Clean Energy Stocks: Resilient Safe Havens in the Volatility of Dirty Cryptocurrencies

Abstract

Green investors have expressed concerns about the environment and sustainability due to the high energy consumption involved in cryptocurrency mining and transactions. This article investigates the safe haven characteristics of clean energy stock indexes in relation to three cryptocurrencies, taking into account their respective levels of “dirty” energy consumption from 16 May 2018 to 15 May 2023. The purpose is to determine whether the eventual increase in correlation resulting from the events of 2020 and 2022 leads to volatility spillovers between clean energy indexes and cryptocurrencies categorized as “dirty” due to their energy-intensive mining and transaction procedures. The level of integration between clean energy stock indexes and cryptocurrencies will be inferred by using Gregory and Hansen’s methodology. Furthermore, to assess the presence of a volatility spillover effect between clean energy stock indexes and “dirty-classified” cryptocurrencies, the t-test of the heteroscedasticity of two samples from Forbes and Rigobon will be employed. The empirical findings show that clean energy stock indexes may offer a viable safe haven for dirty energy cryptocurrencies. However, the precise associations differ depending on the cryptocurrency under examination. The implications of this study’s results are significant for investment strategies, and this knowledge can inform decision-making procedures and facilitate the adoption of sustainable investment practices. Investors and policy makers can gain a deeper understanding of the interplay between investments in renewable energy and the cryptocurrency market.

Balancing Portfolios with Metals: A Safe Haven for Green Energy Investors?

“…Investors can examine the environmental impact of their investments by examining financial performance, examining policy and regulatory situations, and navigating the energy transition. This overview establishes the groundwork for a more in-depth examination of these asset classes and their implications for investors in the evolving financial and clean energy markets [24][25][26][27].…”

“…Recently, the authors of [25,26,36] examined the long-and short-term shocks between clean energy stock indexes and assets classified as dirty. The study [36] investigated the co-movements between clean and dirty energy indexes before and during the COVID-19 pandemic.…”

“…Furthermore, ref. [26] investigated whether the eventual increase in correlation caused by the events of 2020 and 2022 causes volatility between clean energy indexes and cryptocurrencies classified as "dirty" due to their energy-intensive extraction and transaction procedures. According to the empirical findings, clean energy stock indexes can provide a sustainable safe haven for dirty energy cryptocurrencies.…”

The Impact of Academic Publications over the Last Decade on Historical Bitcoin Prices Using Generative Models

“…Bitcoin was born along with blockchain technology and while blockchain is perceived as beneficial to many fields, Bitcoin is highly controversial [2][3][4]. The high carbon footprint and energy consumption required by mining processes have led many researchers to call it dirty [5][6][7]. It was estimated that Bitcoin mining is roughly responsible for 65.4 MtCO 2 yearly, which is comparable to Greece's emissions.…”

“…This method, combined with perplexity and topic coherence metrics, is used to determine the optimal number of topics; (3) BERT-transformers and Word2Vec for price prediction: The study innovatively uses BERT-transformers and Word2Vec to vectorize (process) abstracts and assess their potential in predicting Bitcoin prices. This application of advanced NLP technologies in the financial analysis of cryptocurrencies represents a novel approach; (4) The sentiment analysis of the academic community: While sentiment analysis has been widely conducted on social media platforms, this study breaks new ground by focusing on the sentiment within academic research publications and its potential effect on Bitcoin prices; (5) The identification of research gaps and emerging topics: By extracting and analyzing topics from a vast number of research papers, the study identifies gaps and new topics that have been less explored by the academic community, offering directions for future research; (6) A comprehensive scope of analysis: The paper's aim to answer three research questions about relevant topics, academic sentiment, and the connection between research and Bitcoin prices covers a comprehensive scope that has not been collectively explored before in the context of cryptocurrency research. Thus, the novelty of this study is its comprehensive and multidimensional analysis of the relationship between academic research and the Bitcoin market.…”