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Multidimensional risk spillovers among carbon, energy and nonferrous metals markets: Evidence from the quantile VAR network

  • Yuqin Zhou
  • , Shan Wu*
  • , Zeyi Zhang
  • *Corresponding author for this work
  • Chongqing Normal University
  • Nanjing University of Finance & Economics

Research output: Contribution to journalArticlepeer-review

76 Citations (Scopus)

Abstract

Carbon market attracts much attention due to its unique statue of promoting the transformation and development of low-carbon economy. In this paper, we investigate the multidimensional risk spillover effects among carbon, energy and nonferrous metals markets, and also examine the portfolio diversification. The quantile VAR network framework and GARCHSK model are applied. We find that: (i)There are significant risk spillover effects among carbon, energy and nonferrous metal market with prominent dynamic characteristics, while the risk spillover under different dimensions shows apparent differences. (ii)According to the findings based on network structure features, the Coal market becomes the core market of carbon-energy-nonferrous system, and the position of carbon trading market is significantly weakened when the market is downturn. (iii) In their portfolios, the nonferrous metals assets are preferred over carbon and energy, investors should adjust the portfolio structure and hedge positions according to market conditions. These findings have important implications for investors to construct diversified portfolios and regulators to formulate risk regulation policies.

Original languageEnglish
Article number106319
JournalEnergy Economics
Volume114
DOIs
Publication statusPublished - Oct 2022
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth
  2. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production

Keywords

  • Carbon market
  • GARCHSK model
  • Quantile VAR network

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