Bye-bye “Smart Beta”. Hello “Factor Investing”

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In our view, diversified multi-factor approaches exposed to value, low risk, momentum and quality premiums with a strong focus on risk management offer better value for the management fees an investor pays than off-the-shelf smart beta indices.

1) Investors should dump smart beta indices in favour of diversified multi-factor strategies

2) Exposure to value, low risk, momentum and quality premiums should be sought

3) Expect higher risk-adjusted returns from optimised multi-factor strategies which best handle exposures to factor premiums and portfolio constraints.

Smart Beta is all about exposure to risk factor premiums such as value, small caps and low risk

Several years after we first heard of smart beta strategies it is now almost the consensus view that smart beta indices derive their performance and risk from exposures to well-known risk factors such as value, low risk and small caps (see Exhibits 1 and 2 below). We were among the first to point that out. In 2011 we showed that  the performance of both minimum variance and maximum diversification could be explained by their exposure to the low risk factor premium, that risk parity could be explained by exposures to the low risk and the small capitalisation factor premiums and that equally-weighted portfolios could be explained by their exposure to the small capitalisation premium. Our results appeared in a paper “Demystifying risk-based strategies: a simple alpha plus beta description” in the spring 2012 issue of The Journal of Portfolio Management.

Exhibit 1: Decomposition of the excess returns of a simulated risk-controlled global multi-factor strategy exposed to value, momentum, quality and low-risk factors and benchmarked against the MSCI World Index (unhedged net returns).


Source: BNP Paribas Investment Partners, THEAM, MSCI and Exshare on 31 December 2014.


Exhibit 2: Simulated net asset values for a risk-controlled global multi-factor strategy exposed to the value, momentum, quality and low risk factors and benchmarked against the MSCI World Index (unhedged net returns).


Source: BNP Paribas Investment Partners, THEAM, MSCI and Exshare on 31 December 2014.

(Results are based on monthly total returns in USD and gross of fees. Market impact and transaction costs are not included. Hypothetical performance results have many inherent limitations and have been obtained with the benefit of hindsight. Past performance is not indicative of future results.)

Fundamental indexing is just value in disguise

The same is true of fundamentally-weighted smart beta indices wherein stocks are weighted in proportion to their fundamentals such as book-value or earnings. Jason Hsu, Tzee-man Chow and Vitali Kalesnik from Research Affiliates, creators of fundamental indexing, along with Bryce Little from Cornell University, recognised this in a paper “A survey of alternative equity index strategies” published in Financial Analysts Journal in 2011. They acknowledged that exposure to value factors is the driver of performance and risk in fundamentally-weighted strategies.

Smart beta indices are clumsy approaches to gaining exposure to factor premiums

Smart beta strategies are thus nothing more than a form of systematic active strategy where the stock weights are determined by a certain formula. This formula tends to ignore the weight of the stock in the market capitalisation index. For this reason the tracking error is left to the mercy of markets and can be significant and volatile over time. Tracking error tends to have a large systematic component composed of under-diversified and poorly controlled exposures to factor premiums. Smart beta indices are simply not optimally exposed to factor premiums. They have not been designed for that purpose.

The way forward for factor investing

What then is the alternative to smart beta indexing? We provide an efficient answer in a paper “An integrated risk-budgeting approach for multi-strategy equity portfolios” published in Journal of Asset Management in 2014.

We propose a three-step approach. The first concerns the selection of risk-factor premiums and allocation of factor weights. Examples of risk factors with strong academic evidence of a premium include value, momentum, low risk, quality and small capitalisation. As our paper demonstrates, targeting the same risk budget allocation to each factor is a sensible allocation which relies on diversification. In this case, the weight of each factor changes over time and is inversely proportional to its volatility. We explain why targeting a constant risk budget is superior to other factor allocation choices in a more recent paper “Intertemporal risk parity: a constant volatility framework for factor investing” published in The Journal of Investment Strategies at the end of 2014.

The second step is the construction of an unconstrained active portfolio with chosen factor exposures. This requires only basic arithmetic. The weight of a stock in this ideal unconstrained portfolio is just the weighted sum of the stock weight in market-neutral long-short portfolios designed to capture factor premiums plus its weight in the market capitalisation portfolio.

The third step, to handle constraints, is the least straightforward. We propose the use of implied returns derived from our ideal unconstrained portfolio. Implied returns are the returns which accurately reflect the views in the unconstrained portfolio. In the paper we demonstrate that, when optimising from implied returns, the final constrained portfolio remains as close as possible to the initial target unconstrained portfolio, and that the impact of constraints is minimised.

In the paper we illustrate the framework with a number of numerical examples which clearly show how robust the approach is. We show that efficient, investable portfolios with targeted exposures to factor premiums can be built. Furthermore, our experience with the management of such strategies demonstrates that high-capacity factor investing is possible. We strongly believe that our findings are presented at a challenging time for investors and hope that this will help them to improve their portfolio construction and to navigate the world of smart beta and factor investing with more insight.

Raul Leote de Carvalho

Deputy Head of Financial Engineering at BNP Paribas Investment Partners

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