A0215
Title: Investigate the dependence structure of dirty and clean cryptocurrencies with energy and green assets
Authors: Shu-Han Hsu - National Taipei University of Business (Taiwan)
Po-Keng Cheng - National Taipei University (Taiwan) [presenting]
Yiwen Yang - National Taiwan Normal University (Taiwan)
Abstract: The growth of cryptocurrencies, which have high volatility, weak correlations with traditional assets, and high environmental impact, spurred interest in their interaction with energy and green financial markets. The purpose is to innovatively use the Markov-switching generalized autoregressive conditional heteroscedasticity model with dynamic conditional correlation to explore the regime-dependent return and volatility connectedness of dirty and clean cryptocurrencies with energy and green financial assets. The empirical results indicate that cryptocurrencies can act as diversifiers, hedges, and safe havens against different energy and green assets under various market conditions. The findings emphasize the importance of promoting clean cryptocurrencies and integrating green finance principles while addressing contagion risks. Policymakers are urged to support sustainable digital assets and raise environmental awareness to contribute to a more resilient financial ecosystem.
