Optimization With Alpha Decay
Agenda
Presented by Northfield President Dan diBartolomeo
One of the most neglected considerations in most active equity strategies is that alpha estimates for individual securities decay over time. Depending on the nature of the active strategy, the decay in predictive power of alpha estimates may be slow (e.g. a deep value strategy) or rapid (e.g. earnings surprise).
Understanding how rapidly the predictive power of an active strategy declines is the key to determining the optimal level of portfolio turnover in the presence of non-zero transaction costs. For large institutional investors where market impact of trades is a material issue, properly parameterizing alpha decay is imperative.
In this presentation, we will begin with a review of the proposed methods such as Sneddon (JOI, 2006) and Baldacci, Beneviste, and Ritter (SSRN 2022). Next, we will discuss how the “multiperiod approximation” method already present in the Northfield Optimizer contributes to parametrization of optimal turnover levels. We will conclude with discussion of the “doubling negative effect” of less frequent trading, as your portfolio is more impacted decay and your less frequent trades are larger which increases market impact costs.
About Dan diBartolomeo
Dan diBartolomeo is President and founder of Northfield Information Services, Inc. He is also a former Visiting Professor at the CARISMA Research Center of Brunel University in London and serves on the Board of Directors of the Chicago Quantitative Alliance and the advisory board of the International Association for Quantitative Finance. He is a regional director of the Professional Risk Managers International Association, (PRMIA), and the Quantitative Work Alliance for Applied Finance, Education and Wisdom (QWAFAFEW). He is past president and director of the Boston Economic Club.
Dan has been admitted as an expert witness in US federal courts and state courts for litigation matters regarding investment management practices and derivatives.
In 2010, Dan received an award from Institutional Investor magazine as one of the forty most influential executives in financial technology in connection with his analytical work that helped uncover the Madoff investment fraud.
Dan is a director of the American Computer Foundation, and formerly served on the industry liaison committee of the Department of Statistics and Actuarial Sciences at New Jersey Institute of Technology. He continues his more than twenty years of service as a judge in the Moskowitz Prize competition, given by the University of California at Berkeley for excellence in academic research on socially responsible investing.
Dan has a long list of publications including books, book chapters and research papers in professional journals such as Financial Analyst Journal, Quantitative Finance and Journal of Investing. In 2017, he was named co-editor of the Journal of Asset Management