Smart Beta Asset Allocation Models

How to Allocate Smartly to Smart Beta?

March 2019. Reading Time: 10 Minutes. Author: Nicolas Rabener.

SUMMARY

  • Most smart beta strategies outperformed the market since 1990, but few have in recent years
  • Diversifying across strategies mitigates the risk of underperformance
  • Various asset allocation models for creating multi-factor portfolios highlight similar results

INTRODUCTION

The appearance of smart beta ETFs has simplified the life of investors as they no longer need to suffice themselves with plain beta. However, investors that allocated to Value-focused smart beta ETFs have painfully become aware that smart beta is not always better than beta, given the underperformance over the last decade.

Investors, fortunately, have a choice of multiple smart beta categories, which can be exploited by diversifying across strategies in pursuit of outperformance with higher consistency. However, once the decision was made to create a multi-factor portfolio, it raises the question of how to allocate smartly to the strategies.

In this short research note, we will investigate asset allocation models for smart beta strategies in the US stock market (read Factor Allocation Models).

METHODOLOGY

We focus on seven factors namely Value, Size, Momentum, Low Volatility, Quality, Growth, and Dividend Yield in the US stock market. The long-only factor portfolios are created by selecting the 30% stocks ranked most favorably by the factor and weight these by their market capitalization. The factor definitions are in line with academic research. Only stocks with a minimum market capitalization of $1 billion are included. Portfolios are rebalanced monthly and each transaction incurs costs of 10 basis points.

It is worth noting that we are not using the actual returns of smart beta ETFs as these have a limited price history. The first Value and Growth-focused ETFs were launched in 2000 while Low Volatility smart beta ETFs appeared only in 2009. However, we recently benchmarked our theoretical long-only factor portfolios to smart beta ETFs, which revealed relatively minor tracking errors. Please see our research note Bench