PGIM Quantitative Solutions
May 10, 2019
PGIM Quantitative Solutions seeks to help solve complex investment problems with custom systematic solutions across the risk/return spectrum.

A Multi-Factor Strategy for Index Enhancement

One of the most powerful biases that drives stock behavior is also one of the most difficult to capture— investors’ tendency to overpay for stocks that have the possibility (however remote) of a very large payoff. In statistical terms, these stocks are described as having high positive “skew.” More popularly, they can be thought of as “lottery” stocks. “Safety” stocks, those with relatively small chance of a very large loss, display a similar, though not identical, return pattern and also fall into the positive skew group. For both lottery stocks and safety stocks, disproportionately higher expectations for future returns translate to higher current valuations and, consequently, lower future stock performance. This study proposes a multi-factor approach to outperforming an index by avoiding both of these types of stocks. We focus on a combination of three factors —value, volatility and a specific type of quality (profitability) — that in our experience characterize firms with positively skewed return expectations.

Key Findings

  • Contrary to what the low-volatility literature would suggest, we show that it is not necessary to avoid all high-volatility stocks, only those that are expensive and less profitable. Similarly, not all low-volatility stocks outperform. Indeed, those that are expensive relative to their profitability actually underperform the market.
     
  • By applying our multi-factor elimination method to benchmark constituents and then equal weighting those that remain, we are able to create portfolios that outperform all the universes sampled (Russell 1000®, S&P 500, Russell 2000® Value, Russell 2000® Growth, and MSCI EAFE), with average annual excess of returns of 2–3.6% and risk levels comparable to their benchmarks or lower. Alpha is also positive against the equal-weighted versions of the indexes, showing that outperformance is incremental to the small-cap bias inherent in equal weighting.
     
  • The composition of the portfolios generally runs countercyclical to market environments, avoiding more lottery stocks when investor sentiment is high and more safety stocks when sentiment is low, tilting away from sectors or industries generating a lot of investor attention.

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