Cryptocurrency return predictability: What is the role of the environment?

Ephraim Clark, Amine Lahiani and Salma Mefteh-Wali

Technological Forecasting and Social Change, 2023, vol. 189, issue C

Abstract: This paper investigates the lead-lag relationship across the returns of four cryptocurrencies - Bitcoin, Ethereum, Tether and TrueUSD. It identifies the important role of the environment in forecasting the cryptocurrency returns. The study compares the predictive ability of environmental variables such as temperature anomalies and CO2 emissions with that of commodities i.e. Gold and WTI returns. To the best of our knowledge, our study is the first attempt to investigate the leading role of the environment in predicting cryptocurrency returns. Most studies in the literature examine the environmental cost of Bitcoin, but none has considered the possible causal effect of the environment on Bitcoin returns. Our results show evidence of limited predictive power of lagged commodity returns, while lagged CO2 emissions significantly predict the returns of volatile cryptocurrencies, i.e. Bitcoin and Ethereum. On the other hand, environmental variables do not show any predictive power in the returns of stable coins (Tether and TrueUSD). Our findings highlight the increased awareness regarding the degradation of the environment and rapid climate change. Our results have important policy implications.

Keywords: Cryptocurrency; Environmental issues; Sustainability; Public attention; Predictability (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162523000355
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Cryptocurrency return predictability: What is the role of the environment? (2023)
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:eee:tefoso:v:189:y:2023:i:c:s0040162523000355

DOI: 10.1016/j.techfore.2023.122350

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().