This year, the fastest-growing strategy in the realm of exchange-traded funds (ETFs) has been the use of multi-factor models. This strategy—which provides simultaneous exposure to several dimensions of the market, such as value, momentum, dividend and volatility—often brings better risk-adjusted returns. But, critics note, it fails to completely eliminate unpredictability.
Over the long term, different factors outperform and underperform in different amounts and at different times relative to cap-weighted benchmarks—with value, for example, outperforming when momentum is underperforming, said Barry Gordon, president and CEO of First Asset Exchange Traded Funds, speaking on Tuesday at the Exchange Traded Forum in Toronto.
“When you put them together, it provides a blended risk-adjusted profile,” Gordon explained.
When using the mutli-factor strategy, it’s important to understand the cyclicality of the factors you’re employing and how they’ve performed under different investment regimes, said Ryan Spourgitis, vice-president of client coverage for Canada with MSCI.
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And although the multi-factor approach is a relatively new development in the ETF landscape, “factor indexes are nothing new per se,” added Spourgitis, speaking at the same event. In late 2013, MSCI launched a host of multi-factor indices aimed at helping institutional investors to passively implement index-linked multi-factor strategies.
Leap of faith
While multi-factor models may produce better risk-adjusted returns, they don’t eliminate all the guesswork from portfolio construction, critics point out.
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For example, there’s no definitive research showing what the optimum weight for each factor should be in a portfolio—and how many factors should be included, noted Victor Medina-Leal, a financial advisor with Raymond James.
Factors could underperform for a long time and nobody can predict when they’ll start outperforming, so investors just have to hope that the weighting they’ve chosen will work out, Medina-Leal explained.