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

Author

Listed:
  • Simona-Vasilica Oprea

    (Bucharest University of Economic Studies)

  • Irina Alexandra Georgescu

    (Bucharest University of Economic Studies)

  • Adela Bâra

    (Bucharest University of Economic Studies)

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.

Suggested Citation

  • Simona-Vasilica Oprea & Irina Alexandra Georgescu & Adela Bâra, 2024. "Is Bitcoin ready to be a widespread payment method? Using price volatility and setting strategies for merchants," Electronic Commerce Research, Springer, vol. 24(2), pages 1267-1305, June.
    • Handle: RePEc:spr:elcore:v:24:y:2024:i:2:d:10.1007_s10660-024-09812-x
    DOI: 10.1007/s10660-024-09812-x
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    as
    1. Pavel Ciaian & d’Artis Kancs & Miroslava Rajcaniova, 2021. "The economic dependency of bitcoin security," Applied Economics, Taylor & Francis Journals, vol. 53(49), pages 5738-5755, October.
    2. Yaojie Zhang & Mengxi He & Danyan Wen & Yudong Wang, 2022. "Forecasting Bitcoin volatility: A new insight from the threshold regression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 633-652, April.
    3. Katsiampa, Paraskevi, 2017. "Volatility estimation for Bitcoin: A comparison of GARCH models," Economics Letters, Elsevier, vol. 158(C), pages 3-6.
    4. Romi Kher & Siri Terjesen & Chen Liu, 2021. "Blockchain, Bitcoin, and ICOs: a review and research agenda," Small Business Economics, Springer, vol. 56(4), pages 1699-1720, April.
    5. A. V. Biju & Aparna Merin Mathew & P. P. Nithi Krishna & M. P. Akhil, 2022. "Is the future of bitcoin safe? A triangulation approach in the reality of BTC market through a sentiments analysis," Digital Finance, Springer, vol. 4(4), pages 275-290, December.
    6. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    7. Kamer-Ainur Aivaz & Ionela Florea Munteanu & Flavius Valentin Jakubowicz, 2023. "Bitcoin in Conventional Markets: A Study on Blockchain-Induced Reliability, Investment Slopes, Financial and Accounting Aspects," Mathematics, MDPI, vol. 11(21), pages 1-20, November.
    8. Ante, Lennart & Fiedler, Ingo & Strehle, Elias, 2021. "The impact of transparent money flows: Effects of stablecoin transfers on the returns and trading volume of Bitcoin," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    9. Bojaj, Martin M. & Muhadinovic, Milica & Bracanovic, Andrej & Mihailovic, Andrej & Radulovic, Mladen & Jolicic, Ivan & Milosevic, Igor & Milacic, Veselin, 2022. "Forecasting macroeconomic effects of stablecoin adoption: A Bayesian approach," Economic Modelling, Elsevier, vol. 109(C).
    10. Xianfang Su & Yong Li, 2020. "Dynamic sentiment spillovers among crude oil, gold, and Bitcoin markets: Evidence from time and frequency domain analyses," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-26, December.
    11. Lyócsa, Štefan & Molnár, Peter & Plíhal, Tomáš & Širaňová, Mária, 2020. "Impact of macroeconomic news, regulation and hacking exchange markets on the volatility of bitcoin," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    12. Chen, Wei & Xu, Huilin & Jia, Lifen & Gao, Ying, 2021. "Machine learning model for Bitcoin exchange rate prediction using economic and technology determinants," International Journal of Forecasting, Elsevier, vol. 37(1), pages 28-43.
    13. Alqahtani, Mohammed & Hu, Mengqi, 2020. "Integrated energy scheduling and routing for a network of mobile prosumers," Energy, Elsevier, vol. 200(C).
    14. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    15. Ihsan Erdem Kayral & Ahmed Jeribi & Sahar Loukil, 2023. "Are Bitcoin and Gold a Safe Haven during COVID-19 and the 2022 Russia–Ukraine War?," JRFM, MDPI, vol. 16(4), pages 1-22, April.
    16. Tang, Tao & Wang, Yanchen, 2022. "Liquidity Shocks, Price Volatilities, and Risk-managed Strategy: Evidence from Bitcoin and Beyond," Journal of Multinational Financial Management, Elsevier, vol. 64(C).
    17. Chun Tang & Xiaoxing Liu, 2023. "Bitcoin speculation, investor attention and major events. Are they connected?," Applied Economics Letters, Taylor & Francis Journals, vol. 30(8), pages 1033-1041, May.
    18. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
    19. Mokni, Khaled & Bouteska, Ahmed & Nakhli, Mohamed Sahbi, 2022. "Investor sentiment and Bitcoin relationship: A quantile-based analysis," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    20. Luther, William J. & Stein Smith, Sean, 2020. "Is Bitcoin a decentralized payment mechanism?," Journal of Institutional Economics, Cambridge University Press, vol. 16(4), pages 433-444, August.
    21. Muhammad MOHSIN & Sobia NASEEM & Larisa IVAȘCU & Lucian-Ionel CIOCA & Muddassar SARFRAZ & Nicolae Cristian STĂNICĂ, 2021. "Gauging the Effect of Investor Sentiment on Cryptocurrency Market: An Analysis of Bitcoin Currency," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 87-102, December.
    22. Zlatko BEZHOVSKI & Ljupco DAVCEV & Mila MITREVA, 2021. "Current adoption state of cryptocurrencies as an electronic payment method," Management Research and Practice, Research Centre in Public Administration and Public Services, Bucharest, Romania, vol. 13(1), pages 44-50, March.
    23. Zheng-Zheng Li & Ran Tao & Chi-Wei Su & Oana-Ramona Lobonţ, 2019. "Does Bitcoin bubble burst?," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(1), pages 91-105, January.
    24. Brauneis, Alexander & Mestel, Roland & Riordan, Ryan & Theissen, Erik, 2022. "Bitcoin unchained: Determinants of cryptocurrency exchange liquidity," Journal of Empirical Finance, Elsevier, vol. 69(C), pages 106-122.
    25. Wu, Chang-Che & Ho, Shu-Ling & Wu, Chih-Chiang, 2022. "The determinants of Bitcoin returns and volatility: Perspectives on global and national economic policy uncertainty," Finance Research Letters, Elsevier, vol. 45(C).
    26. Viviane Naimy & Omar Haddad & Gema Fernández-Avilés & Rim El Khoury, 2021. "The predictive capacity of GARCH-type models in measuring the volatility of crypto and world currencies," PLOS ONE, Public Library of Science, vol. 16(1), pages 1-17, January.
    27. Krzysztof Marecki & Agnieszka Wójcik-Czerniawska, 2020. "Cryptocurrency Market Of Bitcoin And Payment Acceptability In E-Commerce," Economy & Business Journal, International Scientific Publications, Bulgaria, vol. 14(1), pages 257-267.
    28. Pavel Stoimenov, 2011. "Philippe Jorion, Value at Risk, 3rd Ed: The New Benchmark for Managing Financial Risk," Statistical Papers, Springer, vol. 52(3), pages 737-738, August.
    29. Jeffrey Chu & Stephen Chan & Saralees Nadarajah & Joerg Osterrieder, 2017. "GARCH Modelling of Cryptocurrencies," JRFM, MDPI, vol. 10(4), pages 1-15, October.
    30. Troster, Victor & Tiwari, Aviral Kumar & Shahbaz, Muhammad & Macedo, Demian Nicolás, 2019. "Bitcoin returns and risk: A general GARCH and GAS analysis," Finance Research Letters, Elsevier, vol. 30(C), pages 187-193.
    31. Muhammad MOHSIN & Sobia NASEEM & Larisa IVAȘCU & Lucian-Ionel CIOCA & Muddassar SARFRAZ & Nicolae Cristian STĂNICĂ, 2021. "Gauging the Effect of Investor Sentiment on Cryptocurrency Market: An Analysis of Bitcoin Currency," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 86-102, December.
    32. Andreas Hackethal & Tobin Hanspal & Dominique M Lammer & Kevin Rink, 2022. "The Characteristics and Portfolio Behavior of Bitcoin Investors: Evidence from Indirect Cryptocurrency Investments [The investor in structured retail products: advice driven or gambling oriented]," Review of Finance, European Finance Association, vol. 26(4), pages 855-898.
    33. Tsang, Kwok Ping & Yang, Zichao, 2021. "The market for bitcoin transactions," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    34. Gur Huberman & Jacob D Leshno & Ciamac Moallemi, 2021. "Monopoly without a Monopolist: An Economic Analysis of the Bitcoin Payment System [Blockchain Economics]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(6), pages 3011-3040.
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