We investigate changepoints in the cross-section of stock returns using an ensemble of dedicated unsupervised learning methods. Our large-scale study reveals a sustained incidence of changepoints in the mean, variance, and distribution. This finding is robust to the choice of the changepoint...

Changepoint detection methods originated in Shewhart’s seminal work on quality control in industrial production (Shewhart, 1931, 1939). Wald then pioneered sequential statistical analysis to test hypotheses successively as new data become available (Wald, 1945; Wolfowitz and Wald, 1948). Over the...

"This book is a selection of the journal publications of William T Ziemba. Over a span of 50 years, Professor Ziemba contributed to a wide variety of disciplines including Stochastic Programming, Portfolio Theory, Sports Betting, and Risk Management. In his work he collaborated with academics...

Stochastic processes is one of the key operations research tools for analysis of complex phenomenon. This paper has a unique application to the study of mean changing models in stock markets. The idea is to enter and exit stock markets like Apple Computer and the broad S&P500 index at good times...

This paper discusses the state of the art in research in racetrack and lottery investment markets. Market efficiency and the pricing of various wagers is studied along with new developments since the Thaler and Ziemba (1988) review. The weak form inefficient market approach using stochastic...

This paper studies the US equity market during the COVID-19 period in the first half of 2020. There is a record rise, then a record fall in prices and then a record recovery. Throughout the period there was extreme volatility and much short term momentum with fear and greed alternating. The VIX...