سودآوری استراتژی های سرمایه گذاری مبتنی بر بازگشت و حجم در بازار سهام چین
کد مقاله | سال انتشار | تعداد صفحات مقاله انگلیسی |
---|---|---|
9787 | 2004 | 24 صفحه PDF |
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Pacific-Basin Finance Journal, Volume 12, Issue 5, November 2004, Pages 541–564
چکیده انگلیسی
We examine the informational role of the interaction between past returns and past trading volume in the prediction of cross-sectional returns over intermediate horizons in China's stock market. Our results show that low-volume stocks outperform high-volume stocks, volume discounts are more pronounced for past winners than for past losers, low-volume stocks experience return continuations, and high-volume winners exhibit return reversals. Our results are robust to risk adjustments relative to Fama and French's three-factor model, and to stock exchange as well as large stock sub-samples. Our findings are not entirely consistent with the literature, which are likely to result from the market characteristics, in particular, the short-sales prohibition and the dominance of individual investors in the market.
مقدمه انگلیسی
Academics and practitioners have long recognized that trading volume provides valuable information about future market movements. A large body of finance literature has shown that the relation between trading volume and expected stock returns is in general negative Amihud and Mendelson, 1986, Conrad et al., 1994, Datar et al., 1998 and Brennan et al., 1998, although there is little agreement on how the relation should be interpreted. Amihud and Mendelson (1986), Campbell et al. (1993), and Brennan et al. (1998) attribute the volume–return relation to market microstructure effects, whereas some researchers suggest that this relation is consistent with the behavioral finance theories (e.g., Barberis et al., 1998, Hong and Stein, 1999 and Baker and Stein, 2002). Stock prices and trading volume are jointly determined by the same market dynamics. However, the informational role of the interaction between past prices and trading volume in the prediction of future price changes has not been well understood. A recent study of Lee and Swaminathan (2000) provides evidence on the role of the interaction between intermediate-horizon return predictability and trading volume in the U.S. markets, and document that high- (low-) volume stocks earn lower (higher) returns, momentum strategies are more profitable for high-volume stocks than for low-volume stocks, and past trading volume predicts both the magnitude and the persistence of future price momentum over longer horizons. However, their intriguing findings do not appear to fit into any existing theoretical framework. A better understanding of these issues could benefit from more out-of-sample evidence. This paper uses a sample of all A-shares traded on the Shanghai Stock Exchange (SHSE) and Shenzhen Stock Exchange (SZSE) over the July 1994–December 2000 interval, and examines the interaction between return predictability and trading volume over intermediate horizons (3- to 12-month). A study of China's stock market is motivated by the following considerations. First, the market is usually independent of the U.S. stock market, and thus provides an adequate out-of-sample test of the results of Lee and Swaminathan (2000). Second, China's stock market has experienced rapid expansion, and is ranked the second largest in Asia (after Japan) in about a decade after formal stock exchanges were set up; however, little is known about its stock price behavior. With China's entry into WTO, its stock market increasingly attracts foreign investors' attention because of China's fast development and enormous growth opportunities. An understanding of stock pricing in China's market becomes important in particular for global institutional investors. Lastly, several market characteristics, for example, the short-sales prohibition and the dominance of individual investors, make the study of China's stock market illuminating with regard to discriminating between competing explanations for the volume–return relations. We find that low-volume stocks outperform high-volume stocks, consistent with the liquidity premium hypothesis of Amihud and Mendelson (1986), Datar et al. (1998), Brennan et al. (1998). However, volume discounts are larger in magnitude for past winners than for past losers, which differ from the finding of Lee and Swaminathan (2000) that shows the opposite result from the U.S. data.1 We also find that low-volume stocks experience return continuations. In contrast, high-volume winners exhibit strong return reversals, rendering a momentum strategy unprofitable for high-volume stocks. This result is contrasted with the Lee and Swaminathan's finding that high-volume stocks experience stronger return momentum than low-volume stocks. Our results hold true after risk adjustments relative to Fama and French's (1993) three-factor model, and are robust to stock exchange as well as large stock sub-samples. Our results on the interaction between return predictability and trading volume tend to be consistent with the behavioral finance theories (e.g., Barberis et al., 1998, Hong and Stein, 1999 and Baker and Stein, 2002). Both Barberis et al. (1998) and Hong and Stein (1999) attribute intermediate-horizon return continuations to market underreaction, although the causes of underreaction differ in these two studies. The former contends that the underreaction arises because the representative investors do not update firm-specific public information sufficiently, while the latter attributes the underreaction to insufficient diffusion of information across news watchers. Small trading volume is arguably a proxy for insufficient updating or diffusion of information, and therefore, momentum effects are expected to exist in low-volume stocks but not in high-volume stocks. Baker and Stein (2002) show that trading volume is also a sentiment indicator of irrational investors in the presence of short-sales constraints. A large volume for winner stocks indicates that irrational investors dominate the market, driving stock prices above the fundamental value. However, a large volume for loser stocks is unlikely to result from irrational investors' trading due to short-sales constraints. This provides an explanation for our results that high-volume losers exhibit price continuations, whereas high-volume winners experience price reversals. The characteristics of China's stock market, in particular, the short-sales prohibition and the dominance of individual investors, make the behavioral explanations for our results more relevant. Our study adds to the literature by providing initial evidence on the interaction between intermediate-horizon return predictability and trading volume in China's stock market, and offers an out-of-sample test of the results of Lee and Swaminathan (2000). The out-of-sample evidence from independent samples is beneficial to the inference of the universality of price behavior regularities and the development of robust asset pricing theory. The remainder of this article is organized as follows. Section 2 provides an overview of China's stock market. Section 3 describes the sample and the methodology. Section 4 presents the empirical results. Brief concluding remarks are provided in Section 5.
نتیجه گیری انگلیسی
In this paper, we examine the role of the interaction between past returns and past trading volume in the prediction of cross-sectional returns over intermediate horizons in the emerging China's stock market. We document strong evidence of predictable patterns of cross-sectional returns. In particular, we find that low-volume stocks outperform high-volume stocks, consistent with the liquidity premium hypothesis (e.g., Amihud and Mendelson, 1986, Datar et al., 1998 and Brennan et al., 1998). Moreover, the difference in returns between low- and high-volume stocks is larger for past winners than for past losers. We also find that low-volume stocks experience significant return continuations, whereas high-volume winners experience strong return reversals. Thus, significant momentum profits present in low-volume stocks but not in high-volume stocks. These results hold true after risk adjustments relative to the three-factor model, and are robust to stock exchange as well as large stock sub-samples. Our results are not entirely consistent with the literature (e.g., Lee and Swaminathan, 2000), but appear to be in line with the predictions of behavioral finance models (e.g., Barberis et al., 1998, Hong and Stein, 1999 and Baker and Stein, 2002). The characteristics of China's stock market, for example, the short-sales prohibition and the dominance of unsophisticated individual investors, imply that China's stock market is more prone to behavioral concerns, greatly influencing the return–volume dynamics. This in turn results in the difference in the findings between this study and the literature. Our findings suggest that the informational content of past prices and past trading volume for future market movements can be market specific. Therefore, additional out-of-sample evidence is certainly beneficial for academics to better understand volume–return dynamics in asset markets. Our results also have implications for practical investment strategies and market efficiency in the emerging market. With China's entry into WTO, China's stock market attracts more and more foreign investors' attention. Thus, understanding the behavior of stock prices becomes increasingly important, in particular, for global institutional investors.