SPEAKER: Kartik Sivaramakrishnan

ABSTRACT:

The traditional Markowitz mean-variance framework is based on a single-period portfolio model. Single-period portfolio optimization does not use any data and decisions beyond the rebalancing time horizon with the result that that its policies are "myopic" in nature. For long-term investors, multiperiod optimization offers the opportunity to make "wait-and-see" policy decisions by including approximate forecasts and long-term policy decisions beyond the rebalancing time horizon.

We consider portfolio optimization with a composite alpha signal that is composed of a short-term and a long-term alpha signal. The short-term alpha better predicts returns at the end of the rebalancing period but it decays quickly. On the other hand, the long-term alpha has less predictive power than the short-term alpha but it decays slowly. We develop a two-stage multi-period model that incorporates this alpha model to construct the optimal portfolio at the end of the rebalancing period. We compare this model with the traditional single-period MVO model on simulated and realistic backtests and show that the multi-period model generates portfolios with superior realized performance.

Short Bio:

Kartik Sivaramakrishnan is a Senior Research Associate at Axioma where he maintains Axioma's flagship portfolio optimizer that offers the most flexible construction tool in the market. Kartik is interested in developing second-order mixed-integer portfolio models, and interior point algorithms and associated software for solving these models in a high performance computing environment. He also researches the applications of these models in improving the investment process in practice. Most recently he was involved in developing the NASDAQ-Axioma commodity indexes that track Oil, Gold, and a basket of agricultural products. 

Prior to joining Axioma, Kartik was a tenure-track Assistant Professor in the Department of Mathematics and affiliated with the Operations Research program at North Carolina State University in Raleigh. Kartik has a Ph.D. in Applied Mathematics from Rensselaer Polytechnic Institute and a Masters degree in Electrical Engineering from the Indian Institute of Science in Bangalore. His research has been published in optimization, OR, and practitioner journals.