possible crashes. In recent years, the academic literature has taken giant strides towards improving our understanding of the price process of assets. This book offers a detailed and up-to-date review of the recent theoretical literature in this area. It provides a framework for understanding price processes and emphasizes the informational aspects of asset price dynamics.
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