Pandemic Versus Financial Shocks: Comparison of Two Episodes on the Bitcoin Market
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Pandemic Versus Financial Shocks: Comparison of Two Episodes on the Bitcoin Market
Horky, Florian | Mutascu, Mihai | Fidrmuc, Jarko
Applied Economics Quarterly, Vol. 67 (2021), Iss. 2 : pp. 113–141
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Florian Horky, Zeppelin University Friedrichshafen, Am Seemooser Horn 20, 88045 Friedrichshafen, Germany.
Mihai Mutascu, corresponding author. Zeppelin University Friedrichshafen, Am Seemooser Horn 20, 88045 Friedrichshafen, Germany; Faculty of Economics and Business Administration West University of Timisoara, J. H. Pestalozzi St. 16, 300115, Timisoara, Romania; and LEO (Laboratoire d’Economie d’Orléans), UMR7322, Faculté de Droit d’Economie et de Gestion, University of Orléans, Rue de Blois – BP 26739, 45067, Orléans Cedex 2, France; e-mail: mihai.mutascu@zu.de, mihai.mutascu@gmail.com.
Jarko Fidrmuc, Zeppelin University Friedrichshafen, Am Seemooser Horn 20, 88045 Friedrichshafen, Germany; Mendel University in Brno, Faculty of Business and Economics, Zemědělská 1665, 613 00, Brno-sever-Černá Pole, Czech Republic; and Economic Institute in Bratislava, Slovak Academy of Sciences, Sancova No. 56, 811 05 Bratislava, Slovakia, e-mail: jarko.fidrmuc@zu.de, jarko.fidrmuc@gmail.com.
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References
-
Aguiar-Conraria, L./Azevedo, N./Soares, M. J. (2008): “Using Wavelets to Decompose the Time-Frequency Effects of Monetary Policy,” Physica A: Statistical Mechanics and its Applications 387, 2863–2878.
Google Scholar -
Atsalakis, G. S./Atsalaki, I. G./Pasiouras, F./Zopounidis, C. (2019): “Bitcoin Price Forecasting with Neuro-Fuzzy Techniques,” European Journal of Operational Research 276, 770–780.
Google Scholar -
Aysan, A. F./Demir, E./Gozgor, G./Lau, C. K. M. (2019): “Effects of the Geopolitical Risks on Bitcoin Returns and Volatility,” Research in International Business and Finance 47, 511–518.
Google Scholar -
Bajalinov, E./Duleba, S. (2020): “Seasonal Time Series Forecasting by the Walsh-Transformation Based Technique,” Central European Journal of Operation Research 28, 983–1001.
Google Scholar -
Bams, D./Blanchard, G./Honarvar, I./Lehnert, T. (2017): “Does Oil and Gold Price Uncertainty Matter for the Stock Market?,” Journal of Empirical Finance 44, 270–285.
Google Scholar -
Bank for International Settlements (2015): “Digital Currencies,” Bank for International Settlements, Basel. Retrieved from http://www.bis.org/cpmi/publ/d137.htm.
Google Scholar -
Baur, D. G./Dimpfl, T./Kuck, K. (2018): “Bitcoin, Gold and the US dollar – A Replication and Extension,” Finance Research Letters 25, 103–110.
Google Scholar -
Bedi, P./Nashier, T. (2020): “On the Investment Credentials of Bitcoin: A Cross-Currency Perspective,” Research in International Business and Finance 51, 1–21.
Google Scholar -
Binda, J. (2020): “Cryptocurrencies – Problems of the High-Risk Instrument Definition,” Investment Management and Financial Innovations 17, 227–241.
Google Scholar -
Bitfinex (2020): Bitfinex Dataset, retrieved from https://www.bitfinex.com/ on April 30, 2020.
Google Scholar -
Bolt, W./van Oordt, M. R. C. (2019): “On the value of virtual currencies,” Journal of Money, Credit and Banking 52, 835–862.
Google Scholar -
Borri, N. (2019): “Conditional Tail-Risk in Cryptocurrency Markets,” Journal of Empirical Finance 50, 1–19.
Google Scholar -
Ciaian, P./Rajcaniova, M./Kancs, D. A. (2016): “The Economics of BitCoin Price Formation,” Applied Economics 48, 1799–1815.
Google Scholar -
Conlon, T./Cotter, J./Gençay, R. (2018): “Long-Run Wavelet-Based Correlation for Financial Time Series,” European Journal of Operational Research 271, 676–696.
Google Scholar -
Conlon, T./McGee, R. (2020): “Safe Haven or Risky Hazard? Bitcoin during the Covid-19 Bear Market,” Finance Research Letters 35, 1–5.
Google Scholar -
Corbet, S./Larkin, C. J./Lucey, B. M. (2020): “The Contagion Effects of the COVID-19 Pandemic: Evidence from Gold and Cryptocurrencies,” Finance Research Letters 35, 1–7.
Google Scholar -
Das, D./Le Roux, C. L./Jana, R. K./Dutta, A. (2020): “Does Bitcoin Hedge Crude Oil Implied Volatility and Structural Shocks? A Comparison with Gold, Commodity and the US Dollar,” Finance Research Letters 36, 1–11.
Google Scholar -
Demir, E./Bilgin, M. H./Karabulut, G./Doker, A. C. (2020): “The Relationship between Cryptocurrencies and COVID-19 Pandemic,” Eurasian Economic Review 10, 349–360.
Google Scholar -
Donier, J./Bouchaud, J.‑P. (2015): “Why Do Markets Crash? Bitcoin Data Offers Unprecedented Insights,” PloS One 10, 1–11.
Google Scholar -
Drożdż, S./Minati, L./Oświȩcimka, P./Stanuszek, M./Wa̧torek, M. (2019): “Signatures of the Crypto-Currency Market Decoupling from the Forex,” Future Internet 11, 154.
Google Scholar -
Dyhrberg, A. H. (2016): “Bitcoin, gold and the dollar – A GARCH volatility analysis,” Finance Research Letters 16, 85–92.
Google Scholar -
European Central Bank (2015): Virtual Currency Schemes: A Further Analysis, European Central Bank, Frankfurt am Main.
Google Scholar -
Fantazzini, D./Zimin, S. (2020): “A Multivariate Approach for the Simultaneous Modelling of Market Risk and Credit Risk for Cryptocurrencies,” Journal of Industrial and Business Economics 47, 19–69.
Google Scholar -
Farge, M. (1992): “Wavelet Transforms and their Applications to Turbulence,” Annual Review of Fluid Mechanics 24, 395–457.
Google Scholar -
Fernández-Villaverde, J./Sanches, D. (2019): “Can Currency Competition Work?,” Journal of Monetary Economics 106, 1–15.
Google Scholar -
Fidrmuc, J./Kapounek, S./Junge, F. (2020): “Cryptocurrency Market Efficiency: Evidence from Time-Frequency Analysis,” Finance a Uver: Czech Journal of Economics & Finance 70, 121–144.
Google Scholar -
Figà-Talamanca, G./Patacca, M. (2020): “Disentangling the Relationship between Bitcoin and Market Attention Measures,” Journal of Industrial and Business Economics 47, 71–91.
Google Scholar -
Garcia, D./Tessone, C. J./Mavrodiev, P./Perony, N. (2014): “The Digital Traces of Bubbles: Feedback Cycles between Socio-Economic Signals in the Bitcoin Economy,” Journal of the Royal Society Interface 11, 1–8.
Google Scholar -
Giudici, G./Milne, A./Vinogradov, D. V. (2020): “Cryptocurrencies: Market Analysis and Perspectives,” Journal of Industrial & Business Economics 47, 1–18.
Google Scholar -
Grinsted, A./Moore, S J./Jevrejeva, C. (2004): “Application of the Cross Wavelet Transform and Wavelet Coherence to Geophysical Time Series,” Nonlinear Processes in Geophysics 11, 561–566.
Google Scholar -
Guesmi, K./Saadi, S./Abid, I./Ftiti, Z. (2019): “Portfolio Diversification with Virtual currency: Evidence from Bitcoin,” International Review of Financial Analysis 63, 431–437.
Google Scholar -
Haryanto, S./Subroto, A./Ulpah, M. (2020): “Disposition Effect and Herding Behavior in the Cryptocurrency Market,” Journal of Industrial and Business Economics 47(1), 115–132.
Google Scholar -
Hu, A. S./Parlour, C. A./Rajan, U. (2019): “Cryptocurrencies: Stylized Facts on a New Investible Instrument,” Financial Management 48, 1049–1068.
Google Scholar -
Hudgins, L./Friehe, C./Mayer, M. (1993): “Wavelet Transforms and Atmospheric Turbulence,” Physical Review Letters 71, 3279–3282.
Google Scholar -
Investing (2020): Investing Dataset, retrieved from https://www.investing.com on April 30, 2020.
Google Scholar -
Jo, H./Park, H./Shefrin, H. (2020): “Bitcoin and Sentiment,” Journal of Futures Markets, 2020, 1–19.
Google Scholar -
Johnson, J. (2020): “The Impact of COVID-19 on Bitcoin Trading Activity: A Preliminary Assessment,” SSRN, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3583162.
Google Scholar -
Kapounek, S./Kučerová, Z. (2019). “Historical Decoupling in the EU: Evidence from Time-Frequency Analysis,” International Review of Economics & Finance, 60, 265–280.
Google Scholar -
Kristoufek, L. (2015): “What are the Main Drivers of the Bitcoin Price? Evidence from Wavelet Coherence Analysis,” PloS one 10, 1–15.
Google Scholar -
Lansky, J. (2018): “Possible State Approaches to Cryptocurrencies,” Journal of Systems Integration 9, 19–31.
Google Scholar -
Liu, X./Cao, Y./Ma, C./Shen, L. (2019): “Wavelet-Based Option Pricing: An Empirical Study,” European Journal of Operational Research 272, 1132–1142.
Google Scholar -
Mihanović, H./Orlić, M./Pasrić, Z. (2009): “Diurnal Thermocline Oscillations Driven by Tidal Flow around an Island in the Middle Adriatic,” Journal of Marine Systems 78, 157–168.
Google Scholar -
Mutascu, M./Hegerty, S. W. (2020): “Capital-Flow Volatility and Economic Openness: A Wavelet Approach,” Applied Economics Quarterly 66, 291–318.
Google Scholar -
Ng, E. K. W./Chan, J. C. L. (2012): “Geophysical Applications of Partial Wavelet Coherence and Multiple Wavelet Coherence,” Journal of Atmospheric and Ocean Technology 29, 1845–1853.
Google Scholar -
Office of Financial Research (2020): OFR Index online dataset, U.S Department of the Treasury.
Google Scholar -
Pacicco, F./Vena, L./Venegoni, A. (2020): “Communication and Financial Supervision: How Does Disclosure Affect Market Stability?,” Journal of Empirical Finance 57, 1–15.
Google Scholar -
Phillips, R. C./Gorse, D. (2017): “Predicting Cryptocurrency Price Bubbles using Social Media Data and Epidemic Modelling,” In: 2017 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, 1–7.
Google Scholar -
Richter, C./Roy-Mukherjee, S. (2020): On the Uncertainty Caused by the Referendum on Brexit, Applied Economics Quarterly 66, 145–164.
Google Scholar -
Rua, A. (2010): “Measuring Co-movement in the Time-Frequency Space,” Journal of Macroeconomics 32, 685–691.
Google Scholar -
Rutkowska, A./Kliber, A. (2020): “Say Anything you Want about me if you Spell my Name Right: The effect of Internet Searches on Financial Market,” Central European Journal of Operation Research 29, 633–664.
Google Scholar -
Shaikh, I. (2020): “Policy Uncertainty and Bitcoin Returns,” Borsa Istanbul Review 20, 257–268.
Google Scholar -
Torrence, C./Compo, G. P. (1998): “A Practical Guide to Wavelet Analysis,” Bulletin of the American Meteorological Society 79, 605–618.
Google Scholar -
Trimborn, S./Härdle, W. K. (2018): “CRIX an Index for Cryptocurrencies,” Journal of Empirical Finance 49, 107–122.
Google Scholar -
Urquhart, A./Zhang, H. (2019): “Is Bitcoin a Hedge or Safe Haven for Currencies? An Intraday Analysis,” International Review of Financial Analysis 63, 49–57.
Google Scholar -
Vo, N. N./Xu, G. (2017): “The Volatility of Bitcoin Returns and its Correlation to Financial Markets,” In: 2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC), IEEE, 1–6.
Google Scholar -
Yahoo Finance (2020): Yahoo Finance Dataset, retrieved from https://de.finance.yahoo.com on April 30, 2020.
Google Scholar
Abstract
With its rising popularity, the Bitcoin has also become increasingly independent from global financial markets. Recently, it has joined the class of alternative assets. We use the newly developed wavelet methodology to analyze daily data to compare the COVID-19 pandemic at the beginning of 2020 with the bear market episode at the end of 2018. In both cases, attention signals and a general panic are the main drivers of the Bitcoin fluctuations. We show that the Bitcoin’s dynamic is more complex than the dynamics of standard financial assets. The Bitcoin is, on the one hand, subject to pandemic shocks but also represents an important source of attention signals. On the other hand, because the Bitcoin additionally reacts on an emotional basis, it might react faster than other assets and thus creates a market signal itself. Moreover, we identify short cycles (of several days), which may possibly be related to demand factors, while long cycles (of several weeks) seem to mirror supply factors and might be related to Bitcoin mining in China. Finally, the analysis underlines the importance of continuous financial education and communication by the supervisory authorities about new, alternative financial assets.
Table of Contents
Section Title | Page | Action | Price |
---|---|---|---|
Florian Horky / Mihai Mutascu / Jarko Fidrmuc: Pandemic Versus Financial Shocks: Comparison of Two Episodes on the Bitcoin Market | 113 | ||
Abstract | 113 | ||
1. Introduction | 114 | ||
2. Literature Review | 115 | ||
3. Methodology and Data | 118 | ||
3.1 Methodology | 118 | ||
3.2 Data | 120 | ||
4. Results | 113 | ||
5. Robustness Analysis | 113 | ||
6. Conclusions | 114 | ||
References | 114 | ||
Appendix | 114 |