Volatility Spillovers in the Economics of Cryptocurrencies and Financial Markets
https://doi.org/10.47703/2789-8253-2026-2-24-36
Abstract
With the increasing role of cryptocurrencies in the global financial system, the analysis of the mechanisms by which volatility transfers between digital and traditional assets is becoming particularly relevant.
The purpose of the study is to assess the degree, directions, and temporal variability of volatility spillovers between Bitcoin, leading cryptocurrencies, and traditional financial instruments.
Using daily data and both static and rolling-window estimates, the analysis assesses how shocks to volatility are transmitted between cryptocurrency and macro-financial markets. The results of the study showed that the Total Spillover Index (TSI) in the static model is 28.37 %, while in the dynamic model it reaches an average of 35.9 %, with peak values up to 45.25 % in 2022. It has been established that Bitcoin acts as a net transmitter of volatility: the average level of transmitted effects is 60.31 %, received effects are 50.59 %, and the net spillover is +9.72 %. Moreover, Bitcoin’s place in the network is state-dependent to some extent: while it acts as a net transmitter in the average, speculative episodes in alternative cryptocurrencies can cause Bitcoin to act as a receiver of volatility shocks. The results indicate a high degree of internal connectivity in the cryptocurrency market, with limited integration with the traditional financial system, and a pronounced temporary variability in the structure of volatility interactions. These findings have implications for portfolio diversification, risk management, and the ongoing integration of digital assets into the global financial system.
About the Authors
S. Celik
Izmir Katip Celebi University
Turkey
Turkey
Saban Celik, PhD, Associate Professor
Izmir
A. Duman
Izmir Katip Celebi University
Turkey
Turkey
Aslı Duman, PhD Student
Izmir
References
1. Adelopo, I., & Luo, X. (2025). Interconnectedness among cryptocurrencies and financial markets : a systematic literature review. Digital Finance, 7, 1119–1171. doi: 10.1007/s42521-025-00155-2
2. Bouri, E., Molnár, P., Azzi, G., Roubaud, D., & Hagfors, L. I. (2017). On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier? Finance Research Letters, 20, 192–198. doi: 10.1016/j.frl.2016.09.025
3. Corbet, S., Meegan, A., Larkin, C., Lucey, B., & Yarovaya, L. (2018). Exploring the dynamic relationships between cryptocurrencies and other financial assets. Economics Letters, 165, 28–34. doi: 10.1016/j.econlet.2018.01.004
4. Diebold, F. X., & Yilmaz, K. (2009). Measuring financial asset return and volatility spillovers, with application to global equity markets. The Economic Journal, 119(534), 158–171. doi: 10.1111/j.1468-0297.2008.02208.x
5. Diebold, F. X., & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57–66. doi: 10.1016/j.ijforecast.2011.02.006
6. Diebold, F. X., & Yilmaz, K. (2014). On the network topology of variance decompositions: Measuring the connectedness of financial firms. Journal of Econometrics, 182(1), 119–134. doi: 10.1016/j.jeconom.2014.04.012
7. Félix, J. A., Fernández-Pérez, A., & Sosvilla-Rivero, S. (2020). Distant or close cousins: Connectedness between cryptocurrencies and traditional currencies volatilities. Journal of International Financial Markets Institutions and Money, 67, 101219. doi: 10.1016/j.intfin.2020.101219
8. Goodell, J. W., & Goutte, S. (2021). Co-movement of COVID-19 and Bitcoin: Evidence from wavelet coherence analysis. Finance Research Letters, 38, 101625. doi: 10.1016/j.frl.2020.101625
9. Ji, Q., Bouri, E., Lau, C. K. M., & Roubaud, D. (2019). Dynamic connectedness and integration in cryptocurrency markets. International Review of Financial Analysis, 63, 257–272. doi: 10.1016/j.irfa.2018.12.002
10. Kammoun, W. M. (2026). Return and volatility spillover drivers among conventional cryptocurrencies. Digital Finance, 8(1). doi: 10.1007/s42521-025-00167-y
11. Katsiampa, P. (2019). Volatility co-movement between Bitcoin and Ether. Finance Research Letters, 30, 221–227. doi: 10.1016/j.frl.2018.10.005
12. Kurka, J. (2019). Do cryptocurrencies and traditional asset classes influence each other? Finance Research Letters, 31, 38–46. doi: 10.1016/j.frl.2019.04.018
13. Mensi, W., Belghouthi, H. E., Kharusi, S. A., & Kang, S. H. (2025). Tail risk contagion and connectedness between clean cryptocurrency, green assets and commodity markets. International Review of Financial Analysis, 105, 104370. doi: 10.1016/j.irfa.2025.104370
14. Pesaran, H. H., & Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics Letters, 58(1), 17–29. doi: 10.1016/S0165-1765(97)00214-0
15. Polat, O. (2023). Dynamic Volatility Connectedness among Cryptocurrencies: Evidence from Time-Frequency Connectedness Networks. Anadolu Üniversitesi Sosyal Bilimler Dergisi, 23(1), 29. doi: 10.18037/ausbd.1272534
16. Rehman, S. U., Ahmad, T., Desheng, W. D., & Karamoozian, A. (2024). Analyzing selected cryptocurrencies spillover effects on global financial indices: Comparing risk measures using conventional and eGARCH-EVT-Copula approaches. arXiv (Cornell University). doi: 10.48550/arxiv.2407.15766
17. Wu, M., Wang, L., & Yang, H. (2024). Heterogeneity in the volatility spillover of cryptocurrencies and exchanges. Financial Innovation, 10(1), 85. doi: 10.1186/s40854-023-00585-0
Review
For citations:
Celik S., Duman A. Volatility Spillovers in the Economics of Cryptocurrencies and Financial Markets. Eurasian Journal of Economic and Business Studies. 2026;70(2):24-36. https://doi.org/10.47703/2789-8253-2026-2-24-36
Views:
18
JATS XML
Email this article 