因子信号计算的专一性

Mark K. Pyles
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引用次数: 0

摘要

本文考察了五个主要因素类别中彭博因子信号计算的特殊性,重点是实际分析和应用。我们从收益和稳定性的角度考察了它们在2003年至2021年间的表现,重点关注理解报告信号对计算定义的敏感性的重要性。我们发现,在大多数情况下,通过在创建因子信号时结合非极端定义,可以找到更好的回报和风险绩效。我们的研究结果表明,根据信号计算的规格,可以预期基线信号周围约3%的偏差范围。最后,我们考察了不同计算方法对投资组合绩效衡量的潜在影响。最后,我们得出的结论是,投资者应该谨慎地外推所呈现的因子值,无论是在宏观意义上的市场影响,还是因为它与投资组合风险敞口有关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the Specificity of Factor Signal Calculations
This article examines the specificity of calculations for Bloomberg factor signals within five prominent factor categories, with a focus on practical analysis and application. We examine their performance from 2003 to 2021, from both a return and a stability standpoint of the factors, focusing on the importance of understanding the sensitivity of the reported signals to calculation definitions. We find that, in most cases, a better return and risk performance is found by combining non-extreme definitions in creating factor signals. Our findings suggest that an approximately 3% range of deviation around the baseline signal can be expected, dependent upon the specification of the signal calculation. Finally, we examine the potential impact of differing calculations on portfolio performance measurement. Ultimately, we conclude that investors should be careful in extrapolating presented factor values both in a macro sense of market impact and as it relates to portfolio exposures.
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