Herd behavior in financial markets often leads to unjustified macroscopic phenomena.However,despite existing studies on modeling herd behavior,how it varies across individual agents and over time remains unclear.We sh...Herd behavior in financial markets often leads to unjustified macroscopic phenomena.However,despite existing studies on modeling herd behavior,how it varies across individual agents and over time remains unclear.We show that herd behavior in mutual fund companies can be understood from the functional networks representing interactions inferred from investment similarities.Specifically,in this paper,the spatial characteristics of herd behavior stand for the topology relationships of observations in networks.We analyze the collective dynamics of mutual fund investment from 2003 to 2019 in China using the language of network science and show that herding behavior accompanies this industry's development but dwindles after the 2015 Chinese market crash.By integrating community detection analysis,we found an increased degree of coherence in the collective herding behavior of the system,even though the localization of herding behavior decreases for clusters of mutual fund companies when the systemic risk builds up.Further analysis showed that herding behavior impacts the payoff of individual fund companies differently across years.The spatial-temporal changes of herding behavior between mutual funds presented in this paper shed light on the debate of individual versus systemic risk and,thus,could interest regulators and investors.展开更多
本文将账面市值比分解为公司基本面信息和投资者对公司发展前景的主观预期信息,以1994-2008年间在沪深两地上市的A股公司为样本,首先采用Fama and Macbeth(1973)方法检验市场对什么信息过度反应,接着利用羊群行为指标考察证券投资基金...本文将账面市值比分解为公司基本面信息和投资者对公司发展前景的主观预期信息,以1994-2008年间在沪深两地上市的A股公司为样本,首先采用Fama and Macbeth(1973)方法检验市场对什么信息过度反应,接着利用羊群行为指标考察证券投资基金对该信息的反应。结果表明,市场对公司基本面无明显反应,但对公司发展前景的主观预期过度反应;当市场对公司发展前景乐观(悲观)时,基金在股票上表现出买方(卖方)羊群行为,基金羊群行为加重市场过度反应。展开更多
文摘Herd behavior in financial markets often leads to unjustified macroscopic phenomena.However,despite existing studies on modeling herd behavior,how it varies across individual agents and over time remains unclear.We show that herd behavior in mutual fund companies can be understood from the functional networks representing interactions inferred from investment similarities.Specifically,in this paper,the spatial characteristics of herd behavior stand for the topology relationships of observations in networks.We analyze the collective dynamics of mutual fund investment from 2003 to 2019 in China using the language of network science and show that herding behavior accompanies this industry's development but dwindles after the 2015 Chinese market crash.By integrating community detection analysis,we found an increased degree of coherence in the collective herding behavior of the system,even though the localization of herding behavior decreases for clusters of mutual fund companies when the systemic risk builds up.Further analysis showed that herding behavior impacts the payoff of individual fund companies differently across years.The spatial-temporal changes of herding behavior between mutual funds presented in this paper shed light on the debate of individual versus systemic risk and,thus,could interest regulators and investors.
文摘本文将账面市值比分解为公司基本面信息和投资者对公司发展前景的主观预期信息,以1994-2008年间在沪深两地上市的A股公司为样本,首先采用Fama and Macbeth(1973)方法检验市场对什么信息过度反应,接着利用羊群行为指标考察证券投资基金对该信息的反应。结果表明,市场对公司基本面无明显反应,但对公司发展前景的主观预期过度反应;当市场对公司发展前景乐观(悲观)时,基金在股票上表现出买方(卖方)羊群行为,基金羊群行为加重市场过度反应。
