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An approach to the use of cryptocurrencies in Romania using data mining technique

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  • Nora CHIRIȚĂ

    (Bucharest University of Economic Studies, Romania)

  • Ionuț NICA

    (Bucharest University of Economic Studies, Romania)

Abstract

The global economy can be regarded as a complex global adaptive system, which adapts and evolves according to the environment and the behavior of the agents existing on the market. A topic that is topical and can even affect the welfare of a country is the field of cryptocurrencies. Today, the most well-known phenomenon by people in this field is the emergence of bitcoin. Cryptocurrencies or virtual currencies are an emanation of the financial crisis that started in 2008, a crisis that had led to a decline in confidence of traditional bank. In this paper, we discussed the creation of possible speculative bubbles, we presented the virtual currencies, we applied techniques of multidimensional analysis of the data for their analysis, and we evaluated the effects that the appearance of the cryptocurrencies had on the cybernetic economic system in Romania. Also, the paper deals with a section on identifying risks in the field of cryptocurrencies. In the last part of this paper, we focus our attention on the viability of these coins and their future prospects.

Suggested Citation

  • Nora CHIRIȚĂ & Ionuț NICA, 2020. "An approach to the use of cryptocurrencies in Romania using data mining technique," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(1(622), S), pages 5-20, Spring.
    • Handle: RePEc:agr:journl:v:xxvii:y:2020:i:1(622):p:5-20
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    References listed on IDEAS

    as
    1. Vladimir Filimonov & Didier Sornette, "undated". "A Stable and Robust Calibration Scheme of the Log-Periodic Power Law Model," Working Papers ETH-RC-11-002, ETH Zurich, Chair of Systems Design.
    2. Andy Extance, 2015. "The future of cryptocurrencies: Bitcoin and beyond," Nature, Nature, vol. 526(7571), pages 21-23, October.
    3. Filimonov, V. & Sornette, D., 2013. "A stable and robust calibration scheme of the log-periodic power law model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3698-3707.
    4. Didier SORNETTE & Guilherme DEMOS & Zhang QUN & Peter CAUWELS & Vladimir FILIMONOV & Qunzhi ZHANG, 2015. "Real-Time Prediction and Post-Mortem Analysis of the Shanghai 2015 Stock Market Bubble and Crash," Swiss Finance Institute Research Paper Series 15-32, Swiss Finance Institute.
    5. Ofer H. Azar, 2007. "The Slowdown In First‐Response Times Of Economics Journals: Can It Be Beneficial?," Economic Inquiry, Western Economic Association International, vol. 45(1), pages 179-187, January.
    6. Vladimir Filimonov & Didier Sornette, 2011. "A Stable and Robust Calibration Scheme of the Log-Periodic Power Law Model," Papers 1108.0099, arXiv.org, revised Jun 2013.
    7. Adhami, Saman & Giudici, Giancarlo & Martinazzi, Stefano, 2018. "Why do businesses go crypto? An empirical analysis of initial coin offerings," Journal of Economics and Business, Elsevier, vol. 100(C), pages 64-75.
    8. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    9. Bouri, Elie & Molnár, Peter & Azzi, Georges & Roubaud, David & Hagfors, Lars Ivar, 2017. "On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier?," Finance Research Letters, Elsevier, vol. 20(C), pages 192-198.
    10. Baur, Dirk G. & Hong, KiHoon & Lee, Adrian D., 2018. "Bitcoin: Medium of exchange or speculative assets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 54(C), pages 177-189.
    11. Anders Johansen & Olivier Ledoit & Didier Sornette, 2000. "Crashes As Critical Points," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 3(02), pages 219-255.
    12. Cheah, Eng-Tuck & Fry, John, 2015. "Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin," Economics Letters, Elsevier, vol. 130(C), pages 32-36.
    13. Dean Fantazzini & Stephan Zimin, 2020. "A multivariate approach for the simultaneous modelling of market risk and credit risk for cryptocurrencies," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(1), pages 19-69, March.
    14. Anat R. Admati, Paul Pfleiderer, 1988. "A Theory of Intraday Patterns: Volume and Price Variability," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 3-40.
    15. Saman Adhami & Dominique Guegan, 2020. "Crypto assets: the role of ICO tokens within a well-diversified portfolio," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(2), pages 219-241, June.
    16. Graf v. Bothmer, Hans-Christian & Meister, Christian, 2003. "Predicting critical crashes? A new restriction for the free variables," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 320(C), pages 539-547.
    17. C. Baek & M. Elbeck, 2015. "Bitcoins as an investment or speculative vehicle? A first look," Applied Economics Letters, Taylor & Francis Journals, vol. 22(1), pages 30-34, January.
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    Cited by:

    1. Nora CHIRIȚĂ & Camelia DELCEA & Ionuț NICA & Simona-Liliana CRĂCIUNESCU (PARAMON) & Ștefan-Andrei IONESCU, 2023. "Financial contagion and identifying speculative frenzies: Unraveling price bubbles in cryptocurrency markets," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(3(636), A), pages 21-40, Autumn.

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