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Modeling garch processes in base metals returns using panel data

Author

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  • Borkowski, Bolesław
  • Krawiec, Monika
  • Karwański, Marek
  • Szczesny, Wiesław
  • Shachmurove, Yochanan

Abstract

This paper investigates returns-volatility for six base metals traded on London Metal Exchange. Dividing the daily sample that extends from January 2, 2007 until February 15, 2018, to three periods, the financial crisis, “stabilization” and “prosperity.” The study applies panel data with Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH) models. The analysis shows high conditional variance for the first two periods. The best model is the panel model with random effects for the first period and with fixed effects for the second. For the “prosperity” period, the best model is “pooled regression.” For this period, one cannot dictate any accumulation of variances.

Suggested Citation

  • Borkowski, Bolesław & Krawiec, Monika & Karwański, Marek & Szczesny, Wiesław & Shachmurove, Yochanan, 2021. "Modeling garch processes in base metals returns using panel data," Resources Policy, Elsevier, vol. 74(C).
    • Handle: RePEc:eee:jrpoli:v:74:y:2021:i:c:s0301420721004207
    DOI: 10.1016/j.resourpol.2021.102411
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    More about this item

    Keywords

    Base metals; Pooled regression; Least square dummy variable (LSDV); Generalized auto-regressive conditional heteroskedasticity (GARCH); London Metal Exchange (LME); Aluminum; Bai and Perron multiple structural change tests;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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