Robust and Efficient Strategies to Track and Outperform a Benchmark
32 Pages Posted: 19 Feb 2009
There are 3 versions of this paper
Robust and Efficient Strategies to Track and Outperform a Benchmark
Robust and Efficient Strategies to Track and Outperform a Benchmark
Robust and Efficient Strategies to Track and Outperform a Benchmark
Date Written: February 15, 2009
Abstract
I investigate the question of how to construct a portfolio consisting of a few securities that an investor can use to track a benchmark. I consider two approaches: a sequential stepwise regression and another method based on factor models of security returns. The rst approach produces the standard hedge portfolio that has the maximum feasible correlation with the benchmark. The second approach produces weights that are proportional to a "signal-to-noise" ratio of factor beta to idiosyncratic volatility. I also consider a second objective that maximizes expected returns subject to minimizing the variance of tracking error. The security selection criterion naturally extends to the product of the information ratio and the signal-to-noise ratio. I implement the algorithms presented in the paper using three widely followed stock indices with very good results.
Keywords: Optimal Portfolio Weights, Benchmarking
JEL Classification: G11, G12
Suggested Citation: Suggested Citation