Artikel

Extreme connectedness between green bonds, government bonds, corporate bonds and other asset classes: Insights for portfolio investors

This paper aims to examine the connectedness between green and conventional assets, particularly during the period of economic downturn. Specifically, we examine quantile-based time-varying connectedness between the green bond market and other financial assets using quantile vector autoregression (QVAR) from 9 March 2018 to 10 March 2021. We use daily prices of S&P U.S. Treasury Bond Index, S&P US Aggregate Bond Index, S&P US Treasury Bond Current 10Y Index, S&P 500 Bond Index, S&P 500 Financials index, S&P 500 Energy Bond Index and S&P 500, giving a total of 784 observations, and using Composite Index as a representative of conventional assets classes and S&P Green Bond Index to denote the green bond market. Results shows the connectedness between green bonds and the conventional asset classes intensified during the outbreak of the Coronavirus pandemic (COVID-19) as investors shifted their investment towards fixed income assets due to the plunge in the prices of stocks and commodities. The results also shows that green bonds are strongly connected with treasury bonds, aggregate bonds and bond index, as they share similarities with respect to issuance, risk and governance. Connectedness is weak in the case of composite index and energy bond index, as their prices do not have substantial influence on the green bond market. The study highlights the hedging and diversification benefits of green bonds. We have several implications for portfolio managers, policy makers and researchers.

Sprache
Englisch

Erschienen in
Journal: Journal of Risk and Financial Management ; ISSN: 1911-8074 ; Volume: 15 ; Year: 2022 ; Issue: 10 ; Pages: 1-17

Klassifikation
Management
Thema
green bonds
stocks
corporate bonds
treasury bonds
quantile VAR

Ereignis
Geistige Schöpfung
(wer)
Abakah, Emmanuel Joel Aikins
Tiwari, Aviral Kumar
Sharma, Aarzoo
Mwamtambulo, Dorika Jeremiah
Ereignis
Veröffentlichung
(wer)
MDPI
(wo)
Basel
(wann)
2022

DOI
doi:10.3390/jrfm15100477
Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Abakah, Emmanuel Joel Aikins
  • Tiwari, Aviral Kumar
  • Sharma, Aarzoo
  • Mwamtambulo, Dorika Jeremiah
  • MDPI

Entstanden

  • 2022

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