Swedroe: Factors & Emerging Markets

August 31, 2018

There have been so many factors identified in the academic literature that John Cochrane, in his 2011 presidential address to the American Finance Association, famously described it as a factor “zoo.” With 600 or more having been “discovered,” how can investors determine which factors are suitable for investment?

In our book, “Your Complete Guide to Factor-Based Investing,” Andrew Berkin and I offered the following criteria, which reduced the proverbial factor zoo to not much more than a handful of exhibits in the equity section.

Specifically, we argue that a factor must be persistent across long periods of time and economic regimes, pervasive across the globe and even asset classes, implementable, have intuitive or risk-based explanations for why an investor should expect the premium to exist going forward, and be robust to various definitions.

Meeting these criteria minimizes, if not completely eliminates, risks of data mining. A good test of the pervasiveness criterion is to determine whether a factor exists not only in the developed world, but also in emerging markets.

Global Factors Or Not?

Yigit Atilgan, K. Ozgur Demirtas and A. Doruk Gunaydin contribute to the literature on factor-based investing with their August 2018 study, “The Cross-Section of Equity Returns in Emerging Markets.”

Their data set covers 27 emerging market countries over the period 1988 to 2014, though there are some markets for which data is available for a shorter sample period (such as Russia and Vietnam, whose return series commence in 1995 and 2006, respectively).

Following is a summary of the authors’ main findings:

  • Univariate, equal-weighted portfolio analyses that sort stocks into deciles based on various firm-specific attributes reveal that the low-beta, firm size, book-to-market ratio, momentum and illiquidity factors also are observed in emerging market stocks.
  • Using value-weighted portfolios, the size, value and momentum anomalies remain statistically significant.
  • The book-to-market ratio and momentum anomalies survive after controlling for firm size.
  • Return momentum over the prior year has a significantly positive relation with one-month-ahead returns.
  • The anomaly of the demand for lottery stocks, which have a negative premium and the low probability of a very high return, observed in U.S. equities has the opposite relationship with expected returns in emerging market equities (such stocks have a positive premium).
  • Consistent with the low-beta anomaly observed in U.S. stocks, the equal-weighted average excess return in emerging markets is relatively flat across the market beta deciles, except for a sharp drop from the ninth decile to 10th decile portfolios. However, the anomaly is no longer significant when using value-weighted returns.
  • Moving across the firm size deciles reveals that larger firms have lower expected returns, although the pattern is not entirely uniform. The return and alphas to the zero-cost portfolio formed based on firm size vary between -0.81% and -1.21% with significantly negative t-statistics.
  • Equities with higher book-to-market ratios demand higher expected returns. The monthly return to the zero-cost portfolio formed based on book-to-market ratio is as high as 1.67% with a t-statistic of 3.95.
  • The momentum anomaly also manifests itself across deciles, with winners over the prior year (excluding the last month) having a higher one-month-ahead return, 2.40% with a t-statistic of 4.37, compared to the losers.

Find your next ETF

CLEAR FILTER