Investigation of the impact of uncertainty indices on Bitcoin volatility using the ARDL model
DOI:
https://doi.org/10.22394/1993-7601-2024-74-35-50Keywords:
Bitcoin, криптовалюта, реализованная волатильность, ARDL модель, индексы неопределенности, COVID‑19Abstract
The article uses the ARDL model to study the impact of the VIX index and the indices of economic and market uncertainty based on data from the social network X (formerly Twitter, blocked in the Russian Federation) on the volatility of Bitcoin. To estimate the unobservable cryptocurrency volatility, the author uses a nonparametric estimator derived from 5-minute data on Bitcoin closing prices, considering adjustments if there are gaps within the day. The paper considers the data for the period from 02.01.2018 to 30.12.2022, divided into two half-periods: pre-COVID-19 period (from 02.01.2018 to 28.02.2020) and post-COVID-19 period (from 01.03.2020 to 31.12.2022). According to the results obtained by estimating the ARDL model at different half-periods, in the long term, there is a significant negative VIX index impact on the realized volatility of Bitcoin. This paper observed a short-term (instantaneous) significant positive effect on the realized volatility of Bitcoin for the index of market uncertainty TMU_ENG in the pre-COVID-19 period. The identified significant effects make it possible to use the VIX and TMU_ENG indices to improve the forecast quality in models for the volatility of the Bitcoin cryptocurrency.Agencies
Author is grateful for the financial support of the Russian Science Foundation, grant № 24-28-00280 (https://rscf.ru/project/24-28-00280/).Downloads
References
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Nouir J. B., Hamida H. B. H. (2023). How do economic policy uncertainty and geopolitical risk drive Bitcoin volatility? Research in International Business and Finance, 64, 101809. DOI: 10.1016/j.ribaf.2022.101809.
Pesaran M. H., Shin Y., Smith R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16 (3), 289–326. DOI: 10.1002/jae.616.
Shaikh I. (2019). On the relationship between economic policy uncertainty and the implied volatility index. Sustainability, 11 (6), 1–11. DOI: 10.3390/su11061628.
Simran, Sharma A. K. (2023). Asymmetric impact of economic policy uncertainty on cryptocurrency market: Evidence from NARDL approach. The Journal of Economic Asymmetries, 27, e00298. DOI: 10.1016/j.jeca.2023.e00298.
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Wang J., Lu X., He F., Ma F. (2020). Which popular predictor is more useful to forecast international stock markets during the coronavirus pandemic: VIX vs EPU? International Review of Financial Analysis, 72. DOI: 10.1016/j.irfa.2020.101596.
White H., Kim T.-H., Manganelli S. (2015). VAR for VaR: Measuring tail dependence using multivariate regression quantiles. Journal of Econometrics, 187, 169–188. DOI: 10.1016/j.jeconom.2015.02.004.
Yu J., Shi X., Guo D., Yang L. (2021). Economic policy uncertainty (EPU) and firm carbon emissions: Evidence using a China provincial EPU index. Energy Economics, 94. DOI: 10.1016/j.eneco.2020.105071.
