IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v64y2024i2d10.1007_s10614-023-10477-1.html
   My bibliography  Save this article

Dynamic Analysis of Bitcoin Price Under Market News and Sentiments and Government Support Policies

Author

Listed:
  • Pardis Roozkhosh

    (Ferdowsi University of Mashhad)

  • Alireza Pooya

    (Ferdowsi University of Mashhad)

Abstract

Numerous variables are involved in determining the market capitalization and price of cryptocurrencies. So, It is impossible to ignore the feedback of each variable on the other ones. Also, Bitcoin management is challenging due to inter-dependencies and feedback between economic and social drivers. To better understand the dynamics that different variables have on Bitcoin, a system dynamics approach has been developed to investigate the complex interactions between factors related to Bitcoin and paper money and how these factors may affect the stability of Bitcoin. This paper aims to examine the impact of government support for Bitcoin in the future, news and sentiments effect on Bitcoin market price, and the future orientation of Bitcoin. For this purpose, a simulation period is considered from 2017 to 4500 days later. Moreover, In this study, policies have been designed to check the impact of policies on variables in the long term by keeping other variables constant. The results show that if governments support Bitcoin as an official trading currency in the future, the market price of Bitcoin and its trading volume will grow upward and fluctuate so that its market price will go up to about 90 thousand dollars.

Suggested Citation

  • Pardis Roozkhosh & Alireza Pooya, 2024. "Dynamic Analysis of Bitcoin Price Under Market News and Sentiments and Government Support Policies," Computational Economics, Springer;Society for Computational Economics, vol. 64(2), pages 1163-1198, August.
    • Handle: RePEc:kap:compec:v:64:y:2024:i:2:d:10.1007_s10614-023-10477-1
    DOI: 10.1007/s10614-023-10477-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10614-023-10477-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10614-023-10477-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Léo Malherbe & Matthieu Montalban & Nicolas Bédu & Caroline Granier, 2019. "Cryptocurrencies and Blockchain: Opportunities and Limits of a New Monetary Regime," International Journal of Political Economy, Taylor & Francis Journals, vol. 48(2), pages 127-152, April.
    2. Masafumi Nakano & Akihiko Takahashi & Soichiro Takahashi, 2018. "Bitcoin technical trading with artificial neural network," CARF F-Series CARF-F-441, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    3. Yechen Zhu & David Dickinson & Jianjun Li, 2017. "Erratum to: Analysis on the influence factors of Bitcoin’s price based on VEC model," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 3(1), pages 1-1, December.
    4. Selgin, George, 2015. "Synthetic commodity money," Journal of Financial Stability, Elsevier, vol. 17(C), pages 92-99.
    5. Joshua R. Hendrickson & Thomas L. Hogan & William J. Luther, 2016. "The Political Economy Of Bitcoin," Economic Inquiry, Western Economic Association International, vol. 54(2), pages 925-939, April.
    6. Lahmiri, Salim, 2018. "Minute-ahead stock price forecasting based on singular spectrum analysis and support vector regression," Applied Mathematics and Computation, Elsevier, vol. 320(C), pages 444-451.
    7. Karishma Chaudhary & Prem Vrat, 2020. "Circular economy model of gold recovery from cell phones using system dynamics approach: a case study of India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(1), pages 173-200, January.
    8. Parthajit Kayal & Purnima Rohilla, 2021. "Bitcoin in the economics and finance literature: a survey," SN Business & Economics, Springer, vol. 1(7), pages 1-21, July.
    9. Beate Sauer, 2016. "Virtual Currencies, the Money Market, and Monetary Policy," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 22(2), pages 117-130, May.
    10. Dean Fantazzini & Nikita Kolodin, 2020. "Does the Hashrate Affect the Bitcoin Price?," JRFM, MDPI, vol. 13(11), pages 1-29, October.
    11. Aslanidis, Nektarios & Bariviera, Aurelio F. & Martínez-Ibañez, Oscar, 2019. "An analysis of cryptocurrencies conditional cross correlations," Finance Research Letters, Elsevier, vol. 31(C), pages 130-137.
    12. Steinmetz, Fred & von Meduna, Marc & Ante, Lennart & Fiedler, Ingo, 2021. "Ownership, uses and perceptions of cryptocurrency: Results from a population survey," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    13. Sui, Jianli & Liu, Biying & Li, Zhigang & Zhang, Chengping, 2022. "Monetary and macroprudential policies, output, prices, and financial stability," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 212-233.
    14. Serdar Ongan & Ismet Gocer, 2021. "Monetary policy uncertainties and demand for money for Japan: Nonlinear ARDL approach," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 26(1), pages 1-12, January.
    15. Dyhrberg, Anne Haubo, 2016. "Bitcoin, gold and the dollar – A GARCH volatility analysis," Finance Research Letters, Elsevier, vol. 16(C), pages 85-92.
    16. Yechen Zhu & David Dickinson & Jianjun Li, 2017. "Analysis on the influence factors of Bitcoin’s price based on VEC model," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 3(1), pages 1-13, December.
    17. C. Alexander & M. Dakos, 2020. "A critical investigation of cryptocurrency data and analysis," Quantitative Finance, Taylor & Francis Journals, vol. 20(2), pages 173-188, February.
    18. Wang, Lei & Zhu, Taihui, 2021. "Population aging and money demand," Economics Letters, Elsevier, vol. 206(C).
    19. Duc Huynh, Toan Luu & Burggraf, Tobias & Wang, Mei, 2020. "Gold, platinum, and expected Bitcoin returns," Journal of Multinational Financial Management, Elsevier, vol. 56(C).
    20. Masafumi Nakano & Akihiko Takahashi & Soichiro Takahashi, 2018. "Bitcoin technical trading with artificial neural network," CARF F-Series CARF-F-430, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    21. Lahmiri, Salim & Bekiros, Stelios, 2019. "Cryptocurrency forecasting with deep learning chaotic neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 118(C), pages 35-40.
    22. Al Mamun, Md & Uddin, Gazi Salah & Suleman, Muhammad Tahir & Kang, Sang Hoon, 2020. "Geopolitical risk, uncertainty and Bitcoin investment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    23. Guesmi, Khaled & Saadi, Samir & Abid, Ilyes & Ftiti, Zied, 2019. "Portfolio diversification with virtual currency: Evidence from bitcoin," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 431-437.
    24. Young Bin Kim & Jurim Lee & Nuri Park & Jaegul Choo & Jong-Hyun Kim & Chang Hun Kim, 2017. "When Bitcoin encounters information in an online forum: Using text mining to analyse user opinions and predict value fluctuation," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-14, May.
    25. Frode Kjærland & Aras Khazal & Erlend A. Krogstad & Frans B. G. Nordstrøm & Are Oust, 2018. "An Analysis of Bitcoin’s Price Dynamics," JRFM, MDPI, vol. 11(4), pages 1-18, October.
    26. Nakano, Masafumi & Takahashi, Akihiko & Takahashi, Soichiro, 2018. "Bitcoin technical trading with artificial neural network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 587-609.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ahmed, Walid M.A., 2022. "Robust drivers of Bitcoin price movements: An extreme bounds analysis," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    2. Flori, Andrea, 2019. "News and subjective beliefs: A Bayesian approach to Bitcoin investments," Research in International Business and Finance, Elsevier, vol. 50(C), pages 336-356.
    3. Helder Miguel Correia Virtuoso Sebastião & Paulo José Osório Rupino Da Cunha & Pedro Manuel Cortesão Godinho, 2021. "Cryptocurrencies and blockchain. Overview and future perspectives," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 21(3), pages 305-342.
    4. Yue, Yao & Li, Xuerong & Zhang, Dingxuan & Wang, Shouyang, 2021. "How cryptocurrency affects economy? A network analysis using bibliometric methods," International Review of Financial Analysis, Elsevier, vol. 77(C).
    5. Helder Sebastião & Pedro Godinho, 2021. "Forecasting and trading cryptocurrencies with machine learning under changing market conditions," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-30, December.
    6. Ren, Yi-Shuai & Ma, Chao-Qun & Kong, Xiao-Lin & Baltas, Konstantinos & Zureigat, Qasim, 2022. "Past, present, and future of the application of machine learning in cryptocurrency research," Research in International Business and Finance, Elsevier, vol. 63(C).
    7. Zhang, Dingxuan & Sun, Yuying & Duan, Hongbo & Hong, Yongmiao & Wang, Shouyang, 2023. "Speculation or currency? Multi-scale analysis of cryptocurrencies—The case of Bitcoin," International Review of Financial Analysis, Elsevier, vol. 88(C).
    8. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & David Martinez-Rego & Fan Wu & Lingbo Li, 2022. "Cryptocurrency trading: a comprehensive survey," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-59, December.
    9. Julien Chevallier & Dominique Guégan & Stéphane Goutte, 2021. "Is It Possible to Forecast the Price of Bitcoin?," Forecasting, MDPI, vol. 3(2), pages 1-44, May.
    10. Rico-Peña, Juan Jesús & Arguedas-Sanz, Raquel & López-Martin, Carmen, 2023. "Models used to characterise blockchain features. A systematic literature review and bibliometric analysis," Technovation, Elsevier, vol. 123(C).
    11. Gradojevic, Nikola & Kukolj, Dragan & Adcock, Robert & Djakovic, Vladimir, 2023. "Forecasting Bitcoin with technical analysis: A not-so-random forest?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 1-17.
    12. Bouteska, Ahmed & Abedin, Mohammad Zoynul & Hajek, Petr & Yuan, Kunpeng, 2024. "Cryptocurrency price forecasting – A comparative analysis of ensemble learning and deep learning methods," International Review of Financial Analysis, Elsevier, vol. 92(C).
    13. Tapia, Sebastian & Kristjanpoller, Werner, 2022. "Framework based on multiplicative error and residual analysis to forecast bitcoin intraday-volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    14. Aurelio F. Bariviera & Ignasi Merediz‐Solà, 2021. "Where Do We Stand In Cryptocurrencies Economic Research? A Survey Based On Hybrid Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 377-407, April.
    15. Lahmiri, Salim & Bekiros, Stelios, 2019. "Cryptocurrency forecasting with deep learning chaotic neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 118(C), pages 35-40.
    16. Andrea Flori, 2019. "Cryptocurrencies In Finance: Review And Applications," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(05), pages 1-22, August.
    17. Syed Abul, Basher & Perry, Sadorsky, 2022. "Forecasting Bitcoin price direction with random forests: How important are interest rates, inflation, and market volatility?," MPRA Paper 113293, University Library of Munich, Germany.
    18. Yu Song & Bo Chen & Xin-Yi Wang, 2023. "Cryptocurrency technology revolution: are Bitcoin prices and terrorist attacks related?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-20, December.
    19. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.
    20. Panagiotidis, Theodore & Papapanagiotou, Georgios & Stengos, Thanasis, 2024. "A Bayesian approach for the determinants of bitcoin returns," International Review of Financial Analysis, Elsevier, vol. 91(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:compec:v:64:y:2024:i:2:d:10.1007_s10614-023-10477-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.