 Volatility spillovers in commodity markets: A large t-vector autoregressive approachLuca Barbaglia, Christophe Croux and Ines Wilms Energy Economics, 2020, vol. 85, issue C Abstract: Prices of commodities have shown large fluctuations. A high volatility of one commodity today may impact the volatility of another commodity tomorrow. As such, agricultural and energy commodities are closely dependent due to the expansion of the biofuel industry. We study volatility spillovers among a large number of energy, agriculture and biofuel commodities using the vector auto regressive (VAR) model. To account for the possible fat-tailed distribution of the model errors, we propose the t-lasso method for obtaining a large VAR. The t-lasso is shown to have excellent properties, and a forecast analysis shows that the t-lasso attains better forecast accuracy than standard estimators. Our empirical analysis shows the existence of volatility spillovers between energy and biofuel, and between energy and agricultural commodities. Keywords: Commodities; Forecasting; Lasso; Multivariate t-distribution; Vector autoregressive model; Volatility spillover (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:85:y:2020:i:c:s0140988319303500 DOI: 10.1016/j.eneco.2019.104555 Access Statistics for this article Energy Economics is currently edited by R. S. J. Tol, Beng Ang, Lance Bachmeier, Perry Sadorsky, Ugur Soytas and J. P. Weyant More articles in Energy Economics from Elsevier |
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