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The correlation between the green bond market and carbon trading markets under climate change: Evidence from China.
- Source :
- Technological Forecasting & Social Change; Jun2024, Vol. 203, pN.PAG-N.PAG, 1p
- Publication Year :
- 2024
-
Abstract
- The environmental crisis induced by global warming has generated an increasingly heightened recognition of the imperative to embark on a journey toward sustainability. In this paper, we focus on the price correlations between two potential emission mitigation instruments: green bond (GB) and the carbon trading market. The Cross-Quantilogram (CQ) method is employed to identify these relationships within Chinese markets spanning from July 16, 2021, to March 31, 2023. Our findings reveal a diverse array of dependence structures, which are most pronounced at the first lag and tend to diminish with subsequent lags. Further analysis through the Partial Cross-Quantilogram (PCQ) approach reveals that the dependence structure is reshaped by both micro-market volatility and climate policy uncertainty, but the latter exerts influence at more extended lags. Likewise, these correlations are subject to temporal shifts, with coefficients displaying heightened magnitude and increased volatility in extreme scenarios compared to normal states. Therefore, investors and industries seeking to participate in the carbon trading market should closely monitor the performance of green bonds, particularly during tumultuous periods. • We apply the Cross-Quantilogram method to pinpoint correlations between green bond market and carbon markets. • The analysis exposes varied dependence patterns, most evident at the lag 1. • The dependence structure is reshaped by both micro-market volatility and climate policy uncertainty. • Correlations fluctuate over time, with marked intensification in extreme conditions. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00401625
- Volume :
- 203
- Database :
- Supplemental Index
- Journal :
- Technological Forecasting & Social Change
- Publication Type :
- Academic Journal
- Accession number :
- 176864925
- Full Text :
- https://doi.org/10.1016/j.techfore.2024.123367