آنالیز تجربی از رفتار گله ای در بازارهای سهام جهانی
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|16478||2010||11 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Banking & Finance, Volume 34, Issue 8, August 2010, Pages 1911–1921
This paper examines herding behavior in global markets. By applying daily data for 18 countries from May 25, 1988, through April 24, 2009, we find evidence of herding in advanced stock markets (except the US) and in Asian markets. No evidence of herding is found in Latin American markets. Evidence suggests that stock return dispersions in the US play a significant role in explaining the non-US market’s herding activity. With the exceptions of the US and Latin American markets, herding is present in both up and down markets, although herding asymmetry is more profound in Asian markets during rising markets. Evidence suggests that crisis triggers herding activity in the crisis country of origin and then produces a contagion effect, which spreads the crisis to neighboring countries. During crisis periods, we find supportive evidence for herding formation in the US and Latin American markets.
In the behavioral finance literature, herding is often used to describe the correlation in trades resulting from interactions between investors. This behavior is considered to be rational for less sophisticated investors, who attempt to mimic financial gurus or follow the activities of successful investors, since using their own information/knowledge would incur a higher cost.1 The consequence of this herding behavior is, as Nofsinger and Sias (1999) note, “a group of investors trading in the same direction over a period of time”. Empirically, this may lead to observed behavior patterns that are correlated across individuals and that bring about systematic, erroneous decision-making by entire populations (Bikhchandani et al., 1992). Thus, to achieve the same degree of diversification, investors need a larger selection of securities that constitute a lower degree of correlation. In addition, if market participants tend to herd around the market consensus, investors’ trading behavior can cause asset prices to deviate from economic fundamentals. As a result, assets are not appropriately priced. Empirical investigations of herding behavior in financial markets have branched into two paths.2 The first path focuses on co-movement behavior based on the measure of dynamic correlations. For instance, in their tests for financial contagion, Corsetti et al. (2005) find “some contagion, some interdependence” among Asian stock markets. Chiang et al. (2007) report that the contagion effect took place during the early stage of the Asian financial crisis and that herding behavior dominated the later stage of the crisis, as the bad news became widespread and investors realized the full impact of the crisis. Boyer et al. (2006) discover that in emerging stock markets, there is greater co-movement during high-volatility periods, suggesting that crises that spread through the asset holdings of international investors are mainly due to contagion rather than to changes in fundamentals.3 The second path for examining herding behavior focuses on the cross-sectional correlation dispersion in stock returns in response to excessive changes in market conditions. By observing information asymmetry in emerging markets, researchers anticipate that investors in these markets are more likely to demonstrate herding behavior. In their study of international herding behavior, Chang et al. (2000) find significant evidence of herding in South Korea and Taiwan and partial evidence of herding in Japan. However, there is no evidence of herding on the part of market participants in the US and Hong Kong. By focusing on Hong Kong’s stocks, Zhou and Lai (2009) discover that herding activity in Hong Kong’s market tends to be more prevalent with small stocks and that investors are more likely to herd when selling rather than buying stocks. Turing to the Chinese markets, Demirer and Kutan (2006) investigate whether investors in Chinese markets, in making their investment decisions, are following market consensus rather than private information during periods of market stress. Their study reveals no evidence of herding formation, suggesting that market participants in Chinese stock markets make investment choices rationally. Yet, in a recent study of Chinese stock markets, Tan et al. (2008) report that herding occurs under both rising and falling market conditions and is especially present in A-share investors.4 Thus, the evidence from the studies cited above shows mixed results and that most herding behavior is present in emerging markets and not in advanced markets. Although the above-mentioned studies have made contributions to describing herding behavior in various aggregate markets, they are mainly restricted to a single market boundary. No attempts have been made to examine herding behavior across national borders. The empirical results based on such a setting are likely to produce two drawbacks. First, from an econometric point of view, there is the potential for bias in the OLS estimate when important variables are excluded. Sometimes, it could give rise to wrong signs (Kennedy, 2008, p. 368). Second, the empirical evidence derived from a few selected countries essentially shows local behavior, and hence, the testing results do not necessarily reflect a broader test for the validation of a global phenomenon. Recent experience suggests that financial shocks do not stand alone in a country or region. Forbes and Rigobon (2002) find that financial markets are somehow interdependent during the high-volatility period. Chiang et al. (2007) find significant evidence of comovements among various stock markets during the financial turmoil at the later stage of the Asian crisis. In their study of cross-country variations in market-level stock volatility, Bekaert and Harvey (1997) report that a higher return dispersion is associated with higher market volatility for the more developed markets. They suggest that dispersions may reflect the magnitude of firm-/industry-level information flows for these markets. Motivated by these empirical studies, this paper examines herding behavior by testing the cross-sectional stock return dispersions in relation to a set of explanatory variables, including absolute domestic stock returns, excess domestic market conditions, and foreign market influences. This paper differs from previous research in the following respects. First, the data set used by Chang et al., 2000, Demirer and Kutan, 2006, Tan et al., 2008 and Zhou and Lai, 2009 in their investigation of herding behavior is confined to a relatively small set of observations, and their studies are restricted to a few local markets. The current study contains 18 economic units categorized into advanced, Latin American, and Asian markets. Second, we identify the significance of the US market in examining local market herding behavior; the evidence shows that in the majority of cases, investors in each national market are herding around the US market. Third, employing a larger data set allows us to examine different investing behavior associated with different regions. Specifically, we find evidence of herding behavior occurring in countries classified as advanced markets and in Asian markets. However, we find less supportive evidence for herding behavior in the four Latin American markets. Fourth, we investigate the role of financial crisis in testing herding behavior. Specifically, consistent with common intuition, herding behavior appears to be more apparent during the period in which the crisis occurs. In particular, we find herding in the Mexican and Argentine stock markets, respectively, when the 1994 Mexican and 1999 Argentine crises took place. Otherwise, no evidence of herding is found in these Latin American countries over the entire sample period. The remainder of this paper is organized as follows. Section 2 presents the estimation model for examining herding behavior. Section 3 describes the data. Section 4 reports the empirical evidence of herding behavior and estimates the effect of the US market. Section 5 examines herding behavior under different market conditions. Section 6 contains a summary and conclusions.
نتیجه گیری انگلیسی
This study examines investors’ herding activity for 18 countries divided into three groups: the advanced stock markets (Australia, France, Germany, Hong Kong, Japan, the United Kingdom, and the United States); Latin American markets (Argentina, Brazil, Chile, and Mexico); and Asian markets (China, South Korea, Taiwan, Indonesia, Malaysia, Singapore, and Thailand). By applying daily data from May 25, 1988, through April 24, 2009, for industrial stock returns, this study finds significant evidence to support the existence of herding in each national market except the US and Latin America. This result stands in contrast to the earlier literature that shows no herding in advanced markets (Chang et al. 2000) and in Chinese markets (Demirer and Kutan, 2006). This paper pioneers research by extending the investigation of herding behavior from domestic markets to global markets. In particular, we find significant evidence that most investors herd with the US market in addition to their domestic markets. Thus, the traditional approach of excluding foreign markets in testing herding behavior is likely to produce biased estimates. Interestingly, this study finds that most market participants investing in the Latin American markets herd with the US market, not their own markets. While testing the performance of sub-samples, we find that with the exception of the US and Latin American markets, herding is present in both up and down markets, although herding asymmetry is more profound in Asian markets during rising markets. By examining the data from financial crises, we find that crisis triggers herding activity in the crisis country of origin and then produces a contagion effect, which spreads the crisis to neighboring countries. The evidence also reveals herding formation in the US and Latin American markets during crisis periods.