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An Analysis of Bitcoin’s Price Dynamics

Author

Listed:
  • Frode Kjærland

    (NTNU Business School, Norwegian University of Science and Technology, 7491 Trondheim, Norway
    Nord University Business School, Nord University, 8049 Bodø, Norway)

  • Aras Khazal

    (NTNU Business School, Norwegian University of Science and Technology, 7491 Trondheim, Norway)

  • Erlend A. Krogstad

    (NTNU Business School, Norwegian University of Science and Technology, 7491 Trondheim, Norway)

  • Frans B. G. Nordstrøm

    (NTNU Business School, Norwegian University of Science and Technology, 7491 Trondheim, Norway)

  • Are Oust

    (NTNU Business School, Norwegian University of Science and Technology, 7491 Trondheim, Norway)

Abstract

This paper aims to enhance the understanding of which factors affect the price development of Bitcoin in order for investors to make sound investment decisions. Previous literature has covered only a small extent of the highly volatile period during the last months of 2017 and the beginning of 2018. To examine the potential price drivers, we use the Autoregressive Distributed Lag and Generalized Autoregressive Conditional Heteroscedasticity approach. Our study identifies the technological factor Hashrate as irrelevant for modeling Bitcoin price dynamics. This irrelevance is due to the underlying code that makes the supply of Bitcoins deterministic, and it stands in contrast to previous literature that has included Hashrate as a crucial independent variable. Moreover, the empirical findings indicate that the price of Bitcoin is affected by returns on the S&P 500 and Google searches, showing consistency with results from previous literature. In contrast to previous literature, we find the CBOE volatility index (VIX), oil, gold, and Bitcoin transaction volume to be insignificant.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jjrfmx:v:11:y:2018:i:4:p:63-:d:175742
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    References listed on IDEAS

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    Cited by:

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    3. Dean Fantazzini & Nikita Kolodin, 2020. "Does the Hashrate Affect the Bitcoin Price?," JRFM, MDPI, vol. 13(11), pages 1-29, October.
    4. Christian M. Hafner & Sabrine Majeri, 2022. "Analysis of cryptocurrency connectedness based on network to transaction volume ratios," Digital Finance, Springer, vol. 4(2), pages 187-216, September.
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    6. Marthinsen, John E. & Gordon, Steven R., 2022. "The price and cost of bitcoin," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 280-288.
    7. Kokulo K. Lawuobahsumo & Bernardina Algieri & Leonardo Iania & Arturo Leccadito, 2022. "Exploring Dependence Relationships between Bitcoin and Commodity Returns: An Assessment Using the Gerber Cross-Correlation," Commodities, MDPI, vol. 1(1), pages 1-16, August.
    8. Burcu Kapar & Jose Olmo, 2021. "Analysis of Bitcoin prices using market and sentiment variables," The World Economy, Wiley Blackwell, vol. 44(1), pages 45-63, January.
    9. Christophe Schinckus & Canh Phuc Nguyen & Felicia Hui Ling Chong, 2023. "Between financial and algorithmic dynamics of cryptocurrencies: An exploratory study," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 3055-3070, July.
    10. López-Cabarcos, M. Ángeles & Pérez-Pico, Ada M. & Piñeiro-Chousa, Juan & Šević, Aleksandar, 2021. "Bitcoin volatility, stock market and investor sentiment. Are they connected?," Finance Research Letters, Elsevier, vol. 38(C).
    11. Senarathne Chamil W. & Šoja Tijana, 2019. "Heteroskedasticity in Excess Bitcoin Return Data: Google Trend vs. Garch Effects," Financial Sciences. Nauki o Finansach, Sciendo, vol. 24(3), pages 35-45, September.
    12. John E. Marthinsen & Steven R. Gordon, 2022. "The Price and Cost of Bitcoin," Papers 2204.13102, arXiv.org.
    13. Uzonwanne, Godfrey, 2021. "Volatility and return spillovers between stock markets and cryptocurrencies," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 30-36.
    14. Hang Bui Thi Thu & Huy Dinh Tran Ngoc & An Phan Thuy & Ngoc Nguyen Thi Bich & Duyen Huynh Thi My, 2020. "Current situation of Bitcoin management and use: perspectives from the world and recommendations for vietnam," Management, Sciendo, vol. 24(2), pages 209-235, December.
    15. Süssmuth, Bernd, 2019. "Bitcoin and Web Search Query Dynamics: Is the price driving the hype or is the hype driving the price?," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203566, Verein für Socialpolitik / German Economic Association.
    16. Kubal, Jan & Kristoufek, Ladislav, 2022. "Exploring the relationship between Bitcoin price and network’s hashrate within endogenous system," International Review of Financial Analysis, Elsevier, vol. 84(C).
    17. Ahmed M. Khedr & Ifra Arif & Pravija Raj P V & Magdi El‐Bannany & Saadat M. Alhashmi & Meenu Sreedharan, 2021. "Cryptocurrency price prediction using traditional statistical and machine‐learning techniques: A survey," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 28(1), pages 3-34, January.
    18. Bernd Süssmuth, 2022. "The mutual predictability of Bitcoin and web search dynamics," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 435-454, April.
    19. Kliber, Agata & Marszałek, Paweł & Musiałkowska, Ida & Świerczyńska, Katarzyna, 2019. "Bitcoin: Safe haven, hedge or diversifier? Perception of bitcoin in the context of a country’s economic situation — A stochastic volatility approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 246-257.
    20. Dilip B. Madan & Sofie Reyners & Wim Schoutens, 2019. "Advanced model calibration on bitcoin options," Digital Finance, Springer, vol. 1(1), pages 117-137, November.

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