The role of outliers and oil price shocks on volatility of metal prices

Abstract

SummaryThis study investigates the price volatility of metals, using the GARCH and GJR models. First we examine the persistence of volatility and the leverage effect across metal markets taking into account the presence of outliers, and second we estimate the effects of oil price shocks on the price volatility of metals, allowing for the asymmetric responses. We use daily spot prices for the selected metals, including aluminum, copper, lead, nickel, tin, zinc, gold, silver, palladium and platinum.The main findings indicate that, returns show a high degree of volatility persistence before and after correcting outliers, outliers bias the parameters estimation of the GARCH-type models, and removing outliers improves the performance of models in capturing volatility. However in a comparison, Student-t distribution outperforms the approach of correcting outliers in capturing volatility. Moreover, we find the existence of inverse leverage effect for seven metals, the leverage effect for copper and no leverage effect for nickel and palladium. Finally, price volatility of metals differently reacts to oil price shocks and there is an asymmetric reaction of volatility to oil price shocks for seven metals.Keywords: Metals, Commodities, Volatility, Oil Price, Outliers. JEL Classification: G13, Q4, C1Acknowledgments: We thank participants to the FEEM seminars. Moreover, the authors acknowledge financial support from the "Energy: Resources and Markets" research program of Fondazione Eni Enrico Mattei (FEEM).

Testing for multiple bubbles in the copper price: Periodically collapsing behavior

“…From the demand perspective, accompanying the advent of accelerated industrialization and urbanization, explosive demand growth in emerging countries like China has drastically boosted price for copper, which is used as a pivotal input in manufacturing (Jerrett and Cuddington, 2008;Irandoust, 2017). Nevertheless, in the context of the commodity financialization, the key role of excessive speculation in pushing price above the level justified by market fundamentals has been highlighted in the copper market (Behmiri and Manera, 2015). In addition, the U.S. dollar has been a contributing factor to additional volatility since the international copper price is typically denominated in it (Buncic and Moretto, 2015).…”

Copula-Based Local Dependence Between Energy, Agriculture and Metal Commodity Markets

“…A second bulk of the literature addresses the co-movement and volatility spillover between energy and metal markets (Aguilera and Radetzki 2017;Behmiri and Manera, 2015;Bildirici and Turkmen. 2015;Choi and Hammoudeh, 2010;Ewing and Malik, 2013;Hammoudeh and Yuan, 2008;Ji et al, 2018b.…”

“…For example, Choi and Hammoudeh (2010) investigate the volatility transmission between oil and industrial commodities using a regimeswitching model, while Bildirici and Turkmen (2015) analyse the cointegration and causality relationship among oil and precious metals using a nonlinear ARDL cointegration framework and nonlinear causality tests. Whereas Aguilera and Radetzki (2017) investigate the synchronisation of oil and gold prices, Behmiri and Manera (2015) underline the role of oil price shocks to explain volatility in metal prices.…”

A separate reduced‐form volatility forecasting model for nonferrous metal market: Evidence from copper and aluminum

“…Early studies on volatility modeling and forecasting in the metal market primarily focused on generalized autoregressive conditional heteroskedasticity (GARCH)type models (Behmiri & Manera, 2015;Bentes, 2015;Hammoudeh, Malik, & McAleer, 2011;Hammoudeh & Yuan, 2008;Kristjanpoller & Hernández, 2017;Kristjanpoller & Minutolo, 2015;McKenzie, Mitchell, Brooks, & Faff, 2001). More recent literature suggests that high-frequency data can significantly improve the prediction accuracy of future volatility (Gong, He, Li, & Zhu, 2014;Wang & Wang, 2016;Wen, Gong, & Cai, 2016).…”

“…Watkins and McAleer (2004) found that only 45 referred to publications concentrating on metal's price volatility between 1980 and 2002 and none of them utilized intraday data. The literature on metals concentrates on volatility properties (Hammoudeh & Yuan, 2008;Todorova, 2015;Watkins & McAleer, 2008), spillover effects and information flows in different markets (Aruga & Managi, 2011;Cochran, Mansur, & Odusami, 2012;Hammoudeh, Yuan, McAleer, & Thompson, 2010;Lien & Yang, 2009;Sensoy, 2013;Xu & Fung, 2005), and the impact of news sentiment, investor sentiment, speculation, outliers and oil price shocks on the volatility of metal prices (Balcilar, Bonato, Demirer, & Gupta, 2017;Behmiri & Manera, 2015;Bosch & Pradkhan, 2015;Fassas, 2012;Smales, 2015).…”