Examining the evidence of risk spillovers between Shanghai and London non-ferrous futures markets: a dynamic Copula-CoVaR approach. Issue 5 (20th October 2020)

• Record Type: Journal Article
• Authors: Shen, Hong; Tang, Yue; Xing, Ying; Ng, Pin
• Is Part Of: International journal of emerging markets. Volume 16:Issue 5(2021)
• Page Start: 929
• Page End: 945
• Publication Date: 2020-10-20
• Subjects: Futures market -- Risk spillovers -- Copula -- CoVaR; Business enterprises -- Finance -- Periodicals; Investments -- Developing countries -- Periodicals; Commerce -- Periodicals; Developing countries -- Economic conditions -- Periodicals; 330.91724
• DOI: 10.1108/IJOEM-04-2020-0355
• Languages: English
• ISSNs: 1746-8809

Abstract

Abstract : Purpose: This paper aims to examine the evidence of risk spillovers between Shanghai and London non-ferrous futures markets using a dynamic Copula-CoVaR approach. Design/methodology/approach: With daily data, the marginal distributions and optimal Copula functions are determined using the kernel estimation method and squared Euclidean distance test. The conditional value-at-risk and the conditional value-at-risk spillover rate are computed from the Copula estimated parameters based on the Copula-CoVaR model. Also, the dynamic correlation coefficient between the two futures markets is investigated. Findings: The empirical results are as follows: overall, the risk spillover effect exerted by the London Metal Exchange on the Shanghai Futures Exchange is more significant than vice versa. Moreover, the degree of risk spillovers exerted by the London Metal Exchange on the Shanghai Futures Exchange for zinc and copper are more significant when they are depressed in the London Metal Exchange. Moreover, the dynamic of the correlation between the Shanghai and London futures markets is attributed to be largely due to changes in the global economy. Research limitations/implications: The Copula-CoVaR model used in this paper is suitable for measuring the risk spillovers between two different markets, while the risk spillovers across multiple markets or the consideration of multiple risk factors cannot be accurately captured using this framework. Multiple state variables to capture time variation in the conditional moments of return series will be a topic in future research. Practical implications: The results provide theoretical support for risk management and monitoring of the non-ferrous futures markets. Originality/value: The ability of the Copula function to accurately describe a nonlinear relationship and tail correlation is harnessed to measure the risk spillovers, explore the degree and direction of risk spillovers and identify the source of risk spillovers. The global economy is incorporated as a macro factor to explore its inner connection with the dynamic of risk spillovers in the non-ferrous metal futures market.