A Model-based Commodity Risk Measure on Commodity and Stock Market Returns

2022 University of Rochester Conference in Econometrics, Paris December Finance Meeting 2022, FMA Annual Meeting 2022, FMA-Europe 2022, EFMA 2022

82 Pages Posted: 21 Sep 2022 Last revised: 21 Nov 2022

See all articles by Ai Jun Hou

Ai Jun Hou

Stockholm University

Emmanouil Platanakis

University of Bath - School of Management

Xiaoxia Ye

University of Liverpool Management School

Guofu Zhou

Washington University in St. Louis - John M. Olin Business School

Date Written: November 19, 2022

Abstract

We propose a novel measure of the ex-ante commodity downside-risk premium (CDP) for each commodity based on a term structure model of commodity futures. Our theory-based CDP, capturing forward-looking information in the futures markets, outperforms well-known characteristics in explaining the cross-section of commodity returns. The CDP factor – the high minus low portfolio constructed from sorting CDP – has the highest Sharpe ratio among existing factors, and none of the latter can explain it, implying it has substantial new information. Moreover, various aggregations of individual commodity CDP predict future stock market returns significantly, even after controlling for major economic predictors. The link between commodities and the stock market is stronger than previously thought.

Keywords: Commodities, Term structure models, Predictability, Cross-sectional asset pricing

JEL Classification: G10, G11, G12, G13

Suggested Citation

Hou, Ai Jun and Platanakis, Emmanouil and Ye, Xiaoxia and Zhou, Guofu, A Model-based Commodity Risk Measure on Commodity and Stock Market Returns (November 19, 2022). 2022 University of Rochester Conference in Econometrics, Paris December Finance Meeting 2022, FMA Annual Meeting 2022, FMA-Europe 2022, EFMA 2022, Available at SSRN: https://ssrn.com/abstract=4213690 or http://dx.doi.org/10.2139/ssrn.4213690

Ai Jun Hou

Stockholm University ( email )

Universitetsvägen 10
Stockholm, Stockholm SE-106 91
Sweden

Emmanouil Platanakis (Contact Author)

University of Bath - School of Management ( email )

Claverton Down
Bath, BA2 7AY
United Kingdom

Xiaoxia Ye

University of Liverpool Management School ( email )

Chatham Street
Liverpool, L69 7ZH
United Kingdom

Guofu Zhou

Washington University in St. Louis - John M. Olin Business School ( email )

Washington University
Campus Box 1133
St. Louis, MO 63130-4899
United States
314-935-6384 (Phone)
314-658-6359 (Fax)

HOME PAGE: http://apps.olin.wustl.edu/faculty/zhou/

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