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Is Bitcoin ready to be a widespread payment method? Using price volatility and setting strategies for merchants

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Abstract

Bitcoin has gradually gained acceptance as a payment method that, unlike electronic payments in dollars or euros, passes through the international trading system with zero or lower fees. Moreover, Bitcoin and e-commerce have become increasingly intertwined in recent years as cryptocurrencies gain mainstream acceptance. In this paper, we analyze Bitcoin price evolution from September 2014 until July 2023, factors that influence price volatility and assess its future volatility using Autoregressive Conditional Heteroskedasticity (ARCH) models that predict the volatility of financial returns to conceive strategies for merchants that accept Bitcoin as a payment option. The Generalized ARCH model (GARCH) extends the model to capture more persistent volatility patterns. Further, we estimate symmetric and asymmetric GARCH (1,1)-type models with normal and non-normal innovations. The best proved to be EGARCH (1,1) with t-distribution innovation. To assist merchants in making decisions regarding Bitcoin adoption, two concepts are relevant: the EGARCH model and VaR. EGARCH model is used to forecast the volatility of the financial asset, while VaR is a widely used risk management tool that estimates the potential loss in value of a portfolio over a defined period. For a merchant holding Bitcoin, VaR assists in understanding the maximum expected loss over a certain time frame with a certain level of confidence (like 95% or 99%). The results show that a VaR coverage of 0.044 at a 5% probability level suggests that there is 95% confidence that the maximum loss will not exceed 4.4% of the investment value.

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Data availability

The data will be made available upon reasonable request.

Notes

  1. https://bitpay.com/directory/.

  2. https://www.forbes.com/advisor/business/accept-bitcoin-business/.

  3. https://www.investopedia.com/articles/investing/052014/why-bitcoins-value-so-volatile.asp.

  4. https://www.shopify.com/.

  5. https://github.com/simonavoprea/Bitcoin_data_2014-2023

References

  1. Wonglimpiyarat, J. (2015). The new Darwinism of the payment system: Will Bitcoin replace our cash-based society? Journal of Internet Banking and Commerce. https://doi.org/10.4172/1204-5357.S2-002

    Article  Google Scholar 

  2. Bourghelle, D., Jawadi, F., & Rozin, P. (2022). Do collective emotions drive bitcoin volatility? A triple regime-switching vector approach. Journal of Economic Behavior & Organization. https://doi.org/10.1016/j.jebo.2022.01.026

    Article  Google Scholar 

  3. Sapkota, N. (2022). News-based sentiment and bitcoin volatility. International Review of Financial Analysis. https://doi.org/10.1016/j.irfa.2022.102183

    Article  Google Scholar 

  4. Mattke, J., Maier, C., Reis, L., & Weitzel, T. (2019). Bitcoin investment: A mixed methods study of investment motivations. European Journal of Information Systems. https://doi.org/10.1080/0960085X.2020.1787109

    Article  Google Scholar 

  5. 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. https://doi.org/10.1016/j.resourpol.2020.101816

    Article  PubMed  PubMed Central  Google Scholar 

  6. Erdin, E., Cebe, M., Akkaya, K., Solak, S., Bulut, E., & Uluagac, S. (2020). A Bitcoin payment network with reduced transaction fees and confirmation times. Computing Networks. https://doi.org/10.1016/j.comnet.2020.107098

    Article  Google Scholar 

  7. Divakaruni, A., & Zimmerman, P. (2023). The lightning network: Turning bitcoin into money. Finance Research Letters. https://doi.org/10.1016/j.frl.2022.103480

    Article  Google Scholar 

  8. Hannon, C., & Jin, D. (2019). Bitcoin payment-channels for resource limited IoT devices. ACM Int. Conf. Proceeding Ser. https://doi.org/10.1145/3312614.3312629

    Article  Google Scholar 

  9. Mensah, I. K., & Mwakapesa, D. S. (2022). The drivers of the behavioral adoption intention of BITCOIN Payment from the perspective of Chinese citizens. Secur. Commun. Networks. https://doi.org/10.1155/2022/7373658

    Article  Google Scholar 

  10. McGinn, D., McIlwraith, D., & Guo, Y. (2018). Towards open data blockchain analytics: A bitcoin perspective. R. Soc. Open Sci. https://doi.org/10.1098/rsos.180298

    Article  PubMed  PubMed Central  Google Scholar 

  11. Nerurkar, P., Patel, D., Busnel, Y., Ludinard, R., Kumari, S., & Khan, M. K. (2021). Dissecting bitcoin blockchain: Empirical analysis of bitcoin network (2009–2020). Journal of Network and Computer Applications. https://doi.org/10.1016/j.jnca.2020.102940

    Article  Google Scholar 

  12. Kher, R., Terjesen, S., & Liu, C. (2021). Blockchain, Bitcoin, and ICOs: A review and research agenda. Small Business Economics. https://doi.org/10.1007/s11187-019-00286-y

    Article  Google Scholar 

  13. Mjoska, M., Ristevski, B., Savoska, S., Trajkovik, V. Predicting Bitcoin Volatility Using Machine Learning Algorithms and Blockchain Technology, in: CEUR Workshop Proc., 2022

  14. Loh, E. C., Ismail, S., Khamis, A., & Mustapha, A. (2020). Comparison of feedforward neural network with different training algorithms for bitcoin price forecasting. ASM Science Journal. https://doi.org/10.32802/asmscj.2020.sm26

    Article  Google Scholar 

  15. Huberman, G., Leshno, J. D., & Moallemi, C. (2021). Monopoly without a monopolist: An economic analysis of the bitcoin payment system. Review of Economic Studies. https://doi.org/10.1093/restud/rdab014

    Article  MathSciNet  Google Scholar 

  16. Luther, W. J., & Stein Smith, S. (2020). Is Bitcoin a decentralized payment mechanism. Journal of Institutional Economics. https://doi.org/10.1017/S1744137420000107

    Article  Google Scholar 

  17. Al-Haija, Q. A., & Alsulami, A. A. (2021). High performance classification model to identify ransomware payments for heterogeneous bitcoin networks. Electron. https://doi.org/10.3390/electronics10172113

    Article  Google Scholar 

  18. Paquet-Clouston, M., Haslhofer, B., & Dupont, B. (2019). Ransomware payments in the Bitcoin ecosystem. Journal of Cybersecurity. https://doi.org/10.1093/cybsec/tyz003

    Article  Google Scholar 

  19. Ciaian, P., D’artis, K., & Rajcaniova, M. (2021). The economic dependency of bitcoin security. Applied Economics. https://doi.org/10.1080/00036846.2021.1931003

    Article  Google Scholar 

  20. Bergsli, L. Ø., Lind, A. F., Molnár, P., & Polasik, M. (2022). Forecasting volatility of Bitcoin. Research in International Business and Finance. https://doi.org/10.1016/j.ribaf.2021.101540

    Article  Google Scholar 

  21. Longo, R., Podda, A. S., & Saia, R. (2020). Analysis of a consensus protocol for extending consistent subchains on the bitcoin blockchain. Computation. https://doi.org/10.3390/COMPUTATION8030067

    Article  Google Scholar 

  22. Swammy, S., Thompson, R., & Loh, M. (2019). Tales from the Crypt: The dawn of crypto currency. Crypto Uncovered The Evolution of Bitcoin and the Crypto Currency Marketplace. https://doi.org/10.1007/978-3-030-00135-3_2

    Article  Google Scholar 

  23. Hedman, J., Beaulieu, T., & Karlström, M. (2021). The tales of alphanumerical symbols in media: The case of bitcoin. Journal of Theoretical and Applied Electronic Commerce Research. https://doi.org/10.3390/jtaer16070152

    Article  Google Scholar 

  24. López-Cabarcos, M. Á., Pérez-Pico, A. M., Piñeiro-Chousa, J., & Šević, A. (2021). Bitcoin volatility, stock market and investor sentiment Are they connected? Finance Research Letters. https://doi.org/10.1016/j.frl.2019.101399

    Article  Google Scholar 

  25. Ayboğa, M. H., & Ganii, F. (2022). The Covid 19 crisis and the future of bitcoin in E-commerce. Journal Organization Behavior Research. https://doi.org/10.51847/hta7jg55of

    Article  Google Scholar 

  26. Marecki, K., & Wójcik-Czerniawska, A. (2020). Cryptocurrency market of bitcoin and payment acceptability in E-commerce. Economy Business Journal., 14(1), 257–267.

    Google Scholar 

  27. Mnif, E., & Jarboui, A. (2021). COVID-19, bitcoin market efficiency, herd behaviour. Review of Behavioural Finance. https://doi.org/10.1108/RBF-09-2020-0233

    Article  Google Scholar 

  28. Hou, J. P., Liu, J., & Jie, Y. J. (2021). Examining the psychological state analysis relationship between bitcoin prices and COVID-19. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2021.647691

    Article  PubMed  PubMed Central  Google Scholar 

  29. Ahn, J., Park, M., Shin, H., & Paek, J. (2019). A model for deriving trust and reputation on blockchain-based e-payment system. Applied Sciences. https://doi.org/10.3390/app9245362

    Article  Google Scholar 

  30. Özyılmaz, K.R., Kongel, N.B., Nalbant, A.E. and Özcan, A., 2019. A Multi-protocol Payment System to Facilitate Financial Inclusion. In Data Privacy Management, Cryptocurrencies and Blockchain Technology: ESORICS 2019 International Workshops, DPM 2019 and CBT 2019, Luxembourg, September 26–27, 2019, Proceedings 14 (pp. 321-335). Springer International Publishing.

  31. Abdulhakeem, S. A., & Hu, Q. (2021). Powered by blockchain technology, DeFi (decentralized finance) strives to increase financial inclusion of the unbanked by reshaping the world financial system. Modern Economy. https://doi.org/10.4236/me.2021.121001

    Article  Google Scholar 

  32. Kayral, I. E., Jeribi, A., & Loukil, S. (2023). Are bitcoin and gold a safe haven during COVID-19 and the 2022 Russia-Ukraine War? J. Risk Financ. Manag. https://doi.org/10.3390/jrfm16040222

    Article  Google Scholar 

  33. Zhang, Y., He, M., Wen, D., & Wang, Y. (2022). Forecasting bitcoin volatility: A new insight from the threshold regression model. Journal of Forecasting. https://doi.org/10.1002/for.2822

    Article  MathSciNet  Google Scholar 

  34. Hackethal, A., Hanspal, T., Lammer, D. M., & Rink, K. (2022). The Characteristics and portfolio behavior of bitcoin investors: evidence from indirect cryptocurrency investments. Rev. Financ. https://doi.org/10.1093/rof/rfab034

    Article  Google Scholar 

  35. Diaconaşu, D. E., Mehdian, S., & Stoica, O. (2022). An analysis of investors’ behavior in Bitcoin market. PLoS ONE. https://doi.org/10.1371/journal.pone.0264522

    Article  PubMed  PubMed Central  Google Scholar 

  36. Zhu, P., Zhang, X., Wu, Y., Zheng, H., & Zhang, Y. (2021). Investor attention and cryptocurrency: Evidence from the Bitcoin market. PLoS ONE. https://doi.org/10.1371/journal.pone.0246331

    Article  PubMed  PubMed Central  Google Scholar 

  37. Tang, T., & Wang, Y. (2022). Liquidity shocks, price volatilities, and risk-managed strategy: evidence from bitcoin and beyond. Journal of Multinational Financial Management. https://doi.org/10.1016/j.mulfin.2022.100729

    Article  Google Scholar 

  38. Guesmi, K., Saadi, S., Abid, I., & Ftiti, Z. (2019). Portfolio diversification with virtual currency: Evidence from bitcoin. International Review of Financial Analysis. https://doi.org/10.1016/j.irfa.2018.03.004

    Article  Google Scholar 

  39. Troster, V., Tiwari, A. K., Shahbaz, M., & Macedo, D. N. (2019). Bitcoin returns and risk: A general GARCH and GAS analysis. Finance Research Letters. https://doi.org/10.1016/j.frl.2018.09.014

    Article  Google Scholar 

  40. Lyócsa, Š, Molnár, P., Plíhal, T., & Širaňová, M. (2020). Impact of macroeconomic news, regulation and hacking exchange markets on the volatility of bitcoin. Journal of Economic Dynamics & Control. https://doi.org/10.1016/j.jedc.2020.103980

    Article  MathSciNet  Google Scholar 

  41. Shen, Z., Wan, Q., & Leatham, D. J. (2021). Bitcoin return volatility forecasting: A comparative study between GARCH and RNN. J. Risk Financ. Manag. https://doi.org/10.3390/jrfm14070337

    Article  Google Scholar 

  42. Wu, C. C., Ho, S. L., & Wu, C. C. (2022). The determinants of Bitcoin returns and volatility: Perspectives on global and national economic policy uncertainty. Finance Research Letters. https://doi.org/10.1016/j.frl.2021.102175

    Article  PubMed  PubMed Central  Google Scholar 

  43. Omura, A., Cheung, A., & Su, J. J. (2023). Does natural gas volatility affect Bitcoin volatility? Evidence from the HAR-RV model. Applied Economics. https://doi.org/10.1080/00036846.2023.2168608

    Article  Google Scholar 

  44. Bakas, D., Magkonis, G., & Oh, E. Y. (2022). What drives volatility in Bitcoin market? Finance Research Letters. https://doi.org/10.1016/j.frl.2022.103237

    Article  Google Scholar 

  45. Ben Nouir, J., & H. Ben Haj Hamida,. (2023). How do economic policy uncertainty and geopolitical risk drive Bitcoin volatility? Research in International Business and Finance. https://doi.org/10.1016/j.ribaf.2022.101809

    Article  Google Scholar 

  46. Alqahtani, M., & Hu, M. (2020). Integrated energy scheduling and routing for a network of mobile prosumers. Energy. https://doi.org/10.1016/j.energy.2020.117451

    Article  Google Scholar 

  47. Liang, C., Zhang, Y., Li, X., & Ma, F. (2022). Which predictor is more predictive for Bitcoin volatility? And why? International Journal of Finance and Economics. https://doi.org/10.1002/ijfe.2252

    Article  Google Scholar 

  48. Anamika, M., & Chakraborty, S. (2023). Subramaniam, Does Sentiment Impact Cryptocurrency? Journal of Behavioral Finance. https://doi.org/10.1080/15427560.2021.1950723

    Article  Google Scholar 

  49. Mohsin, M., Naseem, S., Ivașcu, L., Cioca, L. I., Sarfraz, M., & Stănică, N. C. (2021). Gauging the effect of investor sentiment on cryptocurrency market: an analysis of bitcoin currency. Romanian Jornal of Economic Forecasting., 24(4), 87.

    Google Scholar 

  50. Engle, R. F., & Ng, V. K. (1993). Measuring and Testing the Impact of News on Volatility. Journal of Finance. https://doi.org/10.2307/2329066

    Article  Google Scholar 

  51. Jesika, S., Pratiwi, W., & Handani, D. (2023). Potential analysis of bitcoin cryptocurrency as a future investment asset: A systematic literature review. Open Access Indonesia Journal of Social Sciences, 6(4), 1010–1016.

    Article  Google Scholar 

  52. Rudolf, K. O., El Zein, S. A., & Lansdowne, N. J. (2021). Bitcoin as an investment and hedge alternative. A dcc mgarch model analysis. Risks. https://doi.org/10.3390/risks9090154

    Article  Google Scholar 

  53. Brik, H., El Ouakdi, J., & Ftiti, Z. (2022). Roles of stable versus nonstable cryptocurrencies in Bitcoin market dynamics. Research in International Business and Finance. https://doi.org/10.1016/j.ribaf.2022.101720

    Article  Google Scholar 

  54. Attarzadeh, A., & Balcilar, M. (2022). On the dynamic return and volatility connectedness of cryptocurrency, crude oil, clean energy, and stock markets: A time-varying analysis. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-022-20115-2

    Article  PubMed  Google Scholar 

  55. Tang, C., & Liu, X. (2023). Bitcoin speculation, investor attention and major events. Are they connected? Applied Economics Letters. https://doi.org/10.1080/13504851.2022.2033677

    Article  Google Scholar 

  56. Bouoiyour J., Selmi R., Tiwari A., Is Bitcoin business income or speculative bubble? Unconditional vs conditional frequency domain analysis, Ann Financ Econ (2018)

  57. Su, C. W., Xi, Y., Tao, R., & Umar, M. (2022). Can bitcoin be a safe haven in fear sentiment? Technological and Economic Development of Economy. https://doi.org/10.3846/tede.2022.15502

    Article  Google Scholar 

  58. Li, Z. Z., Tao, R., Su, C. W., & Lobonţ, O. R. (2019). Does Bitcoin bubble burst? Quality & Quantity. https://doi.org/10.1007/s11135-018-0728-3

    Article  Google Scholar 

  59. Kumari, V., Bala, P. K., & Chakraborty, S. (2023). An empirical study of user adoption of cryptocurrency using blockchain technology: analysing role of success factors like technology awareness and financial literacy. Journal of Theoretical and Applied Electronic Commerce Research, 18, 1580–1600. https://doi.org/10.3390/jtaer18030080

    Article  Google Scholar 

  60. Grobys, K., Junttila, J., Kolari, J. W., & Sapkota, N. (2021). On the stability of stablecoins. Journal of Empirical Finance. https://doi.org/10.1016/j.jempfin.2021.09.002

    Article  Google Scholar 

  61. Ante, L., Fiedler, I., & Strehle, E. (2021). The impact of transparent money flows: Effects of stablecoin transfers on the returns and trading volume of Bitcoin. Technol. Forecast. Soc. Change. https://doi.org/10.1016/j.techfore.2021.120851

    Article  Google Scholar 

  62. Bojaj, M. M., Muhadinovic, M., Bracanovic, A., Mihailovic, A., Radulovic, M., Jolicic, I., Milosevic, I., & Milacic, V. (2022). Forecasting macroeconomic effects of stablecoin adoption: A Bayesian approach. Economic Modelling. https://doi.org/10.1016/j.econmod.2022.105792

    Article  Google Scholar 

  63. Mukharil, A., & Hanifah, R. N. (2019). Bitcoin influence on E-commerce. IOP Conf. Ser. Mater. Sci. Eng. https://doi.org/10.1088/1757-899X/662/3/032037

    Article  Google Scholar 

  64. Budree, A., & Nyathi, T. N. (2023). Can cryptocurrency be a payment method in a developing economy? The case of bitcoin in South Africa. Journal of Electronic Commerce in Organizations. https://doi.org/10.4018/JECO.320223

    Article  Google Scholar 

  65. Dewi, I. A., Miftahuddin, Y., Fattah, M. A., Palenda, C. B., & Erawan, S. F. (2021). Point of Sales System in InHome Café Website using Agile Methodology. Journal of Innovation and Community Engagement. https://doi.org/10.28932/jice.v1i1.3321

    Article  Google Scholar 

  66. Manan, W. D. W. A., & Ridzwian, A. A. B. M. (2019). A point-of-sale system for measuring sales performance. International Journal of Advanced Trends Computer Science Engineering. https://doi.org/10.30534/ijatcse/2019/3081.52019

    Article  Google Scholar 

  67. Bensona, S., Prasetya, F. H., & Harnadi, B. (2022). Implementation of Qr-code based point of sales application for retail store. Journal of Busines and Technology. https://doi.org/10.24167/jbt.v2i2.4395

    Article  Google Scholar 

  68. C. Lu, G. Lauritano, J. Peltonen, CryptoKitties vs. Axie Infinity: Computational Analysis of NFT Game Reddit Discussions, in: Lect. Notes Inst. Comput. Sci. Soc. Telecommun. Eng. LNICST, 2023. https://doi.org/10.1007/978-3-031-28993-4_8.

  69. Bezhovski, Z., Davcev, L., & Mitreva, M. (2021). Current adoption state of cryptocurrencies as an electronic payment method. Management Reseach and Practice., 13(1), 44–50.

    Google Scholar 

  70. Osman, S., Jabaruddin, N., Zon, A. S., Jifridin, A. A., & Zolkepli, A. K. (2021). Factors influencing the use of E-wallet among millennium tourist. Journal of Information Technology Management, 13(3), 70–81.

    Google Scholar 

  71. Tsang, K. P., & Yang, Z. (2021). The market for bitcoin transactions. Journal of International Financial Markets. https://doi.org/10.1016/j.intfin.2021.101282

    Article  Google Scholar 

  72. Yu, M. (2019). Forecasting Bitcoin volatility: The role of leverage effect and uncertainty. Physica A: Statistical Mechanics and Its Applications. https://doi.org/10.1016/j.physa.2019.03.072

    Article  Google Scholar 

  73. Dias, I. K., Fernando, J. M. R., & Fernando, P. N. D. (2022). Does investor sentiment predict bitcoin return and volatility? A quantile regression approach. International Review of Financial Analysis. https://doi.org/10.1016/j.irfa.2022.102383

    Article  Google Scholar 

  74. Mokni, K., Bouteska, A., & Nakhli, M. S. (2022). Investor sentiment and Bitcoin relationship: A quantile-based analysis. The North American Journal of Economics and Finance. https://doi.org/10.1016/j.najef.2022.101657

    Article  Google Scholar 

  75. Eom, C., Kaizoji, T., Kang, S. H., & Pichl, L. (2019). Bitcoin and investor sentiment: Statistical characteristics and predictability. Physica A: Statistical Mechanics and Its Applications. https://doi.org/10.1016/j.physa.2018.09.063

    Article  Google Scholar 

  76. Guizani, S., & Nafti, I. K. (2019). The Determinants of bitcoin price volatility: An investigation with ARDL Model. Procedia Computer Science. https://doi.org/10.1016/j.procs.2019.12.177

    Article  Google Scholar 

  77. Pichl, L., & Kaizoji, T. (2017). Volatility analysis of bitcoin price time series. Quantitative Finance and Economics. https://doi.org/10.3934/qfe.2017.4.474

    Article  Google Scholar 

  78. J. Wang, Y. Xue, M. Liu, An Analysis of Bitcoin Price Based on VEC Model, in: 2016. https://doi.org/10.2991/icemi-16.2016.36.

  79. Naimy, V. Y., & Hayek, M. R. (2018). Modelling and predicting the Bitcoin volatility using GARCH models. International Journal of Mathematical Modelling and Numerical. https://doi.org/10.1504/IJMMNO.2018.088994

    Article  Google Scholar 

  80. Naimy, V., Haddad, O., Fernández-Avilés, G., & El Khoury, R. (2021). The predictive capacity of GARCH-type models in measuring the volatility of crypto and world currencies. PLoS ONE. https://doi.org/10.1371/journal.pone.0245904

    Article  PubMed  PubMed Central  Google Scholar 

  81. Chu, J., Chan, S., Nadarajah, S., & Osterrieder, J. (2017). GARCH Modelling of Cryptocurrencies. Journal of Risk and Financial Management. https://doi.org/10.3390/jrfm10040017

    Article  Google Scholar 

  82. Katsiampa, P. (2017). Volatility estimation for Bitcoin: A comparison of GARCH models. Economic Letters. https://doi.org/10.1016/j.econlet.2017.06.023

    Article  MathSciNet  Google Scholar 

  83. De Nicola, G. (2021). On the intraday behavior of bitcoin. Ledger. https://doi.org/10.5195/ledger.2021.213

    Article  Google Scholar 

  84. Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica. https://doi.org/10.2307/1912773

    Article  MathSciNet  Google Scholar 

  85. Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Economics. https://doi.org/10.1016/0304-4076(86)90063-1

    Article  Google Scholar 

  86. Hansen, P. R., & Lunde, A. (2005). A forecast comparison of volatility models: Does anything beat a GARCH(1,1)? Journal of Applied Economics. https://doi.org/10.1002/jae.800

    Article  Google Scholar 

  87. Wang, P. (2005). Financial Econometrics. Routledge. https://doi.org/10.4324/9780203990735

    Book  Google Scholar 

  88. Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica. https://doi.org/10.2307/2938260

    Article  MathSciNet  Google Scholar 

  89. Tsay, R. S. (2010). Analysis of financial time series. Wiley. https://doi.org/10.1002/9780470644560

    Book  Google Scholar 

  90. Bollerslev, T., Russell, J. R., & Watson, M. W. (2010). Volatility and Time Series Econometrics: Essays in Honor of Robert Engle. OUP oxford. https://doi.org/10.1093/acprof:oso/9780199549498.001.0001

    Book  Google Scholar 

  91. Zakoian, J. M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics & Control. https://doi.org/10.1016/0165-1889(94)90039-6

    Article  Google Scholar 

  92. Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of American Statistical Association. https://doi.org/10.2307/2286348

    Article  MathSciNet  Google Scholar 

  93. Stoimenov, P. (2011). Philippe Jorion, Value at Risk, 3rd Ed: The New Benchmark for Managing Financial Risk. Statistical Papers. https://doi.org/10.1007/s00362-009-0296-7

    Article  Google Scholar 

  94. Brauneis, A., Mestel, R., Riordan, R., & Theissen, E. (2022). Bitcoin unchained: Determinants of cryptocurrency exchange liquidity. Journal of Empirical Finance. https://doi.org/10.1016/j.jempfin.2022.08.004

    Article  Google Scholar 

  95. Vo, A., Chapman, T. A., & Lee, Y. S. (2022). Examining bitcoin and economic determinants: An evolutionary perspective. The Journal of Computer Information Systems. https://doi.org/10.1080/08874417.2020.1865851

    Article  Google Scholar 

  96. Sarkodie, S. A., Ahmed, M. Y., & Leirvik, T. (2022). Trade volume affects bitcoin energy consumption and carbon footprint. Finance Research Letters. https://doi.org/10.1016/j.frl.2022.102977

    Article  PubMed  Google Scholar 

  97. Chen, W., Xu, H., Jia, L., & Gao, Y. (2021). Machine learning model for Bitcoin exchange rate prediction using economic and technology determinants. International Journal of Forecasting. https://doi.org/10.1016/j.ijforecast.2020.02.008

    Article  Google Scholar 

  98. Su, X., & Li, Y. (2020). Dynamic sentiment spillovers among crude oil, gold, and Bitcoin markets: Evidence from time and frequency domain analyses. PLoS ONE. https://doi.org/10.1371/journal.pone.0242515

    Article  PubMed  PubMed Central  Google Scholar 

  99. Huynh, T. L. D. (2023). When Elon Musk changes his tone, does bitcoin adjust its tune? Computational Economics. https://doi.org/10.1007/s10614-021-10230-6

    Article  Google Scholar 

  100. Suardi, S., Rasel, A. R., & Liu, B. (2022). On the predictive power of tweet sentiments and attention on bitcoin. International Review of Economics and Finance. https://doi.org/10.1016/j.iref.2022.02.017

    Article  Google Scholar 

  101. Fakharchian, S. (2023). Designing a forecasting assistant of the Bitcoin price based on deep learning using market sentiment analysis and multiple feature extraction. Soft Computing. https://doi.org/10.1007/s00500-023-09028-5

    Article  Google Scholar 

  102. Akyildirim, E., Corbet, S., Katsiampa, P., Kellard, N., & Sensoy, A. (2020). The development of Bitcoin futures: Exploring the interactions between cryptocurrency derivatives. Finance Research Letters. https://doi.org/10.1016/j.frl.2019.07.007

    Article  Google Scholar 

  103. Yi, E., Yang, B., Jeong, M., Sohn, S., & Ahn, K. (2023). Market efficiency of cryptocurrency: Evidence from the Bitcoin market. Science and Reports. https://doi.org/10.1038/s41598-023-31618-4

    Article  Google Scholar 

  104. 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. https://doi.org/10.1007/s42521-022-00052-y

    Article  PubMed  PubMed Central  Google Scholar 

  105. Aivaz, K.-A., Munteanu, I. F., & Jakubowicz, F. V. (2023). Bitcoin in conventional markets: A study on blockchain-induced reliability investment slopes financial and accounting aspects. Mathematics. https://doi.org/10.3390/math11214508

    Article  Google Scholar 

  106. Roozkhosh, P., & Pooya, A. (2023). Dynamic analysis of bitcoin price under market news and sentiments and government support policies. Computational Economics. https://doi.org/10.1007/s10614-023-10477-1

    Article  Google Scholar 

  107. Abdalla, S. Z. S. (2012). Modelling exchange rate volatility using GARCH models: Empirical evidence from Arab countries. International Journal of Economics and Finance. https://doi.org/10.5539/ijef.v4n3p216

    Article  Google Scholar 

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Acknowledgements

This work was supported by a grant from the Ministry of Research, Innovation and Digitization, CNCS- UEFISCDI, project number PN-III-P4-PCE-2021-0334, within PNCDI III.

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S-VO: Conceptualization, Validation, Formal analysis, Investigation, Writing – Original Draft, Writing – Review and Editing, Visualization, Project administration; IAG: Methodology, Writing – Original Draft, Writing – Review and Editing; AB: Conceptualization, Formal analysis, Investigation, Resources, Data Curation, Writing – Original Draft, Writing – Review and Editing, Visualization, Supervision.

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Correspondence to Simona-Vasilica Oprea.

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Oprea, SV., Georgescu, I.A. & Bâra, A. Is Bitcoin ready to be a widespread payment method? Using price volatility and setting strategies for merchants. Electron Commer Res (2024). https://doi.org/10.1007/s10660-024-09812-x

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