Measuring Tail Dependencies Between ESG and Renewable Energy Stocks: A Copula Approach

Xie He (), Guizhou Liu () and Shigeyuki Hamori
Additional contact information
Xie He: Kobe University
Guizhou Liu: Beijing Dajia Internet Information Technology Co., Ltd.

Chapter Chapter 3 in ESG Investment in the Global Economy, 2021, pp 37-52 from Springer

Abstract: Abstract As a sustainable and responsible investment (SRI), this research aims to measure the tail dependencies between investment in companies that have the highest environmental, social, and governance (ESG) rated performance and renewable energy companies based on the copula approach, which is crucial to monitoring systemic and extreme risks between two assets. Meanwhile, we evaluate whether renewable energy stock investors can effectively increase their portfolio performance by constructing a portfolio with the best ESG companies. The results reveal that tail dependence between ESG stocks and renewable energy stocks had been volatile during most periods. However, the strengthening trend could also be found when some extreme events occurred. On the other hand, we found that ESG stocks can effectively benefit renewable energy stock portfolios by improving risk-adjusted returns and lowering the standard deviation, value-at-risk (VaR), and conditional value-at-risk (CVaR).

Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (3)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:spbchp:978-981-16-2990-7_3

Ordering information: This item can be ordered from
http://www.springer.com/9789811629907

DOI: 10.1007/978-981-16-2990-7_3

Access Statistics for this chapter

More chapters in SpringerBriefs in Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().