Currency devaluations, failed economic plans, regulatory changes, coups and other national financial “shocks” are notoriously difficult to predict and may have disasterous consequences for global portfolios. Indeed, these characteristics often define the difference in investment in the capital markets of developed and emerging economies. Research on emerging markets has suggested three market features: high average returns, high volatility and low correlations both across the emerging markets and with developed markets.
Indeed, the lesson of volatility was learned the hard way by many investors in December 1994 when the Mexican stock market began a fall that would reduce equity value in U. S. dollars by 80% over the next three months. But, we have learned far more about these fledgling markets. First, we need to be careful in interpreting the average performance of these markets. Harvey (1995) points out that the International Finance Corporation (IFC) backfilled some of the index data resulting in a survivorship bias in the average returns.
Second, the countries that are currently chosen by the IFC are the ones that have a proven track record. This selection of winners induces another type of selection bias. Third, Goetzmann and Jorion (1996) detail a re-emerging market bias. Some markets, like Argentina, have a long history beginning in the last half of the 19th century. At one point in the 1920’s, Argentina’s market capitalization exceeded that of the U. K. However, this market submerged. To sample returns from 1976 (as the IFC does), only measures the “re-emergence” period.
A longer horizon mean, in this case, would be lower than the one calculated from 1976. This insight is consistent with the out-of-sample portfolio simulations carried out by Harvey (1993) indicating that the performance of the dynamic strategy was affect by the initial five years. Fourth, exposure as measured by the IFC is not necessarily attainable for world investor’s [see Bekart and Urias (1996)]. Second, we have learned that the emerging market returns are more predictable than developed market returns.
Harvey (1995) details much higher explanatory power for emerging equity markets than developed market returns. The sources of this predictability could be time-varying risk exposures and/or time-varying risk premiums, such as in Ferson and Harvey’s (1991, 1993) study of U. S. and international markets. The predictability could also be induced by fundamental inefficiencies. In many countries, the predictability is of a remarkably simple form: autocorrelation. For example, Harvey (1995) details 0. 25 autocorrelation coefficient for Mexico in a sample that ends in June 1992.
An investor who followed a strategy based on autocorrelation in this country would have lost 35% like everyone else in December 1994. However, the investor would have been completely out of the market in the next three months (or short if possible). Momentum appears to be important for many of these markets. Third, we have learned that the structure of the returns distribution is potentially unstable. Ghysels and Garcia (1996) reject the structural stability of the prediction regressions presented in Harvey (1995).
These regressions allow for the influence of both local and world information. Bekaert and Harvey (1995, 1996) present a model which explains the results of Ghysels and Garcia. The Bekaert and Harvey model allows for the relative influence of local and world information to change through time. They hypothesize that as a market becomes more “integrated” into world capital markets, the world information becomes relatively more important. Bekaert and Harvey (1996) find that the changing relative importance of world information also influences volatility.
Fourth, the Bekaert and Harvey (1996) framework suggests the increasing influence of world factors on emerging expected returns will manifest itself in increased correlation with developed market benchmarks. The goal of this paper is to explore three aspects of the emerging markets data. First, we examine the behaviorial characteristics beyond the volatility – the skewness and kurtosis. Second, the paper explores the relation between risk variables and expected returns.
Harvey (1995) and Bekaert (1995) find that higher betas (from a capital asset pricing framework) are associated with lower expected returns. This is the opposite from what we would expect from theory, however, it is consistent with these markets being segmented. That is, the countries with the higher betas are the ones that are more likely integrated, hence have lower expected returns relative to the segmented countries. Third, we examine the time-varying correlation of these markets with developed markets.
Solnik and Longin (1994) and Erb, Harvey and Viskanta (1995) detail how correlations change through time in developed markets. Harvey (1995) and Bekaert and Harvey (1996) show some evidence that correlations are changing in emerging markets. Finally, we examine what is important for explaining both the cross-section of expected returns and volatility in emerging markets. Following Erb, Harvey and Viskanta (1996), we try to link political, economic, and financial risk, as well as, a number of fundamental attributes to explain the cross-sectional behavior of emerging market returns.