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On cryptocurrencies as an independent asset class: Long-horizon and COVID-19 pandemic era decoupling from global sentiments

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  • Sifat, Imtiaz

Abstract

Employing high-dimensional stochastic-volatility commonality tests on crypto-assets against a basket of global investor sentiment proxies, we report new evidence that the cryptocurrency market is decoupled from global sentiments. Our approach's novelty resides in employment of appropriate sources of risk and uncertainty and two comprehensive indices (CRIX and VCRIX) that permit treating cryptocurrencies as a united pool from 2016 to 2021. Our consolidated findings suggest nugatory association between cryptocurrencies and global risk, risk aversion, and uncertainty. Further COVID-19 resampling reinforces long-horizon results. These findings bolster the growing wave of support for recognizing crypto-assets as an independent asset class.

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  • Sifat, Imtiaz, 2021. "On cryptocurrencies as an independent asset class: Long-horizon and COVID-19 pandemic era decoupling from global sentiments," Finance Research Letters, Elsevier, vol. 43(C).
    • Handle: RePEc:eee:finlet:v:43:y:2021:i:c:s1544612321000945
    DOI: 10.1016/j.frl.2021.102013
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    1. Assaf, Ata & Bhandari, Avishek & Charif, Husni & Demir, Ender, 2022. "Multivariate long memory structure in the cryptocurrency market: The impact of COVID-19," International Review of Financial Analysis, Elsevier, vol. 82(C).
    2. Hadhri, Sinda, 2023. "Do cryptocurrencies feel the music?," International Review of Financial Analysis, Elsevier, vol. 89(C).
    3. Banerjee, Ameet Kumar & Akhtaruzzaman, Md & Dionisio, Andreia & Almeida, Dora & Sensoy, Ahmet, 2022. "Nonlinear nexus between cryptocurrency returns and COVID-19 news sentiment," Journal of Behavioral and Experimental Finance, Elsevier, vol. 36(C).
    4. Bouteska, Ahmed & Mefteh-Wali, Salma & Dang, Trung, 2022. "Predictive power of investor sentiment for Bitcoin returns: Evidence from COVID-19 pandemic," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    5. Jiang, Wen & Xu, Qiuhua & Zhang, Ruige, 2022. "Tail-event driven network of cryptocurrencies and conventional assets," Finance Research Letters, Elsevier, vol. 46(PB).
    6. Lin, Xudong & Meng, Yiqun & Zhu, Hao, 2023. "How connected is the crypto market risk to investor sentiment?," Finance Research Letters, Elsevier, vol. 56(C).
    7. Apergis, Nicholas, 2022. "COVID-19 and cryptocurrency volatility: Evidence from asymmetric modelling," Finance Research Letters, Elsevier, vol. 47(PA).
    8. Kim, Jang Ho, 2022. "Analyzing diversification benefits of cryptocurrencies through backfill simulation," Finance Research Letters, Elsevier, vol. 50(C).
    9. Díaz, Antonio & Esparcia, Carlos & Huélamo, Diego, 2023. "Stablecoins as a tool to mitigate the downside risk of cryptocurrency portfolios," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    10. Rachida Ben Ahmed Daho, 2021. "The Relationship between Cryptocurrency Prices and Share Prices of Technology Companies in Light of Covid-19," International Journal of Economics and Financial Issues, Econjournals, vol. 11(5), pages 37-44.
    11. Ştefan Cristian Gherghina & Liliana Nicoleta Simionescu, 2023. "Exploring the asymmetric effect of COVID-19 pandemic news on the cryptocurrency market: evidence from nonlinear autoregressive distributed lag approach and frequency domain causality," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-58, December.
    12. Huynh, Nhan & Phan, Hoa, 2023. "Emotions in the crypto market: Do photos really speak?," Finance Research Letters, Elsevier, vol. 55(PB).

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