Efficiency Of Racetrack Betting Markets

A reprint of one of the classic volumes on racetrack efficiency, this book is the only one in its field that deals with the racetrack betting market in-depth, containing all the important historical papers on racetrack efficiency. As evidenced by the collection of articles, the understanding of racetrack betting is clearly drawn from, and has correspondingly returned something to, all the fields of psychology, economics, finance, statistics, mathematics and management science.

William T Ziemba is the Alumni Professor of Financial Modeling and Stochastic Optimization, Emeritus in the Sauder School of Business, University of British Columbia, Canada where he taught from 1968 to 2004. He now teaches as a Visiting Professor. He has been a Visiting Professor at Cambridge, Oxford, London School of Economics, and Warwick in the UK; Stanford, UCLA, Berkeley, Chicago and MIT in the US; Bergamo and Venice in Italy; Tsukuba in Japan; and the National University of Singapore. Leading financial institutions which he has been consultant to include the Frank Russell Company, Morgan Stanley, Buchanan Partners and Gordon Capital. His research is in asset-liability management, portfolio theory and practice, security market imperfections, Japanese and Asian financial markets, sports and lottery investments and applied stochastic programming.

Victor SY Lo is currently Vice President, Decision Sciences at Fidelity Investments where he manages a team of analytic professionals. Previously, he was VP and Manager of Modeling and Analysis at FleetBoston Financial, and a Senior Associate at Mercer Management Consulting. In addition to analytics and management, his work has included bridging the gap between data miners, business analysts, and marketers by recommending and applying novel techniques to maximize business impact. Throughout Lo's industrial career, he has applied experimental design for conjoint-based surveys and direct marketing, time series analysis for measuring advertising effectiveness, propensity score matching for causal measurement, correspondence analysis for perceptual mapping, cluster analysis for segmentation, discrete choice analysis for pricing and feature optimization, survival analysis for employee retention, and data mining techniques such as decision tree and neural network for database marketing. His academic research included applications of probability, statistical, and nonlinear optimization models in gambling strategies and quality engineering. He has published articles in management science, data mining, and statistics literature.

Donald B Hausch is the Dickson-Bascom Professor of Business at the University of Wisconsin-Madison. His main areas of research are auction theory, contract theory and the empirical investigation of market inefficiency. Hausch has coauthored two books and coedited two volumes. He has written numerous articles published in the American Economic Review, Review of Financial Studies, International Economic Review, Management Science, Journal of Business, Journal of Applied Corporate Finance, Economic Theory, RAND Journal of Economics, and other journals. He has consulted for the World Bank on the resolution of systemic financial distress.