Universität zu Köln

Kleppe, Tore Selland, Liesenfeld, Roman ORCID: 0000-0001-6996-6215, Moura, Guilherme Valle and Oglend, Atle (2022). Analyzing Commodity Futures Using Factor State-Space Models with Wishart Stochastic Volatility. Econom. Stat., 23. S. 105 - 128. AMSTERDAM: ELSEVIER. ISSN 2452-3062

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Abstract

A factor state-space approach with stochastic volatility is proposed for modeling and forecasting the maturity structure of future commodity contracts. The proposed approach builds upon the dynamic 3-factor Nelson-Siegel model and its 4-factor Svensson extension and assumes for the latent level, slope and curvature factors a Gaussian vector autoregression with a multivariate Wishart stochastic volatility process. A computationally fast and easy to implement MCMC algorithm for the Bayesian posterior analysis is developed, which exploits the conjugacy of the Wishart and the Gaussian distribution. An empirical application to daily prices for contracts on crude oil with stipulated delivery dates ranging from one to 24 months ahead show that the estimated 4-factor Svensson model with two curvature factors provides a good parsimonious representation of the serial correlation in the individual prices and their volatility. It also shows that this model has a good out-of-sample forecast performance. (c) 2021 EcoSta Econometrics and Statistics. Published by Elsevier B.V. All rights reserved.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Kleppe, Tore Selland UNSPECIFIED UNSPECIFIED UNSPECIFIED Liesenfeld, Roman UNSPECIFIED orcid.org/0000-0001-6996-6215 UNSPECIFIED Moura, Guilherme Valle UNSPECIFIED UNSPECIFIED UNSPECIFIED Oglend, Atle UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-674199
DOI:	10.1016/j.ecosta.2021.03.008
Journal or Publication Title:	Econom. Stat.
Volume:	23
Page Range:	S. 105 - 128
Date:	2022
Publisher:	ELSEVIER
Place of Publication:	AMSTERDAM
ISSN:	2452-3062
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language TERM-STRUCTURE; VECTOR AUTOREGRESSIONS; OIL FUTURES Multiple languages Economics Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/67419