The Low-volatility Anomaly and the Adaptive Multi-Factor Model

40 Pages Posted: 4 May 2021 Last revised: 3 Nov 2021

See all articles by Robert A. Jarrow

Robert A. Jarrow

Cornell University - Samuel Curtis Johnson Graduate School of Management

Rinald Murataj

T Rowe Price

Martin T. Wells

Cornell University - Law School

Liao Zhu

Cornell University - Department of Statistics and Data Science

Date Written: April 25, 2021

Abstract

The paper provides a new explanation of the low-volatility anomaly. We use the Adaptive Multi-Factor (AMF) model estimated by the Groupwise Interpretable Basis Selection (GIBS) algorithm to find those basis assets significantly related to low and high volatility portfolios. These two portfolios load on very different factors, indicating that volatility is not an independent risk, but that it's related to existing risk factors. The out-performance of the low-volatility portfolio is due to the (equilibrium) performance of these loaded risk factors. The practical insight is that the long and short legs of a portfolio are with different risks and need to be modeled separately. Our methodology is applicable to any long-short anomaly but we focus on the low-volatility anomaly since it is formed explicitly on the risk characteristic rather than on embedded risks of other anomalies. The AMF model outperforms the Fama-French 5-factor model significantly both in-sample and out-of-sample.

Keywords: Low-volatility anomaly, AMF model, GIBS algorithm, high-dimensional statistics, machine learning, False Discovery Rate.

JEL Classification: C10, G10

Suggested Citation

Jarrow, Robert A. and Murataj, Rinald and Wells, Martin T. and Zhu, Liao, The Low-volatility Anomaly and the Adaptive Multi-Factor Model (April 25, 2021). Cornell Legal Studies Research Paper No. 21-21, Available at SSRN: https://ssrn.com/abstract=3834026 or http://dx.doi.org/10.2139/ssrn.3834026

Robert A. Jarrow

Cornell University - Samuel Curtis Johnson Graduate School of Management ( email )

Department of Finance
Ithaca, NY 14853
United States
607-255-4729 (Phone)
607-254-4590 (Fax)

Rinald Murataj

T Rowe Price ( email )

United States

Martin T. Wells

Cornell University - Law School ( email )

Comstock Hall
Ithaca, NY 14853
United States
607-255-8801 (Phone)

Liao Zhu (Contact Author)

Cornell University - Department of Statistics and Data Science ( email )

301 Tower Road
Ithaca, NY 14853-3801
United States
607-379-7330 (Phone)

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