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Exploring time and frequency linkages of green bond with renewable energy and crypto market

Author

Listed:
  • Miklesh Prasad Yadav

    (Indian Institute of Foreign Trade)

  • Priyanka Tandon

    (Regenesys Business School)

  • Anurag Bhadur Singh

    (XIM University)

  • Adam Shore

    (Liverpool John Moores University)

  • Pali Gaur

    (Regenesys Business School)

Abstract

This paper examines the dynamic linkages of green bond with the energy and crypto market. The S&P green bond index (RSPGB) is used as a proxy for the green bond market; S&P global clean energy index and ISE global wind energy (RIGW) are used as proxies for the renewable energy market, and; Bitcoin and Ethereum (RETHER) are used as the proxies of the crypto market. The daily prices of these constituent series are collected using Bloomberg from October 3, 2016 to February 23, 2021. We undertake an empirical analysis through the application of three key tests, namely: dynamic conditional correlation (DCC), Diebold and Yilmaz (Int J Forecast 28(1):57–66, 2012. 10.1016/j.ijforecast.2011.02.006), Baruník and Křehlík (J Financ Econom 16(2):271–296, 2018. 10.1093/jjfinec/nby001) model. The DCC reveals no dynamic linkages of volatility from the green bond to the energy and crypto market in the short run. Referring to Diebold and Yilmaz (2012), it dictates that the green bond (RSPGB) is a net receiver while the energy market (RIGW) and cryptocurrency (RETHER) are the largest and least contributors to the transmission of the volatility. Additionally, the Baruník and Křehlík (2018) model confirmed that the magnitude of the total spillover is high in more prolonged than shorter periods, suggesting reduced diversification opportunities. Overall, the present study exemplifies the significance of the green bond market as protection against risk.

Suggested Citation

  • Miklesh Prasad Yadav & Priyanka Tandon & Anurag Bhadur Singh & Adam Shore & Pali Gaur, 2025. "Exploring time and frequency linkages of green bond with renewable energy and crypto market," Annals of Operations Research, Springer, vol. 348(3), pages 1547-1572, May.
    • Handle: RePEc:spr:annopr:v:348:y:2025:i:3:d:10.1007_s10479-022-05074-8
    DOI: 10.1007/s10479-022-05074-8
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