收缩调整夏普比率:一种改进的共同基金选择方法

IF 0.6 Q4 BUSINESS, FINANCE
Moshe Levy, Richard Roll
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引用次数: 0

摘要

众所周知,选择共同基金是一项困难的任务,因为过去的业绩对未来的业绩预测很差。我们提出了一个基金业绩指标,其中包含了一个简单的想法:Bayes James Stein意义上的收缩应该应用于总回报参数,而不是已知的费用。相对于现有方法,所提出的收缩调整夏普比(SAS)显著改进了对样本外性能的预测。当费用比样本回报重五倍时,可以获得最佳预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Shrinkage Adjusted Sharpe Ratio: An Improved Method for Mutual Fund Selection
Mutual fund selection is a notoriously difficult task, because past performance is a poor predictor of future performance. We propose a fund performance measure that incorporates a simple idea: shrinkage, in the sense of Bayes-James-Stein, should be applied to gross return parameters, but not to fees, which are known. The proposed Shrinkage Adjusted Sharpe ratio (SAS) substantially improves the prediction of out-of-sample performance relative to existing methods. The best prediction is obtained when fees are weighed five times heavier than sample returns.
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来源期刊
Journal of Investing
Journal of Investing BUSINESS, FINANCE-
CiteScore
1.10
自引率
16.70%
发文量
42
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