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A statistically robust decomposition of mutual fund performance

机译:共同基金业绩的统计稳健分解

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摘要

Previous decompositions of risk-adjusted mutual fund performance might deliver biased results. In this paper, we provide new reliable insights on the drivers of mutual fund performance by decomposing risk-adjusted performance of U.S. equity mutual funds using the Generalized Calendar Time regression model. According to our results, out of all previously considered fund characteristics, only the negative effect of lagged fund size and the positive effects of lagged performance and lagged family size remain highly significant. Our analysis further suggests that much of the variation in previous empirical results can be attributed to methodological issues.
机译:风险调整后的共同基金绩效的先前分解可能会带来有偏差的结果。在本文中,我们通过使用通用日历时间回归模型分解美国股权共同基金的风险调整后绩效,为共同基金绩效的驱动因素提供了新的可靠见解。根据我们的结果,在所有先前考虑​​的基金特征中,只有滞后基金规模的负面影响以及滞后业绩和滞后家庭规模的正面影响仍然非常重要。我们的分析进一步表明,先前经验结果的许多差异都可以归因于方法论问题。

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