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Volatility spillovers in commodity markets: A large t-vector autoregressive approach

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  • Barbaglia, Luca
  • Croux, Christophe
  • Wilms, Ines

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.

Suggested Citation

  • Barbaglia, Luca & Croux, Christophe & Wilms, Ines, 2020. "Volatility spillovers in commodity markets: A large t-vector autoregressive approach," Energy Economics, Elsevier, vol. 85(C).
  • Handle: RePEc:eee:eneeco:v:85:y:2020:i:c:s0140988319303500
    DOI: 10.1016/j.eneco.2019.104555
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    Cited by:

    1. Tadahiro Nakajima & Yuki Toyoshima, 2020. "Examination of the Spillover Effects among Natural Gas and Wholesale Electricity Markets Using Their Futures with Different Maturities and Spot Prices," Energies, MDPI, Open Access Journal, vol. 13(7), pages 1-14, March.

    More about this item

    Keywords

    Commodities; Forecasting; Lasso; Multivariate t-distribution; Vector autoregressive model; Volatility spillover;

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market

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