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Claessens, S., S. Dasgupta, and J. Glen (1995), “Return Behavior in Emerging Stock Markets,” The World Bank Economic Review, vol.9 no.1, pp. 131–151.
Claessens, S., and M. Rhee (1993), “The Effect of Equity Barriers on Foreign Investment in Developing Countries,” National Bureau of Economic Research Working Paper No. 4579, December.
De Long, B., A. Shleifer, L. Summers, and R. Waldmann (1990), “Positive Feedback Investment Strategies and Destabilizing Rational Speculation,” Journal of Finance, vol. XLV, no.2, June.
Feldman, R.A. and M.S. Kumar (1994) Emerging Equity Markets: Growth. Benefits, and Policy Concerns. IMF Paper on Policy Analysis and Assessment (PPAA/94/7), March.
Lo, A. and A.C. MacKinlay (1988), “Stock Market Prices Do Not Follow Random Walks: Evidence from a Simple Specification Test,” Review of Financial Studies, vol.1, no.1, pp.41–66.
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I am grateful to John Anderson, Jahangir Aziz, Elaine Buckberg, and Steven Dunaway for helpful discussions and comments on earlier drafts. The views expressed in this paper are my own and do not necessarily reflect those of the International Monetary Fund.
Comprehensive and consistent estimates of institutional investor equity holdings in developing country stock markets have not yet been constructed. However, indirect measures show rapid increases in institutional investor holdings of developing country equities beginning in the early 1990’s. Net equity purchases by emerging market mutual funds are estimated to have increased by several times beginning in 1992 (see Chapter II of IMF (1995a)). Similarly, emerging market capitalization as a share of world capitalization nearly doubled between 1990 and 1993, corresponding to a sharp increase in industrialized country investment flows into emerging markets (see Chapter IV of IMF (1995b)).
While similar views were reported in a wide range of financial publications, references in this paper are taken from various issues of The Economist. The Financial Times. The Wall Street Journal, and Emerging Markets Week.
See Bekaert and Urias (1995) for a partial discussion of the large literature on the diversification benefits of emerging markets. A good example of the backward-looking nature typical of this analysis appears in a recent Financial Times column (December 4, 1995). The analyst argues that:
Despite the ups and downs of emerging markets there is a strong theoretical case for including them in global portfolios based on the likelihood of a worthwhile return for the risk incurred. An optimum portfolio of 80 percent of the FT/S&P World Index plus 20 percent of the IFCII [emerging markets index] should return about two-and-a-half percent more a year than the World Index, but with slightly lower volatility.
It would not be a gross exaggeration to characterize investors who act on this sort of advice as “trend chasers.”
Given the difficulties in assessing the economic gains from trade liberalization, privatization, and other efficiency enhancing policies adopted by many of these countries at the time, it would not be surprising if institutional investors looked to past performance for evidence of future prospects. Krugman (1995) goes one step further in arguing that in light of the uncertainty of the benefits of these policies, the speculative bubble in financial markets reinforced (and was in turn reinforced by) a similar “bubble” in policy making circles. According to this process, policy makers rallied around the “Washington Consensus” towards liberalization because markets were rewarding these policies so spectacularly, and markets were willing to supply so much capital because they saw as unstoppable the move toward policy reform.
For a summary discussion of asset price bubbles and noise traders, see Chapter V of IMF (1995b). For a theoretical description of positive feedback trading, see De Long, et.al. (1990). See also Shleifer and Summers (1990), for broader applications of the noise trader approach to finance.
This is generally known as the “Random Walk Hypothesis,” which itself is a variant of the “weak form” of the Efficient Market Hypothesis (see Fama, 1991). According to weak-form efficiency, a market is efficient if investors cannot earn abnormal profits on the basis of an analysis of past price patterns. Under certain theoretical conditions, price deviations from the random walk do not by themselves imply market inefficiency, but can result from factors such as shifting risk premia which are consistent with efficient markets. As argued in Section II.2, however, the measured deviations from the random walk for emerging markets as a whole appear many times larger than can be reasonably accounted for by shifts in the variance of risk premia.
Variance ratios of less than one reflect negative autocorrelation of excess returns. The variance ratio has several properties which make it particularly desirable for testing the presence of bubbles or other asset market inefficiencies. Since the variance ratio requires only a minimum of structural assumptions, it is robust to many specification errors common to bubbles tests. It does not, for example, require that the variance of an asset’s rate of return be stable over time--that is, estimates of the standard errors of the variance ratio are heteroskedasticity-robust. By focusing on the appropriate behavior of an asset’s price rather than the appropriate level, the variance ratio avoids the specification errors occurring in tests which depend on correctly identifying and measuring an asset’s fundamentals. The variance ratio test is also robust to changes or asymmetries in the structure of autocorrelation, which are particularly likely if bubbles are present. This property gives the test more power to detect erratic serial dependence than tests which require structurally stable autocorrelation. See Lo and MacKinlay (1988) for a complete discussion of the variance ratio test.
Chart 2 shows the variance ratio for the composite index recalculated over different holding periods, from 2-weeks to 32-weeks. The chart shows that the variance ratio in the early sample period (1989-91) does not differ statistically from one for any of the holding periods. In contrast, the variance ratio for the later sample period (1992-95) is significantly different from one for all holding periods. Since the results are robust to the length of the holding period, only the results for holding periods of 16 weeks are presented in full detail.
Moreover, this increase is many times more than can be reasonably accounted for solely by an increase in the variance of the risk premium on emerging market stocks. Even in the extreme, where deviations from a random walk are caused entirely by shifting risk premia, the variance of the risk premium on emerging market stocks based on uncertainty about long term prospects would have to have increased several times between the two periods in order to produce such a large shift in the variance ratio observed for emerging markets as a whole. One would expect such an increase to be reflected, at least partially, in the variance of other indicators of country risk. Indicators such as secondary market prices for emerging market debt claims, for example, do not appear to have experienced major increases in variance.
Lo and MacKinlay (1988) found positive statistically significant auto correlation on overall U.S. stock market index returns and negative (although insignificant) autocorrelation on the returns of individual securities. Claessens et al (1995) find that for emerging markets, the means of the first order autocorrelations for individual stocks were smaller than the first order correlations of the economy-wide indexes. From this, they conclude that “the portfolio-formation process influenced the higher degree of predictability found for the index and portfolio rates of return.”
In the words of one analyst, “most investment managers regard emerging markets like venture capital holdings--you have to spread your money around because you can’t be sure which ones will do well and which ones will collapse.”
The predominance of funds using managers who employ “balanced expertise,” according to which a manager spreads his portfolio over several asset classes, is said to arise because of the difficulty in comparing the performance of a “specialist” in one asset class with the performance of specialists in another classes. In contrast, it is relatively easy to compare the performance of a balanced manager with the performance of other balanced managers. As a result, however, balanced expertise is said to involve a kind of herd instinct, where no manager strays too far from the mainstream asset allocation for fear of producing results below the median.
Claessens and Rhee (1993), for example, find that for most of the developing country markets they examined, barriers to access by foreigners had a negative impact on the price-earnings ratio of stocks.
This final result should be treated with caution. As the sample period is subdivided, one increasingly runs the risk of understating the degree of auto-correlation of returns. To see this, consider the extreme example that total returns are abnormally high throughout the first sub-period and abnormally low in the second. The variance ratio for the period as a whole would be large and positive, while the ratios for each sub-period could be equal to one. The reason is that the variance ratio for each sub-period calculates the persistence of abnormal returns relative to the average return for the sub-period. In this case, the auto-correlation of returns within each sub-period might be low, while the auto-correlation for the whole period might be high. This may explain why in the case of Mexico, the variance ratios do not differ significantly from one for either sub-period, while at the same time being significantly greater than one for the period 1992-95 as a whole.