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August 10, 2013

Lipper Insight: Weighting and Stock Selection Schemes of Smart-Beta Funds

by andrew.clark.

In the first two articles in this series on smart-beta funds we have given a definition of them and started our discussion of characteristics-based and diversification-based smart-beta indices. In this article we look at stock selection and weighting schemes in more detail.

Amenc et al..[1] write, “Stock selection by construction, e.g. stock fundamentals, takes into account only the stand alone properties of stocks and it therefore does not account for the interaction effects between stocks.”  Stock selection on its own does not trade off risk and return but does explicitly and transparently tilt a portfolio toward the desired stock characteristics or risk factor(s).

When we just trade off risk and return, such as in the case of using volatility minimization to build a low-volatility portfolio, the methodology does not take into account the individual stock characteristics. As a consequence the methodology could be adding unwanted risk(s) that come from the stock characteristics “preferred” by the risk-return methodology. The risk-return methodology of portfolio construction, therefore, could lead to an implicit (versus explicit) tilt toward risk factors.  

Each methodology has its risks and benefits. Following both Amenc et al. and Clark and Kenyon[2] we can demonstrate the benefits of combining the two methodologies to construct a smart-beta index. To start, we need to be able to evaluate the merits of the choices made at each step of the index construction process, i.e., a clearly defined objective is required. Unfortunately, most smart-beta index manufacturers do not provide a definition in sufficient detail to evaluate the merits of their choices. For example, the manufacturers of fundamentals-based indices argue that these indices provide a better representation of the business part of the economy versus what cap-weighted indices provide. Unfortunately, most—if not all—fundamentals-based constructors do not show formally that their claim of a better representation of the economy actually occurs.

REUTERS/Vivek Prakash

REUTERS/Vivek Prakash

In contrast to the lack of clarity just noted, a stock selection scheme and risk/return methodology necessarily comes with explicit objectives and a clear way of judging how well the portfolio performs vis a vis its market-cap-weighted index (or a suitable market-cap-weighted benchmark). Two techniques that do examine the issue in some detail are discussed in the aforementioned article by Clark and Kenyon and one by Guerard, Xu, and Gultekin[3]. Clark and Kenyon built a smart-beta index that outperforms (on a nonrisk- adjusted and a risk-adjusted basis) the S&P 500 and a second growth-tilt smart-beta index that outperforms (also on a nonrisk-adjusted and a risk-adjusted basis) the Russell 3000 Growth index. We recommend to the reader the issue of the Journal of Investing that contains both of these articles. We do so because other authors in the issue construct smart-beta indices that outperform their benchmarks (on both a nonrisk-adjusted and risk-adjusted basis).

[1] N. Amenc, F. Goltz, and A. Lodh, “Choose Your Betas: Benchmarking Alternative Equity Strategies,” Journal of Portfolio Management, Volume 39, Number 1.

[2] A. Clark and J. Kenyon, “Using MOEAS to Outperform Stock Benchmarks in the Presence of Typical Portfolio Constraints,” Journal of Investing, Volume 21, Number 1.

[3] J.B. Guerard, G. Xu, and M. Gultekin, “Investing with Momentum: Past Present and Future,” Journal of Investing, Volume 21, Number 1.

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