SPEAKER: Dr. Anureet Saxena

ABSTRACT:

The underestimation of risk of optimized portfolios is a consistent criticism about risk models. Quantitative portfolio managers have historically used a variety of ad hoc techniques to overcome this issue in their investment processes. In this paper, we construct a theory explaining why risk models underestimate the risk of optimized portfolios. We show that the problem is not necessarily with a risk model, but is rather the interaction of expected returns, constraints, and a risk model in an optimizer. We develop an optimization technique that incorporates a dynamic Alpha Alignment Factor (AAF) into the factor risk model during the optimization process. Using actual portfolio manager backtests, we illustrate both how pervasive the underestimation problem can be and the effectiveness of the proposed AAF in correcting the bias of the risk estimates of optimized portfolios.

Speaker bio:
Dr. Anureet Saxena is a research associate at Axioma Inc. Prior to joining Axioma in 2008, he held research positions at Carnegie Mellon University (Egon Balas, mentor), Tata Institute of fundamental research (Narendra Karmarkar, mentor) and T.J. Watson Research Center (IBM).
His research interests include mixed integer linear and non-linear programming, stochastic programming and quantitative finance. He has published four scholarly articles in Mathematical Programming and has delivered more than thirty presentations at various professional meetings. Dr. Saxena is the recipient of the 2008 Gerald L. Thompson doctoral dissertation award in management science for his thesis titled Integer Programming, a Technology.  He holds MS and PhD in industrial administration from Tepper School of Business (CMU), BTech in computer science and engineering from IIT Bombay and is currently a level 2 candidate in the Chartered Financial Analyst (CFA) program.