Exploring asymmetric multifractal cross-correlations of price–volatility and asymmetric volatility dynamics in cryptocurrency markets
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DOI: 10.1016/j.physa.2021.126237
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Cited by:
- Fung, Kennard & Jeong, Jiin & Pereira, Javier, 2022. "More to cryptos than bitcoin: A GARCH modelling of heterogeneous cryptocurrencies," Finance Research Letters, Elsevier, vol. 47(PA).
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- Balcilar, Mehmet & Ozdemir, Huseyin & Agan, Busra, 2022. "Effects of COVID-19 on cryptocurrency and emerging market connectedness: Empirical evidence from quantile, frequency, and lasso networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
- Chowdhury, Mohammad Ashraful Ferdous & Abdullah, Mohammad & Alam, Masud & Abedin, Mohammad Zoynul & Shi, Baofeng, 2023. "NFTs, DeFi, and other assets efficiency and volatility dynamics: An asymmetric multifractality analysis," International Review of Financial Analysis, Elsevier, vol. 87(C).
- Elie Bouri & Afees A. Salisu & Rangan Gupta, 2023. "The predictive power of Bitcoin prices for the realized volatility of US stock sector returns," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-22, December.
- Abdullah, Mohammad & Chowdhury, Mohammad Ashraful Ferdous & Sulong, Zunaidah, 2023. "Asymmetric efficiency and connectedness among green stocks, halal tourism stocks, cryptocurrencies, and commodities: Portfolio hedging implications," Resources Policy, Elsevier, vol. 81(C).
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Keywords
Price–volatility cross-correlations; Asymmetric volatility; Cryptocurrency markets; MF-ADCCA; Asymmetric DCCA coefficients;All these keywords.
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