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FINANCIAL ECONOMICS

An investigation of financial contagion between cryptocurrency and equity markets: Evidence from developed and emerging markets

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Article: 2203432 | Received 26 Sep 2022, Accepted 12 Apr 2023, Published online: 29 Apr 2023

References

  • Ampountolas, A. (2022). Cryptocurrencies intraday high-frequency volatility spillover effects using univariate and multivariate GARCH models. International Journal of Financial Studies, 10(3), 51. https://doi.org/10.3390/ijfs10030051
  • Begušić, S., Kostanjčar, Z., Stanley, H. E., & Podobnik, B. (2018). Scaling properties of extreme price fluctuations in Bitcoin markets. Physica A: Statistical Mechanics and Its Applications, 510, 400–21. https://doi.org/10.1016/j.physa.2018.06.131
  • Bhosale, J., & Mavale, S. (2018). Volatility of select crypto-currencies: A comparison of Bitcoin, Ethereum and Litecoin. Annual Research Journal of SCMS, Pune, (6), 132–141. https://www.scmspune.ac.in/journal/pdf/current/Paper%2010%20-%20Jaysing%20Bhosale.pdf
  • Biju, A. V., Mathew, A. M., Nithi Krishna, P. P., & Akhil, M. P. (2022). Is the future of Bitcoin safe? A triangulation approach in the reality of BTC market through a sentiments analysis. Digital Finance, (4), 275–290. https://link.springer.com/article/10.1007/s42521-022-00052-y
  • Buchwalter, B. (June 4, 2019). Contagious Volatility. Proceedings of Paris December 2019 Finance Meeting EUROFIDAI - ESSEC. https://doi.org/10.2139/ssrn.3478511
  • Catania, L., & Grassi, S. (2017). Modelling Crypto-currencies Financial Time-series. Tor Vergata University.
  • Chinzara, Z., & Aziakpon, M. J. Dynamic returns linkages and volatility transmission between South African and world major stock markets. (2009). Journal of Studies in Economics and Econometrics, 33(3), 69–94. 33(3): 69-94. Studies in Economics and Econometrics. https://doi.org/10.1080/10800379.2009.12106473
  • Corbet, S. Lucey, B., Yarovaya, L., Urquhart, A. (2019). Cryptocurrencies as a financial asset: A systematic analysis. International Review of Financial Analysis, 62, 182–189. https://centaur.reading.ac.uk/79186/1/CorbetLuceyUrquhartYarovaya2018.pdf
  • Dajčman, S. (2013). Co-exceedances in Eurozone sovereign bond markets: Was there a contagion during the global financial crisis and the Eurozone debt crisis. Acta Polytechnica Hungarica, 10(3), 135–152. http://www.epa.hu/02400/02461/00041/pdf/EPA02461_acta_polytechnica_hungarica_2013_03_135-152.pdf
  • Dewandaru, G., Masih, R., & Masih, M. (2018). Unraveling the financial contagion in European stock markets during financial crises: Multi-timescale analysis. Emerging Markets Finance and Trade, 54(4), 859–880. https://doi.org/10.1080/1540496X.2016.1266614
  • 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. https://doi.org/10.1016/j.ijforecast.2011.02.006
  • Dutta, A., Das, D., Jana, R. K., & Vo, X. V. (2020). COVID-19 and oil market crash: Revisiting the safe haven property of gold and Bitcoin. Resources Policy, 69, 101816. https://doi.org/10.1016/j.resourpol.2020.101816
  • Engle, R. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business & Economic Statistics, 20(3), 339–350. https://doi.org/10.1198/073500102288618487
  • Fakhfekh, M., & Jeribi, A. (2020). Volatility dynamics of crypto-currencies’ returns: Evidence from asymmetric and long memory GARCH models. Research in International Business and Finance, 51, 101075. https://doi.org/10.1016/j.ribaf.2019.101075
  • Gençay, R., Selçuk, F., & Whitcher, B. (2003). Systematic risk and timescales. Quantitative Finance, 3(2), 108. http://repository.bilkent.edu.tr/bitstream/handle/11693/24504/bilkent-research-paper.pdf?sequence=1
  • Gupta, H., & Chaudhary, R. (2022). An empirical study of volatility in cryptocurrency market. Journal of Risk and Financial Management, 15(11), 513. https://doi.org/10.3390/jrfm15110513
  • Hashim, K. K., & Masih, A. (2015). Stock Market Volatility and Exchange Rates: MGARCH-DCC and wavelet approaches. University Library of Munich.
  • Hung, N. T. (2022). Asymmetric connectedness among S&P 500, crude oil, gold and Bitcoin. Managerial Finance, 48(4), 587–610. https://doi.org/10.1108/MF-08-2021-0355
  • Huynh, T. L. D., Ahmed, R., Nasir, M. A., Shahbaz, M., & Huynh, N. Q. A. (2021). The nexus between black and digital gold: Evidence from US markets. Annals of Operations Research, 1–26. https://doi.org/10.1007/s10479-021-04192-z
  • In, F., & Kim, S. (2013). An Introduction to Wavelet Theory in Finance: A Wavelet Multiscale Approach. World Scientific.
  • Iyer, T. (2022). Cryptic Connections: Spillovers between Crypto and Equity Markets. International Monetary Fund.
  • Karim, B. A., Abdul-Rahman, A., HWANG, J. Y. T., & Kadri, N. (2021). Portfolio diversification benefits of cryptocurrencies and ASEAN-5 stock markets. The Journal of Asian Finance, Economics and Business, 8(6), 567–577.
  • Khan, M., & Khan, M. (2021). Cryptomarket volatility in times of COVID-19 pandemic: application of GARCH models. Economic Research Guardian, 11(2), 2–13.
  • Kumar, A. S., & Anandarao, S. (2019). Volatility spillover in crypto-currency markets: Some evidences from GARCH and wavelet analysis. Physica A: Statistical Mechanics and Its Applications, 524, 448–458. https://doi.org/10.1016/j.physa.2019.04.154
  • Kumar, A., Iqbal, N., Mitra, S. K., Kristoufek, L., & Bouri, E. (2022). Connectedness among major cryptocurrencies in standard times and during the COVID-19 outbreak. Journal of International Financial Markets, Institutions and Money, 77, 101523. https://doi.org/10.1016/j.intfin.2022.101523
  • Li, Z., Dong, H., Floros, C., Charemis, A., & Failler, P. (2022). Re-examining Bitcoin volatility: A CAViaR-based approach. Emerging Markets Finance and Trade, 58(5), 1320–1338. https://doi.org/10.1080/1540496X.2021.1873127
  • Lucey, B. M., Vigne, S. A., Yarovaya, L., & Wang, Y. (2022). The cryptocurrency uncertainty index. Finance Research Letters, 45, 102147. https://doi.org/10.1016/j.frl.2021.102147
  • Murty, S., Victor, V., & Fekete-Farkas, M. (2022). Is Bitcoin a safe haven for Indian investors? A GARCH volatility analysis. Journal of Risk and Financial Management, 15(7), 317. https://doi.org/10.3390/jrfm15070317
  • Naimy, V., Haddad, O., Fernández-Avilés, G., El Khoury, R., & Trinidad Segovia, J. E. (2021). The predictive capacity of GARCH-type models in measuring the volatility of crypto and world currencies. PloS One, 16(1), e0245904. https://doi.org/10.1371/journal.pone.0245904
  • Othman, A. H. A., Alhabshi, S. M., & Haron, R. (2019). The effect of symmetric and asymmetric information on volatility structure of crypto-currency markets: A case study of Bitcoin currency. Journal of Financial Economic Policy, 11(3), 432–450. https://doi.org/10.1108/JFEP-10-2018-0147
  • Özdemir, O. (2022). Cue the volatility spillover in the cryptocurrency markets during the COVID-19 pandemic: Evidence from DCC-GARCH and wavelet analysis. Financial Innovation, 8(1), 1–38. https://doi.org/10.1186/s40854-021-00319-0
  • Percival, D. P. (1995). On estimation of the wavelet variance. Biometrika, 83(2), 619–631. https://doi.org/10.1093/biomet/82.3.619
  • Percival, D. B., & Walden, A. T. (2000). In Wavelet methods for time series analysis (Vol. 4). Cambridge university press. https://web.archive.org/web/20170808215030id_/http://tocs.ulb.tu-darmstadt.de/179403451.pdf
  • Percival, D. B., & Walden, A. T. (2006). Wavelet Methods for Time Series Analysis (Vol. 4). Cambridge University Press.
  • Ranta, M. (2010). Wavelet Multiresolution Analysis of Financial Time Series. Vaasan yliopisto.
  • Saiti, B., Bacha, O. I., & Masih, M. (2016). Testing the conventional and Islamic financial market contagion: Evidence from wavelet analysis. Emerging Markets Finance and Trade, 52(8), 1832–1849. https://doi.org/10.1080/1540496X.2015.1087784
  • Saleh, F. (2019). Volatility and Welfare in a Crypto Economy. McGill University. https://www.tse-fr.eu/sites/default/files/TSE/documents/sem2018/finance/saleh.pdf
  • Salisu, A. A., & Ogbonna, A. E. (2021). The return volatility of cryptocurrencies during the COVID-19 pandemic: Assessing the news effect. Global Finance Journal, 54, 100641. https://doi.org/10.1016/j.gfj.2021.100641
  • Shahzad, S. J. H., Bouri, E., Rehman, M. U., & Roubaud, D. (2022). The hedge asset for BRICS stock markets: Bitcoin, gold or VIX. The World Economy, 45(1), 292–316. https://doi.org/10.1111/twec.13138
  • Srnic, B. S. (2014). Impact of Economic Crisis Announcements on BRIC Market Volatility. Faculty of Social sciences, Charles University in Prague.
  • van de Schootbrugge, S., 2022. How crypto affects the global stock market and equities. [online] macro hive. Available at: https://macrohive.com/deep-dives/how-crypto-impacts-global-equity-prices/ [Retrieved July 20, 2022].
  • Xu, F., Bouri, E., & Cepni, O. (2022). Blockchain and crypto-exposed US companies and major cryptocurrencies: The role of jumps and co-jumps. Finance Research Letters, 50, 103201. https://doi.org/10.1016/j.frl.2022.103201
  • Yousaf, I., Ali, S., Bouri, E., & Saeed, T. (2022). Information transmission and hedging effectiveness for the pairs crude oil-gold and crude oil-Bitcoin during the COVID-19 outbreak. Economic Research-Ekonomska Istraživanja, 35(1), 1913–1934. https://doi.org/10.1080/1331677X.2021.1927787