Table 1 Review of the literature on volatility spillovers among cryptocurrencies, energy, and technology companies
From: Volatility spillovers among leading cryptocurrencies and US energy and technology companies
Author | Period | Variables | Methodology | Results |
|---|---|---|---|---|
Symitsi and Chalvatzis (2018) | 2011–2018 | Bitcoin, S and P Global Clean Energy Index, MSCI World Energy Index, MSCI World Information and Technology Index | Multivariate GARCH | Spillover transmission from energy and technology stock to Bitcoin Bitcoin's influence includes long-term effects on the volatility of both fossil fuel and clean energy stocks There is a transfer of short-term volatility from technology companies to Bitcoin |
Kumar and Anandarao (2019) | 2015–2018 | Bitcoin, Ethereum, Ripple and Litecoin Returns | GARCH model | In the short term, there exists a moderate correlation in cryptocurrency returns Volatility spillover is impacted by fluctuations in Bitcoin prices |
Zeng et al. (2019) | 2013–2019 | Bitcoin, Crude oil, Gold and USD | Diebold and Yilmaz (2012), Barunik and Krehlik (2018) approach | In terms of return spillovers across different time horizons, the USD plays a significant role as the primary information transmitter Among various assets, crude oil stands out by contributing the highest net positive volatility spillovers, particularly in the long-term horizon |
Yıldırım et al. (2020) | 1990–2019 | Crude oil, Gold, Silver, Platinum. Palladium | The causality-in-variance test approach | Volatility spillover impact comes from the oil markets as a transmitter to the precious metals markets Bidirectional volatility spillover between Crude oil and silver return |
Al-Shboul et al. (2022) | 2015–2021 | Cryptocurrencies, Cryptocurrency policy, and Cryptocurrency price | The quantile VAR model | The total and net spillover index increased because of the COVID-19 crisis Litecoin was more dominant “hedger” during the crisis |
Cao and Xie (2022) | 2015–2020 | Cryptocurrency and China's financial market | The time-varying parameter vector autoregressions (TVP-VAR) model | Financial market has week impact on cryptocurrencies Bitcoin and Ethereum have negative spillover |
Zheng et al. (2022) | 2012–2020 | Crude oil, Renewable energy and High-technology markets | BEKK- GARCH-X approach | Spillover of volatility is observed between renewable energy and high-technology stock markets The renewable energy market in China exhibits a stronger correlation with the high-technology sector than with crude oil |
Khalfaoui et al. (2023) | 2020–2022 | Bloomberg MSCI Global Green Bond Index, Bloomberg MSCI Euro Green Bond Index, S and P Green Bond U.S. Dollar Select Index, Coronavirus Panic Index, Coronavirus Media Hype Index, Coronavirus Fake News Index, Global Sentiment, Coronavirus Infodemic Index, Coronavirus Media Coverage Index, and cryptocurrencies | Diebold and Yilmaz (2012) and the quantile connectedness approach | COVID-19 fake news looks to be the highest net shock provider more than Bitcoin The highest net shock receiver is MSCI Euro green bond |
Cagli and Mandaci (2023) | 2014–2021 | Cryptocurrency, Energy (Crude oil), Precious metals (Gold), Currency (Eurocurrency), Emerging Markets and China stock market volatility indices | Diebold and Yilmaz (2012) and Baruník and Křehlík (2018) approach | The finding indicates a low degree of uncertainty in the connectedness between cryptocurrency and energy commodity Long-term diversification is potential and underscore the dynamics of the cryptocurrency market |