Modeling garch processes in base metals returns using panel data

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

Resources Policy, 2021, vol. 74, issue C

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.

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 (search for similar items in EconPapers)
JEL-codes: C23 C58 G14 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jrpoli:v:74:y:2021:i:c:s0301420721004207

DOI: 10.1016/j.resourpol.2021.102411

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