Robust and Efficient Strategies to Track and Outperform a Benchmark

23 Pages Posted: 17 Mar 2010

See all articles by Paskalis Glabadanidis

Paskalis Glabadanidis

Essential Services Commission of South Australia

Multiple version iconThere are 3 versions of this paper

Date Written: February 3, 2010

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 first 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

Glabadanidis, Paskalis, Robust and Efficient Strategies to Track and Outperform a Benchmark (February 3, 2010). Available at SSRN: https://ssrn.com/abstract=1571250 or http://dx.doi.org/10.2139/ssrn.1571250

Paskalis Glabadanidis (Contact Author)

Essential Services Commission of South Australia ( email )

Level 1, 151 Pirie Street
Adelaide, SA 5001
Australia

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