Cryptocurrencies, including Bitcoin, have rapidly emerged as a new asset class offering enormous opportunities for traders, institutional investors, businesses, and governments although their valuations continue to be highly volatile. A large strand of academic literature has so far used daily data and showed the detachment of cryptocurrencies from the global financial system - including financial assets and macroeconomic variables, suggesting policy implications about the diversification and hedging capabilities of cryptocurrencies. While doing so, they have limited their analysis to the first and second moments of the return distribution although cryptocurrencies are characterized by extreme volatility and non-normally disturbed returns. In this regard, different and more refined cross-market dynamics can be uncovered if intraday high frequency data were used instead and if the analysis is extended to cover higher-order moments such as skewness and kurtosis. Such an understudied research gap deserves to be addressed for the sake of day and high-frequency traders. Otherwise, these market participants will remain very weakly informed about the true intraday market dynamics between cryptocurrencies and financial assets or across various cryptocurrencies and run the risk of making suboptimal decisions that do not account for the deviation of the return distribution from Normality.
Addressing these issues is important, especially given that the post-COVID period has witnessed a shift and an increase in the dynamic of relationship between cryptocurrency and stock markets. This deserves a special attention via granulated data and the analysis of crash risk (i.e. skewness and kurtosis) spillovers, for the sake of policymakers who are increasingly concerned potential destabilizing risk arising from the cryptocurrency ecosystem.
Against this backdrop, the editors of this Special Issue “Hidden market linkages between Bitcoin, cryptocurrencies and financial markets: Evidence from high-frequency data and higher-order moments“ invite you to shed new lights on the grey box of the crypto-financial markets nexus by considering manuscripts applying sophisticated econometric techniques to high-frequency data and higher moments. The covered topics include, inter alia, the following:
- Cryptocurrencies, financial markets, and global uncertainties
- Fintech, Bitcoin, and financial services
- Reaction of cryptocurrencies to news
- Time-varying volatility, skewness, and kurtosis
- Higher-order realized moments and jumps
- Crypto-market efficiency
- Cryptocurrency liquidity and microstructure
- High frequency and temporal trading strategies
- Intraday seasonalities and return predictability
- Average and tail-based connectedness
- Hedging and safe-haven properties of cryptocurrencies
- High frequency (algorithm) trading
- Bitcoin, cryptocurrencies, and stablecoins
- Financial markets
- Fiat currencies
- Economic, uncertainty, and sentiment indicators
- Portfolio analysis and risk management
- Modelling of volatility and higher-order moments
- Long memory Financial derivatives
- Intraday return predictability
- Network analysis
- Market crash and tail risk
- Time series properties
Submission Deadline: Oct, 31,2022
Elie Bouri, School of Business, Lebanese American University (firstname.lastname@example.org)
Syed Jawad Hussain Shahzad, Montpellier Business School, Montpellier (email@example.com)
Ladislav Kristoufek, The Czech Academy of Sciences, Institute of Information Theory and Automation. Institute of Economic Studies, Faculty of Social Sciences, Charles University (LK@fsv.cuni.cz)
Bouri, E., Lei, X., Jalkh, N., Xu, Y., & Zhang, H. (2021). Spillovers in higher moments and jumps across US stock and strategic commodity markets. Resources Policy, 72, 102060.
Bouri, E., Shahzad, S. J. H., Roubaud, D., Kristoufek, L., & Lucey, B. (2020). Bitcoin, gold, and commodities as safe havens for stocks: New insight through wavelet analysis. The Quarterly Review of Economics and Finance, 77, 156-164.
Kumar, A., Iqbal, N., Mitra, S.K., Kristoufek, L., & Bouri, E. (2022). Connectedness among major cryptocurrencies in standard times and during the COVID-19 outbreak. Journal of International Financial Markets, Institutions & Money, 77, 101523.
Naeem, M. A., Bouri, E., Peng, Z., Shahzad, S. J. H., & Vo, X. V. (2021). Asymmetric efficiency of cryptocurrencies during COVID19. Physica A: Statistical Mechanics and its Applications, 565, 125562.
Shahzad, S. J. H., Bouri, E., Kang, S. H., & Saeed, T. (2021). Regime specific spillover across cryptocurrencies and the role of COVID-19. Financial Innovation, 7(1), 1-24.
Xiao, H., Xiong, X., & Chen, W. (2021). Introduction to the special issue on Impact of COVID-19 and cryptocurrencies on the global financial market. Financial Innovation, 7(1), 1-2.
Yousaf, I., & Ali, S. (2020). Discovering interlinkages between major cryptocurrencies using high- frequency data: new evidence from COVID-19 pandemic. Financial Innovation, 6(1), 1-18.