Unveiling the Co-Movement Between Central Bank Digital Currency, Twitter EPU, Volatility Index, and Geopolitical Uncertainty
DOI:
https://doi.org/10.62270/jirms.v6i4.129Keywords:
CBDC, Volatility index, Wavelet connectedness, Geopolitical uncertainty, Twitter-based economic policyAbstract
Purpose—There has been a lot of international interest in the association between central bank digital currencies (CBDCs) and economic instability, as the CBDCs are gaining momentum among policymakers and investors. The CBDC Development Index (CBDCDI) is an instrument that has been used to measure the progress of the central bank digital currency projects across the globe. Each operational definition has quantifiable indicators, such as project stage, frequency of updating, and weighting of the economic size (GDP), and more so, facilitates quantitative transparency by using standardized and reproducible measures, as opposed to subjective reports. As the digital currency issued by central banks has become a competitive alternative to cash and has been discussed and announced in relation to policies, the returns of Bitcoin can be influenced.
Study Design/methodology/approach—In a bid to find out the relevance of CBDC based on Partial Wavelet Coherence (PWC) and Multiple Wavelet Coherence (MWC) on weekly data between January 2015 and December 2022, this study will analyze the co-movement of the CBDC, volatility index, Twitter-based economic policy, and geopolitical uncertainty.
Findings: The results of the study indicate that there is a positive, significant relationship between CBDC, TEP, VI, and GPU across the sample period, which means that economic shocks and uncertainty play a significant role in attracting sustainable financial instruments under different combinations of time frequencies.
Practical Implications—There are some limitations to this study, such as the limitation of the availability of data and a short time horizon. Implications: The findings may be utilized by the bank managers, legislators, and scholars to focus closer on the aspects related to CBDCs.
Originality/Value— With a unique concept that piques scholars' interest, this work offers insight into a novel research question. By combining Twitter-based policy uncertainty, volatility, and geopolitical risk with CBDC attention inside a wavelet time frequency framework, an area with little empirical research to date, the study makes a novel contribution
References
Aharon, D. Y., Demir, E., Lau, C. K. M., & Zaremba, A. (2022). Twitter-Based uncertainty and cryptocurrency returns. Research in International Business and Finance, 59, 101546. DOI: https://doi.org/10.1016/j.ribaf.2021.101546
Akdag, S., İskenderoglu, Ö., & Alola, A. A. (2020). The volatility spillover effects among risk appetite indexes: insight from the VIX and the rise. Letters in Spatial and Resource Sciences, 13(1), 49-65. DOI: https://doi.org/10.1007/s12076-020-00244-3
Akhtaruzzaman, M., Boubaker, S., & Sensoy, A. (2021). Financial contagion during COVID–19 crisis. Finance research letters, 38, 101604. DOI: https://doi.org/10.1016/j.frl.2020.101604
Aloui, C., Hkiri, B., Hammoudeh, S., & Shahbaz, M. (2018). A multiple and partial wavelet analysis of the oil price, inflation, exchange rate, and economic growth nexus in Saudi Arabia. Emerging Markets Finance and Trade, 54(4), 935-956. DOI: https://doi.org/10.1080/1540496X.2017.1423469
Al-Thaqeb, S. A., & Algharabali, B. G. (2019). Economic policy uncertainty: A literature review. The Journal of Economic Asymmetries, 20, e00133. DOI: https://doi.org/10.1016/j.jeca.2019.e00133
Al‐Thaqeb, S. A., Algharabali, B. G., & Alabdulghafour, K. T. (2022). The pandemic and economic policy uncertainty. International Journal of Finance & Economics, 27(3), 2784-2794. DOI: https://doi.org/10.1002/ijfe.2298
Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring economic policy uncertainty. The quarterly journal of economics, 131(4), 1593-1636. DOI: https://doi.org/10.1093/qje/qjw024
Bech, M. L., & Garratt, R. (2017). Central bank cryptocurrencies. BIS Quarterly Review September.
Bech, M. L., Hancock, J., & Wadsworth, A. (2020). Central securities depositories and securities settlement systems.
Bekaert, G., Engstrom, E. C., & Xu, N. R. (2022). The time variation in risk appetite and uncertainty. Management Science, 68(6), 3975-4004. DOI: https://doi.org/10.1287/mnsc.2021.4068
Bian, W., Ji, Y., & Wang, P. (2021). The crowding-out effect of central bank digital currencies: A simple and generalizable payment portfolio model. Finance Research Letters, 43, 102010. DOI: https://doi.org/10.1016/j.frl.2021.102010
Bloom, N. (2009). The impact of uncertainty shocks. econometrica, 77(3), 623-685. DOI: https://doi.org/10.3982/ECTA6248
Bouri, E., Shahzad, S. J. H., & Roubaud, D. (2020). Cryptocurrencies as hedges and safe-havens for US equity sectors. The Quarterly Review of Economics and Finance, 75, 294-307. DOI: https://doi.org/10.1016/j.qref.2019.05.001
Brooks, C. (2014). Introductory econometrics for finance. Cambridge university press. DOI: https://doi.org/10.1017/CBO9781139540872
Caldara, D., & Iacoviello, M. (2022). Measuring geopolitical risk. American economic review, 112(4), 1194-1225. DOI: https://doi.org/10.1257/aer.20191823
Can Ergün, Z., Cagli, E. C., & Durukan Salı, M. B. (2023). The interconnectedness across risk appetite of distinct investor types in Borsa Istanbul. Studies in Economics and Finance, 40(3), 425-444. DOI: https://doi.org/10.1108/SEF-09-2022-0460
Chang, C. L., McAleer, M., & Wang, Y. A. (2020). Herding behaviour in energy stock markets during the Global Financial Crisis, SARS, and ongoing COVID-19. Renewable and Sustainable Energy Reviews, 134, 110349. DOI: https://doi.org/10.1016/j.rser.2020.110349
Chang, H. L., Nie, W. Y., Chang, L. H., Cheng, H. W., & Yen, K. C. (2023). Cryptocurrency Momentum and VIX premium. Finance Research Letters, 57, 104196. DOI: https://doi.org/10.1016/j.frl.2023.104196
Chen, X., Miraz, M. H., Gazi, M. A. I., Rahaman, M. A., Habib, M. M., & Hossain, A. I. (2022). Factors affecting cryptocurrency adoption in digital business transactions: The mediating role of customer satisfaction. Technology in Society, 70, 102059. DOI: https://doi.org/10.1016/j.techsoc.2022.102059
Choi, K. J., Henry, R., Lehar, A., Reardon, J., & Safavi-Naini, R. (2021). A Proposal for a Canadian CBDC. Available at SSRN 3786426. DOI: https://doi.org/10.2139/ssrn.3786426
Demir, E., Gozgor, G., Lau, C. K. M., & Vigne, S. A. (2018). Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation. Finance Research Letters, 26, 145-149. DOI: https://doi.org/10.1016/j.frl.2018.01.005
Demirer, R., Gkillas, K., Gupta, R., & Pierdzioch, C. (2019). Time-varying risk aversion and realized gold volatility. The North American Journal of Economics and Finance, 50, 101048. DOI: https://doi.org/10.1016/j.najef.2019.101048
Diebold, F. X., & Yılmaz, K. (2014). On the network topology of variance decompositions: Measuring the connectedness of financial firms. Journal of econometrics, 182(1), 119-134. DOI: https://doi.org/10.1016/j.jeconom.2014.04.012
Dunbar, K. (2023). CBDC uncertainty: Financial market implications. International Review of Financial Analysis, 87, 102607. DOI: https://doi.org/10.1016/j.irfa.2023.102607
Dunbar, K., & Jiang, J. (2020). What do movements in financial traders’ net long positions reveal about aggregate stock returns?. The North American Journal of Economics and Finance, 51, 100908. DOI: https://doi.org/10.1016/j.najef.2019.01.005
Fatas, A. (2021). Can central bank digital currency transform digital payments?. Central Bank Digital Currency-Considerations, Projects, Outlook, 51-56.
Giannellis, N. (2022). Cryptocurrency market connectedness in Covid-19 days and the role of Twitter: Evidence from a smooth transition regression model. Research in International Business and Finance, 63, 101801. DOI: https://doi.org/10.1016/j.ribaf.2022.101801
González-Sánchez, M., Nave, J., & Rubio, G. (2020). Effects of uncertainty and risk aversion on the exposure of investment-style factor returns to real activity. Research in International Business and Finance, 53, 101236. DOI: https://doi.org/10.1016/j.ribaf.2020.101236
Goodell, J. W., & Shen, D. (2021). The Chinese sovereign digital currency as a catalyst for change: A new trilemma. Understanding cryptocurrency fraud: The challenges and headwinds to regulate digital currencies, 2, 177. DOI: https://doi.org/10.1515/9783110718485-014
Gunay, S. (2019). Impact of public information arrivals on cryptocurrency market: A case of twitter posts on ripple. East Asian economic review, 23(2), 149-168. DOI: https://doi.org/10.11644/KIEP.EAER.2019.23.2.359
Guo, Y., Li, P., & Li, A. (2021). Tail risk contagion between international financial markets during COVID-19 pandemic. International Review of Financial Analysis, 73, 101649. DOI: https://doi.org/10.1016/j.irfa.2020.101649
Hänska, M., & Bauchowitz, S. (2019). Can social media facilitate a European public sphere? Transnational communication and the Europeanization of Twitter during the Eurozone crisis. Social media+ society, 5(3), 2056305119854686. DOI: https://doi.org/10.1177/2056305119854686
Helmi, M. H., Çatık, A. N., & Akdeniz, C. (2023). The impact of central bank digital currency news on the stock and cryptocurrency markets: Evidence from the TVP-VAR model. Research in International Business and Finance, 65, 101968. DOI: https://doi.org/10.1016/j.ribaf.2023.101968
Hoang, Y. H., Ngo, V. M., & Vu, N. B. (2023). Central bank digital currency: A systematic literature review using text mining approach. Research in International Business and Finance, 64, 101889. DOI: https://doi.org/10.1016/j.ribaf.2023.101889
Huang, Y., & Luk, P. (2020). Measuring economic policy uncertainty in China. China economic review, 59, 101367. DOI: https://doi.org/10.1016/j.chieco.2019.101367
Irfan, M., Chen, Z., Adebayo, T. S., & Al-Faryan, M. A. S. (2022). Socio-economic and technological drivers of sustainability and resources management: demonstrating the role of information and communications technology and financial development using advanced wavelet coherence approach. Resources Policy, 79, 103038. DOI: https://doi.org/10.1016/j.resourpol.2022.103038
Jurado, K., Ludvigson, S. C., & Ng, S. (2015). Measuring uncertainty. American Economic Review, 105(3), 1177-1216. DOI: https://doi.org/10.1257/aer.20131193
Kim, Y., Lim, H., & Sohn, W. (2020). Which external shock matters in small open economies? Global risk aversion vs. US economic policy uncertainty. Japan and the World Economy, 54, 101011. DOI: https://doi.org/10.1016/j.japwor.2020.101011
Kristoufek, L., Janda, K., & Zilberman, D. (2016). Comovements of ethanol‐related prices: evidence from Brazil and the USA. Gcb Bioenergy, 8(2), 346-356. DOI: https://doi.org/10.1111/gcbb.12260
Kyriazis, N., Papadamou, S., Tzeremes, P., & Corbet, S. (2023). The differential influence of social media sentiment on cryptocurrency returns and volatility during COVID-19. The Quarterly Review of Economics and Finance, 89, 307-317. DOI: https://doi.org/10.1016/j.qref.2022.09.004
Larina, O. I., & Akimov, O. M. (2020). Digital money at the present stage: Key risks and development direction. Finance: theory and practice, 24(4), 18-30. DOI: https://doi.org/10.26794/2587-5671-2020-24-4-18-30
Lee, D. K. C., Yan, L., & Wang, Y. (2021). A global perspective on central bank digital currency. China Economic Journal, 14(1), 52-66. DOI: https://doi.org/10.1080/17538963.2020.1870279
Li, Z., Yang, C., & Huang, Z. (2022). How does the fintech sector react to signals from central bank digital currencies?. Finance Research Letters, 50, 103308. DOI: https://doi.org/10.1016/j.frl.2022.103308
Masciandaro, D. (2018). Central Bank digital cash and cryptocurrencies: insights from a new Baumol–Friedman demand for money. Australian Economic Review, 51(4), 540-550. DOI: https://doi.org/10.1111/1467-8462.12304
Masciandaro, D., Peia, O., & Romelli, D. (2024). Central bank communication and social media: From silence to Twitter. Journal of Economic Surveys, 38(2), 365-388. DOI: https://doi.org/10.1111/joes.12550
Mihanović, H., Orlić, M., & Pasarić, Z. (2009). Diurnal thermocline oscillations driven by tidal flow around an island in the Middle Adriatic. Journal of Marine Systems, 78, S157-S168. DOI: https://doi.org/10.1016/j.jmarsys.2009.01.021
Morales-Resendiz, R., Ponce, J., Picardo, P., Velasco, A., Chen, B., Sanz, L., ... & Hodge, A. (2021). Implementing a retail CBDC: Lessons learned and key insights. Latin American Journal of Central Banking, 2(1), 100022. DOI: https://doi.org/10.1016/j.latcb.2021.100022
Nazlioglu, S., Soytas, U., & Gupta, R. (2015). Oil prices and financial stress: A volatility spillover analysis. Energy policy, 82, 278-288. DOI: https://doi.org/10.1016/j.enpol.2015.01.003
Nguyen, L. T. M., & Nguyen, P. T. (2024). Do crypto investors wait and see during policy uncertainty? An examination of the dynamic relationships between policy uncertainty and exchange inflows of Bitcoin. Review of Behavioral Finance, 16(2), 234-247. DOI: https://doi.org/10.1108/RBF-01-2023-0013
Onsare, C. (2017). Social media misinformation in Kenya: an analysis of Twitter messages during the Chase Bank collapse. Emerging Trends in Information and Knowledge Management, 487.
Ozili, P. K. (2023). Central bank digital currency research around the World: a review of literature. Journal of Money Laundering Control, 26(2), 215-226. DOI: https://doi.org/10.1108/JMLC-11-2021-0126
Ozturkcan, S., Senel, K., & Ozdinc, M. (2025). Framing the Central Bank digital currency (CBDC) revolution. Technology Analysis & Strategic Management, 37(4), 462-479. DOI: https://doi.org/10.1080/09537325.2022.2099261
Peruffo, L., Cunha, A. M., & Ferrari Haines, A. E. (2023). China’s central bank digital currency (CBDC): an assessment of money and power relations. New Political Economy, 28(6), 881-896. DOI: https://doi.org/10.1080/13563467.2023.2196064
Polyzos, E. (2023). Inflation and the war in Ukraine: Evidence using impulse response functions on economic indicators and Twitter sentiment. Research in International Business and Finance, 66, 102044. DOI: https://doi.org/10.1016/j.ribaf.2023.102044
Prodan, S., Dabija, D. C., & Marincean, L. (2023, July). Exploring consumer sentiment on central bank digital currencies: a Twitter analysis from 2021 to 2023. In Proceedings of the International Conference on Business Excellence (Vol. 17, No. 1, pp. 1085-1102). Sciendo. DOI: https://doi.org/10.2478/picbe-2023-0098
Qadan, M., & Idilbi-Bayaa, Y. (2020). Risk appetite and oil prices. Energy Economics, 85, 104595. DOI: https://doi.org/10.1016/j.eneco.2019.104595
Rehman, M. A., Chopra, R., & Yadav, A. (2025). Co-moment Insights from environmental sustainability with financial markets dynamics. Computational Economics, 66(4), 2959-2985. DOI: https://doi.org/10.1007/s10614-024-10814-y
Rehman, M. A., Sabir, S. A., Javed, M. Z., & Mahmood, H. (2024). The connectedness knowledge from investors’ sentiments, financial crises, and trade policy: An economic perspective. Journal of the Knowledge Economy, 15(4), 20038-20062. DOI: https://doi.org/10.1007/s13132-024-01951-8
Rej, S., Bandyopadhyay, A., Mahmood, H., Murshed, M., & Mahmud, S. (2022). The role of liquefied petroleum gas in decarbonizing India: fresh evidence from wavelet–partial wavelet coherence approach. Environmental Science and Pollution Research, 29(24), 35862-35883. DOI: https://doi.org/10.1007/s11356-021-17471-w
Principe, V. A. (2024). Web3 e esportes: como a tecnologia blockchain pode auxiliar os modelos de negócios nos esportes.
Sandner, P. G., Gross, J., Grale, L., & Schulden, P. (2020). The digital programmable euro, Libra and CBDC: Implications for European banks. Libra and CBDC: Implications for European Banks (July 29, 2020). DOI: https://doi.org/10.2139/ssrn.3663142
Sangeetha, S., & Latha, A. (2023, June). Sentimental analysis of CBDC tweets using machine learning and deep learning techniques. In 2023 2nd International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA) (pp. 1-6). IEEE. DOI: https://doi.org/10.1109/ICAECA56562.2023.10199561
Scharnowski, S. (2022). Central bank speeches and digital currency competition. Finance Research Letters, 49, 103072. DOI: https://doi.org/10.1016/j.frl.2022.103072
Sharif, A., Aloui, C., & Yarovaya, L. (2020). COVID-19 pandemic, oil prices, stock market, geopolitical risk and policy uncertainty nexus in the US economy: Fresh evidence from the wavelet-based approach. International review of financial analysis, 70, 101496. DOI: https://doi.org/10.1016/j.irfa.2020.101496
Shen, W., & Hou, L. (2021). China's central bank digital currency and its impacts on monetary policy and payment competition: Game changer or regulatory toolkit?. Computer Law & Security Review, 41, 105577. DOI: https://doi.org/10.1016/j.clsr.2021.105577
Sinelnikova-Muryleva, E. V. (2020). Central bank digital currencies: Potential risks and benefits. Voprosy Ekonomiki, (4). DOI: https://doi.org/10.32609/0042-8736-2020-4-147-159
Sissoko, C. (2021). The nature of money in a convertible currency world. Review of Economic Analysis (REA), 13(1), 1-43. DOI: https://doi.org/10.15353/rea.v13i1.1771
Tata, F. (2023). Proposing an interval design feature to Central Bank Digital Currencies. Research in International Business and Finance, 64, 101898. DOI: https://doi.org/10.1016/j.ribaf.2023.101898
Tong, W., & Jiayou, C. (2021). A study of the economic impact of central bank digital currency under global competition. China Economic Journal, 14(1), 78-101. DOI: https://doi.org/10.1080/17538963.2020.1870282
Torrence, C., & Compo, G. P. (1998). A practical guide to wavelet analysis. Bulletin of the American Meteorological society, 79(1), 61-78. DOI: https://doi.org/10.1175/1520-0477(1998)079<0061:APGTWA>2.0.CO;2
Torrence, C., & Webster, P. J. (1999). Interdecadal changes in the ENSO–monsoon system. Journal of climate, 12(8), 2679-2690. DOI: https://doi.org/10.1175/1520-0442(1999)012<2679:ICITEM>2.0.CO;2
Umar, Z., Jareño, F., & Escribano, A. (2021). Oil price shocks and the return and volatility spillover between industrial and precious metals. Energy Economics, 99, 105291. DOI: https://doi.org/10.1016/j.eneco.2021.105291
van Oordt, M. R. (2022). Discussion of “Central bank digital currency: Stability and information”. Journal of Economic Dynamics and Control, 142, 104503. DOI: https://doi.org/10.1016/j.jedc.2022.104503
Wang, H. (2023). How to understand China's approach to central bank digital currency?. Computer Law & Security Review, 50, 105788. DOI: https://doi.org/10.1016/j.clsr.2022.105788
Wang, Y., Lucey, B. M., Vigne, S. A., & Yarovaya, L. (2022). The effects of central bank digital currencies news on financial markets. Technological Forecasting and Social Change, 180, 121715. DOI: https://doi.org/10.1016/j.techfore.2022.121715
Wang, Y., Wei, Y., Lucey, B. M., & Su, Y. (2023). Return spillover analysis across central bank digital currency attention and cryptocurrency markets. Research in International Business and Finance, 64, 101896. DOI: https://doi.org/10.1016/j.ribaf.2023.101896
Wu, W., Tiwari, A. K., Gozgor, G., & Leping, H. (2021). Does economic policy uncertainty affect cryptocurrency markets? Evidence from Twitter-based uncertainty measures. Research in International Business and Finance, 58, 101478. DOI: https://doi.org/10.1016/j.ribaf.2021.101478
Xiaofen, T., Qianqian, C., & Qian, Z. (2022). Global Risk Appetite, US Economic Policy Uncertainties and Cross-Border Capital Flow. China Economist, 17(5), 2-18.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Sarah Nawazish

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution (CC-BY) 4.0 License that allows others to share the work with an acknowledgment of the work’s authorship and initial publication in this journal.


