Statistical Models and Methods for Financial Markets
This book presents statistical methods and models of importance to quantitative finance and links finance theory to market practice via statistical modeling and decision making. Part I provides basic background in statistics, which includes linear regress
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Tze Leung Lai Haipeng Xing
Statistical Models and Methods for Financial Markets
Springer Texts in Statistics Series Editors: G. Casella S. Fienberg I. Olkin
Springer Texts in Statistics
For other titles published in this series, go to www.springer.com/series/417
Tze Leung Lai · Haipeng Xing
Statistical Models and Methods for Financial Markets
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Haipeng Xing Department of Statistics Columbia University New York, NY 10027 USA [email protected]
Tze Leung Lai Department of Statistics Stanford University Stanford, CA 94305 USA [email protected]
Editorial Board George Casella Department of Statistics University of Florida Gainesville, FL 32611-8545 USA
Stephen Fienberg Department of Statistics Carnegie Mellon University Pittsburgh, PA 15213-3890 USA
ISBN: 978-0-387-77826-6 DOI: 10.1007/978-0-387-77827-3
Ingram Okin Department of Statistics Stanford University Stanford, CA 94305 USA
e-ISBN: 978-0-387-77827-3
Library of Congress Control Number: 2008930111 c 2008 Springer Science+Business Media, LLC All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Printed on acid-free paper 9 8 7 6 5 4 3 2 1 springer.com
To Letitia and Ying
Preface
The idea of writing this book arose in 2000 when the first author was assigned to teach the required course STATS 240 (Statistical Methods in Finance) in the new M.S. program in financial mathematics at Stanford, which is an interdisciplinary program that aims to provide a master’s-level education in applied mathematics, statistics, computing, finance, and economics. Students in the program had different backgrounds in statistics. Some had only taken a basic course in statistical inference, while others had taken a broad spectrum of M.S.- and Ph.D.-level statistics courses. On the other hand, all of them had already taken required core courses in investment theory and derivative pricing, and STATS 240 was supposed to link the theory and pricing formulas to real-world data and pricing or investment strategies. Besides students in the program, the course also attracted many students from other departments in the university, further increasing the heterogeneity of students, as many of them had a strong background in mathematical and statistical modeling from the mathematical, physical, and engineering sciences but no previous experience in finance. To address the diversity in background but common strong i
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