A Flawed Analysis of Factor Investing
May 25, 2018
BlackRock Inc. (BLK) estimates that by 2022, USD$3.4 trillion will be allocated under the umbrella of factor investing. Factor based investing has gained significant momentum in recent years by proving itself capable of identifying stocks which perform consistently during market and economic cyclicality. In a recent Bloomberg article titled “As Smart-Beta Spreads, Former Fan Wonders If It's Actually Dumb”, author Sarah Ponczek explores an analysis by Vincent Delaurd regarding the effectiveness of a factor ETF investment strategy. Delaurd, a global macro strategist at INTL FCStone Financial Inc, presents a very flawed case as to why multi-factor investing is suboptimal.
For his analysis, Delaured compared a “smart” index to a “dumb” one. The “smart” index was equally weighted over 5 factor-centric “smart-beta” ETFs (iShares Edge MSCI USA Quality Factor ETF (QUAL), iShares Edge MSCI USA Momentum Factor ETF (MTUM), iShares Edge MSCI USA Min Vol USA ETF (USMV), iShares Select Dividend ETF (DVY), ProShares S&P 500 Dividend Aristocrat ETF (NOBL)). The “dumb” index was market-cap weighted and composed of nearly 200 stocks from the S&P 500 that did not meet the criteria for any of these factor ETFs. A simulation was run from November 2016 to May 2018, the result of which was that the “dumb” portfolio outperformed the “smart” portfolio by more than 2%. The most significant concern with Deluared’s analysis is that it is not applicable to real-world multi-factor investing.
Factor investors typically allocate their assets based on which factors have generated the best returns in recent trading. If a factor underperforms for a period of time, it will likely receive a smaller percentage of an investor’s capital. Delaured, in his mock portfolio, allocated assets evenly across the five “smart-beta” factor ETFs without consideration of the recent performance of the factor that each ETF represents. Distributing funds evenly across a multi-factor portfolio dilutes the potency of individual outperforming factors. As such, the results Delaured’s analysis are skewed and are not indicative of how an actual multi-factor investor would invest.
The scope of Delaured’s study also limits the robustness of his thesis. An 18-month analysis provides insufficient data to determine the true effectiveness of the “smart” and “dumb” portfolios. While the 200 stocks he selected outperformed the aggregate return from the “smart-beta” ETFs, an equally weighted portfolio including those same 5 factor ETFs would have outperformed the S&P 500 by 5.27% over a 4-year time horizon.
An important point to highlight is that not all factor-based investments are designed to provide higher absolute returns compared to the market. Specialized factor investing can be geared towards objectives such as reducing volatility or providing steady income through dividends. Delaured’s analysis fails to take into account concepts such as factor-dilution, the time span of his study, and investment objectives.
At Quantamize, we believe that a multi-factor investment strategy enables investors to gain broad-market exposure and more efficiently capitalize on factor-trends in the market. Multi-factor investing takes the noise out of stock investing, and focuses on the elements (such as value, growth, and momentum) that drive the attractiveness of a stock.
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