Mean-Reversion in Commodity Futures Volatility: An Analysis of Daily Range-Based Stochastic Volatility Models

38 Pages Posted: 16 Apr 2021

See all articles by Stephen Figlewski

Stephen Figlewski

New York University - Stern School of Business

Marco Haase

University of Basel - Center for Economic Science (WWZ) - Department of Finance

Matthias Huss

University of Basel - Center for Economic Science (WWZ) - Department of Finance

Heinz Zimmermann

University of Basel

Date Written: April 13, 2021

Abstract

We analyse the dynamic behavior of conditional volatility in commodity markets using a novel, manually collected dataset of daily price ranges over a time span of more than 140 years, which allows more precise daily volatility estimates than are otherwise prevalent in the commodity literature. We find that a one-factor range-based EGARCH-model (REGARCH) is not adequate to capture the very distinct long-run and short-run dynamic volatility components. While the long memory effect of volatility is numerically very small, it strongly affects the parameters of the short-run dynamics which become more stable and plausible in size. Moreover, long-run persistency in volatility shocks is practically unaffected after controlling for regimes which indicates that the stochastic movement of the long-run mean is not a statistical artefact. We also find that consistent with the theory of storage, long run volatility is positively related to lagged returns. Thus, asymmetry in volatility is not a short-run phenomenon.

Keywords: Commodity futures volatility, historical price analysis, range-based volatility estimation, range-based GARCH models, structural volatility breaks

JEL Classification: C58, E30, G13, N21, N51, Q02

Suggested Citation

Figlewski, Stephen and Haase, Marco and Huss, Matthias and Zimmermann, Heinz, Mean-Reversion in Commodity Futures Volatility: An Analysis of Daily Range-Based Stochastic Volatility Models (April 13, 2021). Available at SSRN: https://ssrn.com/abstract=3825894 or http://dx.doi.org/10.2139/ssrn.3825894

Stephen Figlewski

New York University - Stern School of Business ( email )

44 West 4th Street
Department of Finance Suite 9-160
New York, NY 10012-1126
United States
212-998-0712 (Phone)
212-995-4220 (Fax)

Marco Haase

University of Basel - Center for Economic Science (WWZ) - Department of Finance ( email )

Peter Merian Weg 6
Basel, CH-4002
Switzerland

Matthias Huss

University of Basel - Center for Economic Science (WWZ) - Department of Finance ( email )

Peter Merian-Weg 6
Basel, CH-4002
Switzerland

Heinz Zimmermann (Contact Author)

University of Basel ( email )

Peter Merian Weg 6
Basel, 4002
Switzerland
+41 61 267 33 16 (Phone)
+41 61 267 08 98 (Fax)

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