The interrelationship between the carbon market and the green bonds market: Evidence from wavelet quantile-on-quantile method
The interrelationship between the carbon market and the green bonds market: Evidence from wavelet quantile-on-quantile method
The 26th edition of the United Nations climate change conference (COP26) underlines the importance of financial products and markets related to “carbon” (e.g., carbon and green bond markets). We, to our knowledge, are the first to construct a framework based on multiple time scales and market conditions to quantify the interrelationship between the carbon futures and green bond markets. Specifically, we estimate it from short-, medium-, and long-term perspectives and different market conditions by combining the maximum overlap discrete wavelet transform (MODWT) and two quantile methods to decompose the sequences into various frequencies and quantiles. We find that the carbon futures price unilaterally Granger causes the green bond index and empirically analyzes the asymmetric impact of the carbon futures with a two-dimensional quantile model constructed by the quantile-on-quantile (QQ) regression approach. We find positive effects of the carbon futures in the medium to long term and erratic performance in the short term. The effects are more pronounced when both markets are in an extreme state. Our findings enrich the research related to eco-economy and carbon finance, providing a more comprehensive and detailed research framework, and helping others optimize investment portfolios and policy arrangements.
Ren, Xiaohang
970abdf4-ff20-4244-9952-f9ee910736ee
Li, Yiying
8a581d52-64fb-4473-8858-dfc1b29d9929
Yan, Cheng
6153d22a-ca67-4336-b728-c9eed4f36422
Wen, Fenghua
ed1a62d3-c289-4d18-942b-7a5bac10a768
Lu, Zudi
4aa7d988-ac2b-4150-a586-ca92b8adda95
1 June 2022
Ren, Xiaohang
970abdf4-ff20-4244-9952-f9ee910736ee
Li, Yiying
8a581d52-64fb-4473-8858-dfc1b29d9929
Yan, Cheng
6153d22a-ca67-4336-b728-c9eed4f36422
Wen, Fenghua
ed1a62d3-c289-4d18-942b-7a5bac10a768
Lu, Zudi
4aa7d988-ac2b-4150-a586-ca92b8adda95
Ren, Xiaohang, Li, Yiying, Yan, Cheng, Wen, Fenghua and Lu, Zudi
(2022)
The interrelationship between the carbon market and the green bonds market: Evidence from wavelet quantile-on-quantile method.
Technological Forecasting and Social Change, 179, [121611].
(doi:10.1016/j.techfore.2022.121611).
Abstract
The 26th edition of the United Nations climate change conference (COP26) underlines the importance of financial products and markets related to “carbon” (e.g., carbon and green bond markets). We, to our knowledge, are the first to construct a framework based on multiple time scales and market conditions to quantify the interrelationship between the carbon futures and green bond markets. Specifically, we estimate it from short-, medium-, and long-term perspectives and different market conditions by combining the maximum overlap discrete wavelet transform (MODWT) and two quantile methods to decompose the sequences into various frequencies and quantiles. We find that the carbon futures price unilaterally Granger causes the green bond index and empirically analyzes the asymmetric impact of the carbon futures with a two-dimensional quantile model constructed by the quantile-on-quantile (QQ) regression approach. We find positive effects of the carbon futures in the medium to long term and erratic performance in the short term. The effects are more pronounced when both markets are in an extreme state. Our findings enrich the research related to eco-economy and carbon finance, providing a more comprehensive and detailed research framework, and helping others optimize investment portfolios and policy arrangements.
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Accepted/In Press date: 8 March 2022
e-pub ahead of print date: 16 March 2022
Published date: 1 June 2022
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Local EPrints ID: 456158
URI: http://eprints.soton.ac.uk/id/eprint/456158
ISSN: 0040-1625
PURE UUID: 58376c4f-ec8a-4f19-91c4-b26c2830e04b
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Date deposited: 26 Apr 2022 15:07
Last modified: 17 Mar 2024 03:34
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Author:
Xiaohang Ren
Author:
Yiying Li
Author:
Cheng Yan
Author:
Fenghua Wen
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