Frequency Dependent Risks in the Factor Zoo

70 Pages Posted: 25 Oct 2021 Last revised: 20 Nov 2021

See all articles by Jiantao Huang

Jiantao Huang

London School of Economics & Political Science (LSE) - Department of Finance

Date Written: October 22, 2021

Abstract

I propose a novel framework to quantify frequency-dependent risks in the factor zoo. Empirically, the linear stochastic discount factor (SDF) comprised of the first few low-frequency principal components (PCs) yields an out-of-sample monthly Sharpe ratio of 0.37, and other smaller low-frequency PCs are redundant. In contrast, the SDFs consisting of high-frequency and canonical PCs are dense and fail to identify slow-moving conditional information in asset returns. Moreover, I decompose the low-frequency SDF into two orthogonal priced components. The first component, linear in high-frequency PCs, is almost serially uncorrelated and relates to discount-rate news, intermediary factors, jump risk, and investor sentiment. The second component exhibits a persistent conditional dynamic and captures business-cycle risks related to consumption and GDP growth. Overall, asset pricing theory has frequency-dependent relevance.

Keywords: Asset Pricing, Factor Models, Fourier transform, PCA.

JEL Classification: C14, G11, G12.

Suggested Citation

Huang, Jiantao, Frequency Dependent Risks in the Factor Zoo (October 22, 2021). Available at SSRN: https://ssrn.com/abstract=3948519 or http://dx.doi.org/10.2139/ssrn.3948519

Jiantao Huang (Contact Author)

London School of Economics & Political Science (LSE) - Department of Finance ( email )

Houghton St, Holborn
London, WC2A 2AE
Great Britain

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