Investing within the volatile nature of stock markets is commonly perceived as a venture with uncontrollable outcomes. However, employing theories such as probability, “Stock Market Crashes,” attempts to make the unpredictable predictable. Primarily looking into and detailing stock market crashes littered across history, this book acts as a guide on how the past used methods to run around or past the problems and how to use it in the unforeseeable future. Furthermore, this book introduces a stopping rule model that can guarantee good exit results and predictive models that can be used in stochastic investment models.
About the Author
William T. Ziemba is an Alumni Professor of Financial Modeling and Stochastic Optimization in the Sunder School of Business and the University of British Columbia, where he taught from 1986-2006. He gained his Ph.D. from the University of California, Berkeley. Currently, he teaches part-time and makes short visits to numerous universities for research purposes. In his visits, he is also a Visiting Professor at Cambridge, Oxford, London School of Economics, and Warwick, among many others.
Mikhail Zhitlukhin is a researcher at Steklov Mathematical Institute in Moscow, Russia. In addition, he also holds lectures at the Higher School of Economics in Moscow. He has a Ph.D. from Steklov Institute as well as the University of Manchester, UK. His research primarily focuses on probability theory, stochastic processes, optimal control theory, and applications in finance and economics.
Sebastien Lleo is an Associate Professor in the Finance Department at NEOMA Business School in France and a tutor on the Certificate in Quantitative Finance at FitchLearning, UK. He is currently a Director of NEOMA’s doctoral programs and a member of the Steering Group of CQF Institute.
Table of Contents
- Review Quotes
- About the Authors
- Discovery of the Bond-Stock Earnings Yield Differential Model
- Prediction of the 2007-2009 Stock Market Crashes in the U.S., China, and Iceland
- The High Price-Earnings Stock Market Danger Approach of Campbell and Shiller versus the BSEYD Model
- Other Prediction Models for the Big Crashes Averaging – 25%
- Effect of Fed Meetings and Small-Cap Dominance
- Using Zweig’s Monetary and Momentum Models in the Modern Era
- Analysis and Possible Prediction of Declines in the -5% to -15% Range
- A Stopping Rule Model for Exiting Bubble-like Markets with Applications
- A Simple Procedure to Incorporate Predictive Models in Stochastic Investment Models
- Appendix A. Other Bubble-testing Methodologies and Historical Bubbles
- Appendix B. Mathematics of the Changepoint Detection Model