指数基准共同基金的网络和业绩

Dan Xia Wong, Chia-Yi Yen
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摘要

本文通过实证证明,具有相似基准的共同基金之间的网络对基金净资产值(NAV)和总净资产(TNA)的变化具有重要影响。使用表示基金重叠安全持有水平的矩阵,我们获得特征向量中心性,它衡量每个基金的“影响力”。一个具有高特征向量中心性的基金是一个与其他同行有高重叠的基金,而这些同行本身也与其他同行有高重叠。面板VAR分析显示滞后特征向量中心性的变化与基金资产净值和总资产净值的变化呈显著正相关。特征向量中心性的变化“格兰杰”导致基金资产净值和总资产净值的变化,反之亦然。中心性的冲击导致基金资产净值和总资产净值的增加。这些结果使得特征向量中心性成为衡量基准诱导的单个基金羊群效应的可行指标。在同类基金中,具有最高羊群倾向的高中心性基金,其管理的平均总资产规模最大。一般来说,与同类基金相比,高中心性基金的跟踪误差、基金贝塔系数、费用和周转率以及管理费最低。为了达到这些标准,与同行相比,高中心性基金对“低贝塔”股票市场的敞口更大,同时在“高贝塔”股票市场的头寸虽小但灵活。
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Networks and Performance of Index-Benchmarked Mutual Funds
This paper establishes empirical evidence that network among mutual funds that share a similar benchmark plays an important role in changes in fund net asset value (NAV) and total net assets (TNA). Using a matrix that indicates the level of overlapped security holdings of funds, we obtain eigenvector centrality, which measures the `influence' of each fund. A fund that has high eigenvector centrality is one that has high fund holdings overlap with other peers, who themselves have high overlap with others. A panel VAR analysis shows significant positive relation of changes in lagged eigenvector centrality with changes in fund NAV and TNA. Changes in eigenvector centrality `Granger causes' changes in fund's NAV and TNA and vice versa. A shock in centrality leads to an increase in fund NAV and TNA. These results make eigenvector centrality a feasible indicator to measure the benchmark-induced herding of individual funds. High centrality funds that have the highest herding tendencies among their peers have the largest average total assets under management. In general, high centrality funds have the lowest tracking error, fund beta, expense and turnover ratios and management fees compared to their peers. To achieve these criteria, high centrality funds have larger exposure to the `low-beta' stock market segment compared to their peers, as well as small but nimble positions in the `high-beta' stock market segment.
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