高维要素定价模型中alpha的自适应检验

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Qiang Xia, Xianyang Zhang
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引用次数: 0

摘要

本文提出了一种新的方法,通过检验具有大量资产的线性因素定价模型中α的存在来验证多因素定价理论。由于市场的无效定价很可能发生在一小部分特殊资产上,因此我们开发了一种针对稀疏信号特别强大的测试程序。基于高维高斯近似理论,我们提出了一种基于仿真的方法来近似检验的极限零分布。我们的数值研究表明,与稀疏替代方案下的现有测试相比,新程序可以提供合理的尺寸并实现显着的功率改进,特别是对于弱信号。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive Testing for Alphas in High-Dimensional Factor Pricing Models
This article proposes a new procedure to validate the multi-factor pricing theory by testing the presence of alpha in linear factor pricing models with a large number of assets. Because the market’s inefficient pricing is likely to occur to a small fraction of exceptional assets, we develop a testing procedure that is particularly powerful against sparse signals. Based on the high-dimensional Gaussian approximation theory, we propose a simulation-based approach to approximate the limiting null distribution of the test. Our numerical studies show that the new procedure can deliver a reasonable size and achieve substantial power improvement compared to the existing tests under sparse alternatives, and especially for weak signals.
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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