An Evaluation of Alternative Equity Indices - Part 1: Heuristic and Optimised Weighting Schemes

41 Pages Posted: 1 Apr 2013

See all articles by Andrew Clare

Andrew Clare

City, University of London - Bayes Business School

Nick Motson

City University London - Bayes Business School

Steve Thomas

City University London - The Business School

Date Written: March 30, 2013

Abstract

There is now a dazzling array of alternatives to the market-cap approach to choosing constituent weights for equity indices. Using data on the 1,000 largest US stocks every year from 1968 to the end of 2011 we compare and contrast the performance of a set of alternative indexing approaches. The alternatives that we explore can be loosely categorised into two groups. First, a set of weighting techniques that Chow et al (2011) describe as “heuristic.” The second set are based upon “optimisation techniques,” since they all require the maximisation or minimisation of some mathematical function subject to a set of constraints to derive the constituent weights. We find that all of the alternative indices considered here would have produced a better risk-adjusted performance than could have been achieved by having a passive exposure to a market capitalisation-weighted index. However, the most important result of our work stems from our ten million Monte Carlo simulations. We find that choosing constituent weights randomly, that is, applying weights that could have been chosen by monkeys, would also have produced a far better risk-adjusted performance than that produced by a cap-weighted scheme.

Keywords: Alternative equity indices, risk-adjusted performance, Monte Carlo simulation

JEL Classification: G11,12

Suggested Citation

Clare, Andrew D. and Motson, Nicholas E. and Thomas, Stephen H., An Evaluation of Alternative Equity Indices - Part 1: Heuristic and Optimised Weighting Schemes (March 30, 2013). Available at SSRN: https://ssrn.com/abstract=2242028 or http://dx.doi.org/10.2139/ssrn.2242028

Andrew D. Clare (Contact Author)

City, University of London - Bayes Business School ( email )

106, Bunhill Row
London, EC1Y 8TZ
United Kingdom

Nicholas E. Motson

City University London - Bayes Business School ( email )

106 Bunhill Row
London, EC1Y 8TZ
United Kingdom

Stephen H. Thomas

City University London - The Business School ( email )

106 Bunhill Row
London, EC1Y 8TZ
United Kingdom
+44 (0) 20 7040 5271 (Phone)
+44 (0) 20 7040 8881 (Fax)

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