Why factor investing might not work as well as you hope

Objective tests that support the case for factors might not measure up in the real world

Why factor investing might not work as well as you hope

Factor investing strategies that are bolstered by data mining and performance backtests represent a “huge risk” to investors, according to one firm’s research.

In a recent blog post, Greenline Partners Chief Investment Officer and founder Maneesh Shanbhag has argued that many factors don’t work in practice, and even value and momentum may be less effective in generating alpha than historical evidence suggests.

“Investors can avoid being fooled by backtests by always keeping in mind that most attempts to beat markets will fail because trading is a zero-sum activity,” Shanbhag wrote, as reported on Institutiona lInvestor.

Backtests done at his firm indicated that value investing beats growth stocks that have high price-to-earnings ratios, and “past winners” — how the firm referred to momentum stocks — beat “past losers.” But Shanbhag pointed out that cheap value assets are essentially “past losers,” and momentum stocks are highly similar to growth assets. In other words, he said, the backtests’ findings contradict each other.

“Both cannot simultaneously be true,” he argued. If the firm’s logic is correct, he surmised, then investors should observe that value is highly correlated to recent underperformers, while growth should be tightly coupled to recent outperformers.

Speaking to Institutional Investor, Shanbhag said people’s tendency to be misled by factors can be attributed to human bias and the use of historical data in investment marketing materials. Evidence of high market-beating returns makes “eyes light up,” and the human inclination to find a good explanation for good historical results kicks in.

“In this era of big data and cheap computing power, it is easy for anyone to create a winning investment strategy in a backtest,” he cautioned in his blog post. “But investing is forward-looking and markets are adept at pricing in known information.”

Validea, a US-based investment research provider, also spoke out against the pitfalls of factor-based investing this month. In a blog post on his firm’s website, Validea President Jack Forehand noted that some advisors believe that quantitative and factor investing are “less prone to mistakes” because they rely on computers that are unhindered by emotions or biases.

But he warned that the past does not always repeat itself; factors that worked before may stop working at some point, and it could take years of waiting before investors see the results they desire.

“Factor investing works over long periods of time,” Forehand wrote. “In the short-term, the periods of underperformance can be both long and brutal.”


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