اثرات متقابل کشور در رفتار گله ای: شواهدی از چهار بازار جنوب اروپا
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|14210||2011||18 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of International Financial Markets, Institutions and Money, , Volume 21, Issue 3, July 2011, Pages 443-460
This study provides comprehensive evidence testing for the existence of herding effects in the Portuguese, Italian, Spanish and Greek market, constructing a survivor-bias-free dataset of daily stock returns during the period January 1998–December 2008. Moreover, it examines the potential asymmetries of herding effects with respect to the sign of the market return, trading activity and volatility. A novel feature of this study, with implications for financial stability in the Eurozone and international portfolio diversification, is to examine whether the cross-sectional dispersion of returns in one market is affected by the cross-sectional dispersion of returns in the rest three markets. Finally, it tests whether herding effects became more intense during the recent global financial crisis of 2007–2008.
The recent global financial crisis clearly demonstrated that market prices may considerably deviate from fundamental values for prolonged periods. Liquidity constraints, asymmetric information, limits to arbitrage and other frictions are the commonly cited culprits for this phenomenon (see Shleifer, 2000 and Brunnermeier, 2001 for an introduction). These features pose a constant threat to financial stability exposing market participants and financial institutions to unhedgeable systemic risk. A well documented behaviour encountered in such extreme market conditions is herding, defined as the mutual imitation leading to a convergence of action (Shefrin, 2000, Welch, 2000 and Hirshleifer and Teoh, 2003).1 In their seminal study, Bikhchandani et al. (1992) showed that herding behaviour may result in correlated patterns of actions across individuals incurring huge welfare losses. Moreover, this phenomenon provides a characteristic example of the impact of higher order beliefs on asset prices (see De Long et al., 1990 and Morris and Shin, 2003). There are a series of reasons why herding behaviour in financial markets is worth examining and documenting. From a regulatory perspective, correlated patterns of trades may well undermine financial stability (Demirer and Kutan, 2006). Pedersen (2009) provides a detailed analysis of the stability risk arising when all investors simultaneously “run for the exit”. In his account of the financial crisis, Brunnermeier (2009) identifies “fire sales” as an amplification mechanism for the propagation of initial negative shocks across the system. For investors, an increase in the degree of co-movement among asset returns reduces the benefits of portfolio diversification. As a result, it may be necessary to hold a larger number of assets to achieve the desirable reduction of idiosyncratic risk, while in the extreme case that asset returns become almost perfectly correlated, risk reduction via diversification may become unattainable (Chang et al., 2000, Baur, 2006, Chiang and Zheng, 2010 and Morelli, 2010). Moreover, mispricings resulting from this behaviour reduce the effectiveness of the market mechanism to reveal assets’ “fair values”, undermining the fundamental principle of market efficiency (Devenow and Welch, 1996) and potentially creating profitable trading opportunities (Hwang and Salmon, 2004 and Tan et al., 2008). To the extent that these mispricings lead to suboptimal decision making by institutional investors and corporations as well as erroneous reactions from policy makers, it becomes evident that herding behaviour may cause huge reduction in social welfare.2 There is a well established and extensive strand of the literature that examines contagion effects in the transmission of adverse economic and financial shocks across international markets (see for example Karolyi and Stulz, 1996 and Bae et al., 2003). On the other hand, our study contributes to the strand of the literature that focuses on the cross-sectional dispersion of stock returns in extreme market conditions. The pioneering studies of Christie and Huang (1995) and Chang et al. (2000) introduced, respectively, the statistical measures of cross-sectional standard deviation (CSSD) and cross-sectional absolute deviation (CSAD) of individual stock returns for the detection of herding effects. As Christie and Huang (1995) note, it is more likely for a “herd” to be developed in extreme market conditions, because individuals tend to suppress their own beliefs and follow the market consensus. The latter study examined this phenomenon in the US market, while Chang et al. (2000) provided further evidence considering also a series of Asian markets and documenting the existence of herding behaviour in emerging markets, notably South Korea and Taiwan. Utilizing these statistical measures, a series of studies have attempted to provide further international evidence, especially from emerging markets where herding is more likely to be encountered due to their particular characteristics: underdeveloped financial system and regulatory framework, dominance of relatively few institutional investors, exposure to highly volatile international capital flows, thin trading, suboptimal market microstructure mechanisms and non-sophisticated small stockholders.3 For example, Demirer and Kutan (2006) test for herding in the Chinese stock market. They analyze individual firm-level returns as well as sector returns using daily stock return data from 1999 to 2002 and find no evidence of such behaviour. Along the same lines, Tan et al. (2008) examined this issue in dual-listed Chinese A-shares and B-shares from 1996 to 2003. According to their results, there is evidence of herding in both the Shanghai and the Shenzhen A-share markets that are dominated by domestic individual investors as well as in both B-share markets that are dominated by foreign institutional investors. Evidence for herding behaviour is reported to be much stronger using daily data, revealing the short-term nature of the phenomenon. On the other hand, Baur (2006) found no evidence of herding in a sample of eleven developed stock markets during periods of extreme market conditions. More recently, Chiang and Zheng (2010) provided comprehensive evidence from 18 markets during the period 1988–2009. They found evidence of herding in developed markets (except the US) as well as in Asian markets. Moreover, cross-sectional return dispersion in the US played a significant role in explaining herding activity in non-US markets. Finally, there was supportive evidence for herding in the US and Latin American markets during periods of financial crises. In a related study, Caparrelli et al. (2004) examined the case of the Italian stock market for the period 1988–2001, providing mixed evidence, depending on the employed measure. Gleason et al. (2004) employed intraday data for Exchange Traded Funds (ETFs) listed on the AMEX for the period 1999–2002. Finally, Zhou and Lai (2009) used a likelihood based measure and intraday data to test for herding effects in the Hong Kong market.In contrast to the previous studies, we conduct comprehensive tests for the existence of herding behaviour in four south European markets, namely Portugal, Italy, Greece and Spain, anecdotally termed “PIGS”. Despite being members of the European Monetary Union (EMU) and characterized as developed markets, these economies have recently attracted the attention of the financial press, international organizations and market participants due to their macroeconomic imbalances (e.g. high current account deficits, huge debt-to-GDP ratios, higher inflation rates than the Eurozone average) and the threat they pose to the stability of the Eurozone as a result of their unsustainable fiscal policy stances. In particular, we construct and employ a survivor-bias-free dataset consisted of daily returns for the period 1998–2008 for these four markets. Apart from conducting standard tests, we also examine whether there is asymmetric herding behaviour in up and down markets, periods of high and low volatility as well as high and low trading activity.A novel feature of our study is to examine whether the cross-sectional dispersion of returns in one market is affected by the cross-sectional dispersion of returns in the rest three markets. Such an exercise allows us to test whether there is co-movement in the dispersion of returns, and hence whether herding effects appear contemporaneously in these southern European markets. The existence of contemporaneous “herding forces” across these markets poses a considerable threat to the financial stability of Eurozone because they may pull the trigger of a regional financial crisis that would be very hard to contain, given the big aggregate size of these economies and their interlinkages with other European economies. Supporting this argument, Morelli (2010) provided compelling evidence in favour of increased market integration and capital markets’ co-movement among EMU countries. Given the interplay between financial crises and herding behaviour, we further contribute to the literature by examining this phenomenon in detail during the recent crisis period of 2007–2008.The rest of the paper is organized as follows. Section 2 provides the details of the employed dataset and methodology. Section 3 discusses the initial set of results, examining potential asymmetric effects arising from market returns’ sign, volatility and trading activity. Section 4 contains novel tests on the cross-country impact of herding effects. Section 5 examines whether the recent financial crisis had an effect on herding behaviour and presents a series of robustness checks, while Section 6 concludes.
نتیجه گیری انگلیسی
This study provides comprehensive evidence testing for the existence of herding effects in the Portuguese, Italian, Spanish and Greek market. These four countries have been anecdotally termed “PIGS” by the financial press and market analysts due to their macroeconomic imbalances and the unsustainability of their fiscal policy stance. The ongoing debt crisis that these countries face is feared to pose a serious threat to the stability of Eurozone. As a result, it is worth examining a series of market mechanisms that may pull the trigger of a regional financial crisis and herding behaviour is long regarded to be a prime suspect. We construct a survivor-bias-free dataset consisted of daily returns for all stocks listed in these four markets for the period January 1998–December 2008. Calculating the commonly used CSAD measure that proxies the cross-sectional dispersion of stock returns in each market, we conduct a battery of tests to detect potential herding effects. Our results show that herding effects are present mainly in the Greek and the Italian market. We find no such evidence for the Spanish market, while the evidence is mixed for the case of Portugal. Dissecting further this evidence, we find that herding effects present significant asymmetries when consider rising and falling markets, days with high and low trading activity and volatility. Given this evidence, that confirms prior findings in the literature, we suggest that future studies take these asymmetries into account. A key finding of our study that is of particular importance for both international investors and policy makers is that there is a great degree of co-movement in the cross-sectional returns’ dispersion across these four markets. This feature makes more likely the potential coordination of “herding forces” in the region and the occurrence of a financial crisis. Moreover, it demonstrates that international portfolio diversification benefits are rather small when these markets are considered. Given the importance of this issue, future international studies should test for the existence of such co-movements in the cross-sectional dispersions of returns. Finally, a positive finding with respect to stability is that the recent global financial crisis did not induce a more intense herding behaviour in any of the four markets considered.