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References

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1

A version of this paper is forthcoming in the Journal of Finance. The author is grateful to Will Goetzmann, Mark Klock, Heidi Willmann Richards, René Stulz, an anonymous referee, and seminar participants at the Federal Reserve Board for comments, and to Morgan Stanley and Co. for providing some of the data used in this study.

2

In addition, this period was characterized by regulations on brokerage commissions in some countries which increased the costs of trading, and by the absence of index futures contracts which might have effectively prevented short–selling.

3

Monte Carlo simulations indicate that when all countries have similar expected rates of return, the contrarian portfolio has a zero expected return: that is, there is no bias corresponding to the bias in estimated autocorrelations.

4

With the exception of Belgium and Singapore/Malaysia which were not available, the 16 countries include all those for which the MSCI indices are calculated from December 1969.

5

Using estimates of GDP for the 16 countries, I have examined both the average GDP growth rates of the return–ranked portfolios and the average returns for portfolios formed based on GDP growth rates. The results (available on request) suggest that the short–term momentum in returns is not associated with GDP outcomes. More surprisingly, the ranking period return differentials do not appear to be correlated with GDP growth rates at any horizon, though this result may be due to the poor quality of quarterly GDP data for some of the countries or to the need to decompose GDP changes into expected and unexpected components.

6

If the Newey–West correction is instead used to estimate significance levels, the significance levels are less than 1 and 2 percent, respectively.

7

Dumas and Solnik (1995) and Harvey, Solnik and Zhou (1994) provide evidence that exchange rate factors affect the pricing of bonds, but perhaps not stocks. Harvey (1995) shows that national stock market returns are typically correlated with a dollar exchange rate variable, though the sign of the risk exposure often depends on the currency of measurement.

8

To test for possible differences in other risk factors, in other regressions I have included three other risk factors suggested by Harvey, Solnik and Zhou (1994)—the change in the price of oil, G–7 inflation, and the change in G–7 industrial production—but these are not significant.

9

For example, using the PI index of Demirgüç–Kunt and Levine (1995) which is calculated using data from 1986–93 for 41 mature and emerging markets and is normally distributed around zero, the average development indices for the larger and smaller markets are 1.07 and 0.10, respectively.

10

Richards (1996) shows that the tendency for smaller markets to have larger ranking and test–period return differentials holds also for emerging markets which tend to be smaller and less open than the markets studied here.

11

Moreover, it seems plausible that even “prudent” institutional investors (as opposed to “speculative” ones) might tend to focus their investments in countries with high recent returns, while shying away from countries that have recently performed poorly. In particular, an investment in a recent winner may appear prudent regardless of its subsequent outcome, while an investment in a recent loser may appear foolhardy if it should subsequently perform badly (see also Lakoniskok, Shleifer and Vishny (1994) and Shefrin and Statman (1994)).

Winner-Loser Reversals in National Stock Market Indices: Can they Be Explained?
Author: Mr. Anthony J. Richards