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Herding in mutual funds: A complex network approach

机译：相互资金中的放牧：复杂的网络方法

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The paper investigates herding in mutual funds through a complex networks approach. The detection of significant correlation coefficients constitutes the basis for the construction of the network. Some centrality measures and the assortativity are added as explanatory variables in the regression analysis of two popular indicators of herding, largely applied in finance literature. Cross-Sectional Standard Deviation and Cross-Sectional Absolute Deviation are both considered since they emphasize the bulk and the extreme values of herding. Two dummy variables designed to capture differences in investor behaviour in extreme up or down versus relatively normal markets are considered as independent variables. The results show a clear decrease of herding in stressful periods of the market. Moreover, the prevailing explanatory power of the betweenness is well evidenced, thereby highlighting the role of the network structure. In line with the literature on herding, the results also evidence a flight to safety effect.
机译：本文通过复杂的网络方法调查相互资金的遍布。检测显着的相关系数构成网络构造的基础。一些中心度措施和差异被添加到两个流行的放牧指标的回归分析中的解释性变量，主要适用于金融文学。横截面标准偏差和横截面绝对偏差都被认为是因为它们强调散装和放牧的极端值。旨在在极端向上或向下捕获投资者行为差异的两个虚拟变量被认为是独立的变量。结果表明，在市场紧张时期的放牧中明显减少。此外，普遍的解释性能力很大，从而突出了网络结构的作用。符合进一步的文献，结果也证明了安全效果的飞行。

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