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A Bayesian analysis based on multivariate stochastic volatility model: evidence from green stocks

Green stocks are companies environmental protective and friendly. We test Green stock index in Shanghai Stock Exchange and China Securities Index as safe-havens for global investors. Suitable multivariate-SV model and Bayesian method are used to estimate the spillover effect between different assets...

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Detalles Bibliográficos
Autores principales: Ma, Ming, Zhang, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9702865/
https://www.ncbi.nlm.nih.gov/pubmed/36467965
http://dx.doi.org/10.1007/s10878-022-00936-0
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author Ma, Ming
Zhang, Jing
author_facet Ma, Ming
Zhang, Jing
author_sort Ma, Ming
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description Green stocks are companies environmental protective and friendly. We test Green stock index in Shanghai Stock Exchange and China Securities Index as safe-havens for global investors. Suitable multivariate-SV model and Bayesian method are used to estimate the spillover effect between different assets among local and global markets. We choose multivariate volatility model because it can efficiently simulate the spillover effect by using machine learning MCMC method. The results show that the Environmental Protection Index (EPI) of Shanghai Stock Exchange (SSE) and China Securities Index (CSI) have no significant volatility spillover from Shanghai Stock index, S &P index, gold price, oil future prices of USA and China. During COVID-19 pandemic, we find Green stock index is a suitable safe-haven with low volatility spillover. Green stock indexes has a strongly one-way spillover to the crude oil future price. Environmentally friendly investor can use diversity green assets to provide a low risk investment portfolio in EPI stock market. The DCGCt-MSV model using machine learning of MCMC method is accurate and outperform others in Bayes parameter estimation.
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spelling pubmed-97028652022-11-28 A Bayesian analysis based on multivariate stochastic volatility model: evidence from green stocks Ma, Ming Zhang, Jing J Comb Optim Article Green stocks are companies environmental protective and friendly. We test Green stock index in Shanghai Stock Exchange and China Securities Index as safe-havens for global investors. Suitable multivariate-SV model and Bayesian method are used to estimate the spillover effect between different assets among local and global markets. We choose multivariate volatility model because it can efficiently simulate the spillover effect by using machine learning MCMC method. The results show that the Environmental Protection Index (EPI) of Shanghai Stock Exchange (SSE) and China Securities Index (CSI) have no significant volatility spillover from Shanghai Stock index, S &P index, gold price, oil future prices of USA and China. During COVID-19 pandemic, we find Green stock index is a suitable safe-haven with low volatility spillover. Green stock indexes has a strongly one-way spillover to the crude oil future price. Environmentally friendly investor can use diversity green assets to provide a low risk investment portfolio in EPI stock market. The DCGCt-MSV model using machine learning of MCMC method is accurate and outperform others in Bayes parameter estimation. Springer US 2022-11-27 2023 /pmc/articles/PMC9702865/ /pubmed/36467965 http://dx.doi.org/10.1007/s10878-022-00936-0 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Ma, Ming
Zhang, Jing
A Bayesian analysis based on multivariate stochastic volatility model: evidence from green stocks
title A Bayesian analysis based on multivariate stochastic volatility model: evidence from green stocks
title_full A Bayesian analysis based on multivariate stochastic volatility model: evidence from green stocks
title_fullStr A Bayesian analysis based on multivariate stochastic volatility model: evidence from green stocks
title_full_unstemmed A Bayesian analysis based on multivariate stochastic volatility model: evidence from green stocks
title_short A Bayesian analysis based on multivariate stochastic volatility model: evidence from green stocks
title_sort bayesian analysis based on multivariate stochastic volatility model: evidence from green stocks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9702865/
https://www.ncbi.nlm.nih.gov/pubmed/36467965
http://dx.doi.org/10.1007/s10878-022-00936-0
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