Research on the time-varying effects among green finance markets in China: A fresh evidence from multi-frequency scale perspective |
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Affiliation: | 1. School of Economics and Management, China University of Mining and Technology, Xuzhou 221116, China;2. School of Business, Jiangsu Normal University, Xuzhou 221116, China;1. Research Institute on Sustainable Economic Growth (IRCrES), National Research Council of Italy (CNR), Moncalieri, TO, Italy;2. Faculty of Business Administration and Economics, Bielefeld University, Bielefeld, NRW, Germany;1. Department of Risk Management and Insurance, Tamkang University, 151, Yingzhuan Rd., Tamsui Dist., New Taipei City 25137, Taiwan;2. Department of Risk Management and Insurance, Risk and Insurance Research Center, College of Commerce, National Chengchi University, 64, Sec. 2, Zhi-Nan Road, Wen-Shan District, Taipei 11605, Taiwan;1. School of Finance, Nanjing Agricultural University, Weigang 1#, Nanjing 210095, PR China;2. School of Economics and Management, Southeast University, Sipailou 2#, Nanjing 210096, PR China |
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Abstract: | Green finance is an essential instrument for achieving sustainable development. Objectively addressing correlations among different green finance markets is conducive to the risk management of investors and regulators. This paper presents evidence on the time-varying correlation effects and causality among the green bond market, green stock market, carbon market, and clean energy market in China at multi-frequency scales by combining the methods of Ensemble Empirical Mode Decomposition Method (EEMD), Dynamic Conditional Correlation (DCC) GARCH model, Time-Varying Parameter Vector Autoregression with Stochastic Volatility Model (TVP-VAR-SV), and Time-varying Causality Test. In general, the significant negative time-varying correlations among most green finance markets indicate a prominent benefit of risk hedging and portfolio diversification among green financial assets. In specific, for different time points and lag periods, the green finance market shock has obvious time-varying, positive and negative alternating effects in the short-term scales, while its time delay and persistence are more pronounced in the medium-term and long-term scales. Interestingly, a positive event shock will generate positive connectivity among most green finance markets, whereas a negative event including the China/U.S. trade friction and the COVID-19 pandemic may exacerbate the reverse linkage among green finance markets. Furthermore, the unidirectional causality of “green bond market - carbon market - green stock and clean energy markets” was established during 2018–2019. |
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Keywords: | Green finance markets Multi-frequency scales Linkage effects Time-varying causality GB" },{" #name" :" keyword" ," $" :{" id" :" pc_HQ9pFeIKus" }," $$" :[{" #name" :" text" ," _" :" Green bond market GS" },{" #name" :" keyword" ," $" :{" id" :" pc_1OU9Y2Y3eD" }," $$" :[{" #name" :" text" ," _" :" Green stock market NE" },{" #name" :" keyword" ," $" :{" id" :" pc_Sb43ndxeBh" }," $$" :[{" #name" :" text" ," _" :" Clean energy market HBEA" },{" #name" :" keyword" ," $" :{" id" :" pc_Aaqm9w3lA2" }," $$" :[{" #name" :" text" ," _" :" Carbon market DCC-GARCH" },{" #name" :" keyword" ," $" :{" id" :" pc_YFOK5Onvda" }," $$" :[{" #name" :" text" ," _" :" Dynamic Conditional Correlation GARCH model EEMD" },{" #name" :" keyword" ," $" :{" id" :" pc_29BPP3vg1b" }," $$" :[{" #name" :" text" ," _" :" Ensemble Empirical Mode Decomposition Method TVP-VAR-SV" },{" #name" :" keyword" ," $" :{" id" :" pc_dDIfNGP6BE" }," $$" :[{" #name" :" text" ," _" :" Time-Varying Parameter Vector Autoregression with Stochastic Volatility Model |
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