Affiliation:
1. School of Economics and Management Dalian University of Technology Dalian China
2. School of Information and Business Management Dalian Neusoft University of Information Dalian China
3. School of Finance Dongbei University of Finance and Economics Dalian China
Abstract
AbstractAn objective and robust network‐based data‐driven strategy is proposed to analyze risk spillovers in carbon markets. First, we characterize the causality network between the carbon market and potential associated markets using a data‐driven fuzzy cognitive map approach. Second, network‐based community detection is conducted to explore community structures that include carbon trading markets, and five market factors belonging to the same community as EU Allowances (EUA) are identified. Next, we conduct downside and upside‐tail measurements of EUA risk spillover levels within the community based on estimates and fits of marginal and joint distributions for different market pairs. Finally, we point out that the market factor having the most significant upper‐tail spillover effects on EUA is OILFUTURE, besides, EURUSD asset is found to be the best hedge for EUA futures among the detected market factors.
Funder
National Social Science Fund of China
Fundamental Research Funds for the Central Universities
Subject
Economics and Econometrics,Finance,Accounting