We propose a method for optimal portfolio selection using a Bayesian decision theoretic framework that addresses two major shortcomings of the Markowitz approach: the ability to handle higher moments and estimation error. We employ the skew normal distribution which has many attractive features...

We replay an investment game that compares the performance of a player using Bayesian methods for determining portfolio weights with a player that uses the Monte Carlo based resampling approach advocated in Michaud (1998). Markowitz and Usmen (2003) showed that the Michaud player always won....

Machine learning offers a set of powerful tools that holds considerable promise for investment management. As with most quantitative applications in finance, the danger of misapplying these techniques can lead to disappointment. One crucial limitation involves data availability. Many of machine...

We apply state-of-the-art Bayesian machine learning to test whether we can extract valuable information from analysts' recommendations of stock performance. We use a probabilistic model for independent Bayesian classifier combination that has been successfully applied in both the physical and...

Traditional mean-variance efficient portfolios do not capture the potential wealth creation opportunities provided by predictability of asset returns. We propose a simple method for constructing optimally managed portfolios that exploits the possibility that asset returns are predictable. We...

We analyze the history of the equity risk premium from surveys of U.S. Chief Financial Officers (CFOs) conducted every quarter from June 2000 to March 2015. The risk premium is the expected 10-year S&P 500 return relative to a 10-year U.S. Treasury bond yield. We show that the equity risk...

We analyze the history of the equity risk premium from surveys of U.S. Chief Financial Officers (CFOs) conducted every quarter from June 2000 to June 2016. The risk premium is the expected 10-year S&P 500 return relative to a 10-year U.S. Treasury bond yield. The average risk premium in 2016,...

Factor investing has failed to live up to its many promises. Its success is compromised by three problems that are often underappreciated by investors. First, many investors develop exaggerated expectations about factor performance as a result of data mining, crowding, unrealistic trading cost...

Impact costs occur when large buy or sell orders move market prices. The measurement of these costs is crucial for the evaluation of potential trading strategies as well as the successful execution of systematic investment strategies. However, common approaches suffer from a type of myopia:...

In this era of inexpensive computation and vast data, systematic, or algorithmically driven, investment is increasingly popular. Systematic strategies appear in stand-alone products as well in tail-hedging and defensive-overlay strategies. Indeed, given the enormous growth in data, it is...