52 هفته سرمایه گذاری و با شتاب و بزرگ در شاخص بورس های بین المللی
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|19268||2008||17 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : The Quarterly Review of Economics and Finance, Volume 48, Issue 1, February 2008, Pages 61–77
A commonly held view is that short-term momentum and long-term reversals in returns are an integrated process [e.g., Barberis, N., Shleifer, A., & Vishny, R. (1998). A model of investor sentiment. Journal of Financial Economics, 49, 307–343; Daniel, K., Hirshleifer, D., & Subrahmanyam, A. (1998). Investor psychology and security market under- and over-reaction. Journal of Finance, 53, 1839–1886; Hong, H., & Stein, J. C. (1999). A unified theory of underreaction, momentum trading, and overreaction in asset markets. Journal of Finance, 54, 2143–2184]. Recently, George and Hwang [George, T. J., & Hwang, C. (2004). The 52-week high and momentum investing. Journal of Finance, 59, 2145–2176] strikingly find that momentum and reversals are largely separate phenomena. Due to the critical importance of this finding to theoretical asset pricing and practical investment decisions, we examine this issue in international stock markets. Differently from George and Hwang (2004), we find that their conclusions may be open to question because momentum and reversals co-exist in the international stock indexes.
There is substantial domestic and international evidence of stock momentum at short horizons, the case in which stocks that have performed well (poorly) in the recent past continue to perform well (poorly) in the future.1Jegadeesh and Titman (1993), Fama and French (1996), and Grundy and Martin (2001) show that risk adjustment, unconditional or conditional, tends to deepen rather than explain momentum.2 Although Conrad and Kaul (1998) find evidence that momentum is explained by the cross-sectional dispersion in unconditional means (a proxy for expected returns),3Jegadeesh and Titman (2002) reject their claim and find that their results are driven by small sample bias.4 Contrary to Chordia and Shivakumar (2002) who find that momentum can be explained by a set of lagged macroeconomic variables, Griffin, Ji, and Martin (2003) recently find that momentum has little relation to those macro variables. There is also evidence that stock returns exhibit reversals at longer horizons.5Jegadeesh and Titman (1993) find that short-term momentum co-exists with long-term reversals. Motivated by these findings, Barberis, Shleifer, and Vishny (1998) (hereafter, “BSV”), Daniel, Hirshleifer, and Subrahmanyam (1998) (“DHS”), and Hong and Stein (1999) (“HS”) propose behavioral models in which short-run undereaction (delayed overreaction) and long-run overreaction are sequential components of the same process by which investors react to information. BSV and DHS emphasize investor cognitive biases, while HS emphasize gradual information diffusion. Hong, Lim, and Stein (2000) and Lee and Swaminathan (2000) find evidence that is consistent with momentum being caused by slow information diffusion. Jegadeesh and Titman (2001) provide further evidence on the co-existence of short-term momentum and long-term reversals, Balvers and Wu (2006) show that combined momentum-contrarian strategies outperform both pure momentum and pure contrarian strategies. Recently, George and Hwang (2004) propose a new explanation that focuses on an anchor-and-adjust bias. They argue that when good (bad) news has pushed a stock's price near (far from) the reference point (e.g. the 52-week high), investors are reluctant to bid the price higher (lower) even if the information warrants it. 6 But eventually investors correct the initial bias without overreaction. Two important empirical findings are that (1) nearness to the 52-week high dominates past returns in terms of predictive power and largely explains momentum profits, and (2) momentum profits do not reverse when past performance is measured by proximity to the 52-week high. These findings are of great importance. They challenge the behavioral models of BSV, DHS, and HS, because all these behavioral models stress that short-term momentum and long-term reversals are an integrated process. Nevertheless, over the past 20 years, financial economists have looked at stock return predictability every which way. With so much searching, it is likely, purely by chance, that someone will uncover what looks to be patterns. There are several ways of addressing the data-mining issue. Perhaps the most robust is to perform an out-of-sample test. We take this approach and examine 52-week high momentum investing in international stock indexes. To see whether momentum is due to systematic risk in international stock markets, we adjust risk by the ICAPM, the two-factor model of Fama and French (1998), and the multi-factor models that explicitly take exchange-rate risk into account. Empirically, we find that the two-factor model of Fama and French (1998) performs relatively better. This probably is due to that the global market and value factors may already contain the information of exchange-rate risk. Thus, our discussion will mainly focus on the results based on the two-factor model. Nevertheless, our main empirical findings in this paper are generally robust to all benchmark models we use. Consistent with George and Hwang (2004), we find that nearness to the 52-week high dominates past returns in terms of predictive power and largely explains momentum profits. That is, as soon as we control the effects of nearness to the 52-week high, risk-adjusted momentum profits based on past returns generally become insignificant. Outside of January, the mean risk-adjusted momentum profit based on past returns is 0.59% per month with a t-statistics of 3.14; however, as soon as the effects of nearness to the 52-week high are taken into account, it decrease to 0.21% per month with a t-statistics of only 1.13. The stock and currency transaction costs for the momentum strategies are substantial but erase 1/2 to 2/3 of the risk-adjusted profits. Thus, momentum strategies are profitable even after we adjust for risk and transaction costs. The dominance of nearness to the 52-week high supports the notion that the anchor-and-adjust bias may be a better description of investor behavior. However, different from George and Hwang (2004), we find that short-run momentum co-exists with long-run reversals in international stock indexes even after risk adjustment. This is true for both the strategy based on past returns and the strategy based on nearness to the 52-week high. Hence, the notion that momentum and reversals are separate phenomena may be open to question. Our results suggest that investors may still overreact when they correct their initial bias. Intuitively, it is also unlikely that investors only underreact to information, but do not overreact. The remainder of the paper is organized as follows: Section 2 describes the data and the empirical methodology. Section 3 investigates the predictive power of the 52-week high and past returns. Section 4 examines momentum and reversals. Section 5 concludes the manuscript.
نتیجه گیری انگلیسی
Market efficiency implies that stock prices followrandomwalks, and returns are unpredictable. A voluminous literature has developed to test this hypothesis for its important implications for many of the paradigms used in financial economics. Contrary to the early supporting evidence surveyed in Fama (1970), there is evidence that stock prices do not follow random walks and returns are predictable. Jegadeesh and Titman (1993) document short-run momentum in stock returns, while DeBondt and Thaler (1985) discover long-run reversals. Motivated by these findings, Barberis et al. (1998), Daniel et al. (1998), and Hong and Stein (1999) have developed behavioral models to account for both the short-term momentum and long-term reversals. Recently, George andHwang (2004) find that momentum is largely explained by an anchor-andadjust bias where the anchor is the 52-week high of the stock price, and momentum and reversals are largely separate phenomena. The implication of these findings is of great importance, because they indicate a model with an anchor-and-adjust bias may be more tractable to describe investor behavior and investors do not overreact when they adjust. To see whether their findings are sample specific, we perform similar tests as George andHwang (2004) with the MSCI county indexes. The behavioral models are usually driven by firm-specific risk, while this paper uses the country portfolios with firm-specific risk generally eliminated. However, it is important to note that although a country portfolio does not have firm-specific risk, it still has country-specific idiosyncratic risk. Therefore, the basic logic of the behavioral models may still apply.12 For instance, when a country’s market has experienced extreme movements or is near (far from) its 52-week high (while the global market has been quite), there may be more uncertainty regarding whether or not this market has fully incorporated information. As a result, investor underreaction may be particularly strong. Empirically, we find that international momentum strategies are profitable even after risk and transaction-cost adjustments. Furthermore, although nearness to the 52-week also dominates past returns in terms of predictive power in international stock markets, reversals do occur to both the momentum profits from the JT strategy and those from the GH strategy. Taken together, these findings suggest that an anchor-and-adjust bias may be a better description of investor behavior, but investors do overreact when they adjust. Intuitively, it is also unlikely that investors only underreact to information, but do not overreact.