The best-performing multi-factor portfolio, according to Research Affiliates, is one that includes the momentum factor.
The momentum factor — the basis of an investment strategy that has been criticized for having high trading costs that detract from actual returns — is one of six factors that a pair of Research Affiliates executives included in an “optimal” portfolio designed to deliver the best risk-adjusted returns for its cost.
“Neither a focus on maximizing paper portfolio performance, which ignores the associated trading costs, nor a singular focus on low-cost implementation, which misses opportunities for better performance, will produce an optimal result for multi-factor smart beta investors,” wrote the authors of a new Research Affiliates paper on multi-factor strategy design.
The authors — head of investment strategy Feifei Li and vice president for smart beta Joseph Shim — analyzed many different multi-factor portfolios to find “the most advantageous balance between effectively harvesting the factor premium and implementation cost.”
The best portfolio, they concluded, was one which invested in roughly a quarter of the investable universe based on six investment factors: value, low beta, profitability, investment, momentum, and size.
Including momentum reduced the portfolio’s tracking error by 84 basis points and improved its information ratio from 0.46 to 0.57. And despite the more frequent rebalancing which accompanies the inclusion of the momentum factor, Li and Shim found that adding momentum to a $10 billion portfolio actually reduced trading costs by a single basis point.
“Because momentum is associated with more liquid stocks, the additional liquidity compensates for the increased turnover,” they explained, adding that the low or negative correlations between momentum and the other factors results in trades which “cancel out trades initiated by value” or other factors.
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The inclusion of the size factor — whose validity AQR researchers recently been questioned — boosted the $10 billion portfolio’s return by 26 basis points while lowering trading costs by 7 basis points. Although the size factor made the portfolio slightly more volatile, its lower correlation with other factors reduced the portfolio’s tracking error, resulting in a higher information ratio.
“Because the diversification benefit outweighs the increased cost of implementation, we recommend that investors include both the momentum and size factors in a multi-factor strategy,” Lei and Shim wrote.
Beyond selecting their six factors, the Research Affiliates duo also looked at how different levels of stock concentration would affect cost and performance of portfolios ranging from $1 billion to $10 billion in size.
They found that risk-adjusted returns improved as the portfolio became more concentrated — up to a point. Once the underlying factor portfolios reached the limit of 25 percent of the investable universe, the Sharpe ratio stopped climbing.
Since the more concentrated portfolios also resulted in higher trading costs, especially in larger portfolios, the authors concluded that the best concentration level was around 25 percent.