Dynamic volatility connectedness between industrial metal markets |
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| Institution: | 1. School of Management, China Institute for Studies in Energy Policy, Xiamen University, Xiamen 361005, China;2. School of Public Affairs, Zhejiang University, Hangzhou 310058, China;3. Institute for Advanced Studies in Finance and Economics, Hubei University of Economics, Wuhan 430205, China;1. Worcester Polytechnic Institute, Worcester, MA 01609, United States;2. Broadwell School of Business & Economics, Fayetteville State University 1200 Murchison Rd., Fayetteville, NC 28301;1. Department of Economics and Business of Lehman College, City University of New York, USA;2. Department of Economics, Universidad del Valle, Cali, Colombia;3. Riskcenter, University of Barcelona, Barcelona, Spain;4. Escuela Internacional de Ciencias Economicas y Administrativas, Universidad de La Sabana, Chia, Colombia |
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| Abstract: | Combined with the spillover framework of Diebold and Yilmaz (2009, 2012, 2014) and the TVP-VAR-SV model of Primiceri (2005), this paper studies the dynamic volatility connectedness between six major industrial metal (i.e., aluminum, copper, lead, nickel, tin and zinc) spot and futures markets. The results show that: (1) The total volatility connectedness between industrial metal spot or futures markets has three obvious cyclical change periods with a higher connectedness level; (2) The net connectedness of zinc and copper with other metals has been at a high positive level for a long time, which indicates the two metal markets dominate the industrial metal market; (3) Zinc exhibits the strongest volatility spillovers, while tin exhibits the weakest volatility spillovers, no matter in spot markets or futures markets; (4) The connectedness of realized skewness and kurtosis have similarity with volatility connectedness but the spillover effects of skewness and kurtosis are not as obvious as the volatility spillover effects. |
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| Keywords: | Volatility spillover Spillover index Industrial metal TVP-VAR-SV model |
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