IDEAS home Printed from https://ideas.repec.org/a/eee/finana/v84y2022ics1057521922003258.html
   My bibliography  Save this article

Exploring the relationship between Bitcoin price and network’s hashrate within endogenous system

Author

Listed:
  • Kubal, Jan
  • Kristoufek, Ladislav

Abstract

Bitcoin pricing mechanism is a complex system of interactions between factors that are not standard for traditional financial assets. Its understanding is essential for assessing specific topics, most prominently the interaction between Bitcoin price and network’s hashrate as it directly translates into its power demand and consumption and thus also environmental implications. We examine an intertwined system of equations, controlling for various statistical caveats connected to such system, providing a coherent picture of the system dynamics and thus delivering the most rigorous and complex approach in explaining the pricing dynamics of the Bitcoin system up to date. We shown that the whole system is very well structured and delivers economically and logically sound results, pointing at the network security narrative in the Bitcoin price–hashrate nexus.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:finana:v:84:y:2022:i:c:s1057521922003258
    DOI: 10.1016/j.irfa.2022.102375
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1057521922003258
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.irfa.2022.102375?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. David Garcia & Claudio Juan Tessone & Pavlin Mavrodiev & Nicolas Perony, 2014. "The digital traces of bubbles: feedback cycles between socio-economic signals in the Bitcoin economy," Papers 1408.1494, arXiv.org.
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    3. Pavel Ciaian & Miroslava Rajcaniova & d’Artis Kancs, 2016. "The economics of BitCoin price formation," Applied Economics, Taylor & Francis Journals, vol. 48(19), pages 1799-1815, April.
    4. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    5. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    6. Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-529, October.
    7. Dean Fantazzini & Nikita Kolodin, 2020. "Does the Hashrate Affect the Bitcoin Price?," JRFM, MDPI, vol. 13(11), pages 1-29, October.
    8. Kristoufek, Ladislav, 2019. "Is the Bitcoin price dynamics economically reasonable? Evidence from fundamental laws," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    9. Breusch, T S & Pagan, A R, 1979. "A Simple Test for Heteroscedasticity and Random Coefficient Variation," Econometrica, Econometric Society, vol. 47(5), pages 1287-1294, September.
    10. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
    11. Jamal Bouoiyour & Refk Selmi, 2017. "The Bitcoin price formation: Beyond the fundamental sources," Working Papers hal-01548710, HAL.
    12. Korniotis, George & Bhambhwani, Siddharth & Delikouras, Stefanos, 2019. "Blockchain Characteristics and the Cross-Section of Cryptocurrency Returns," CEPR Discussion Papers 13724, C.E.P.R. Discussion Papers.
    13. Aalborg, Halvor Aarhus & Molnár, Peter & de Vries, Jon Erik, 2019. "What can explain the price, volatility and trading volume of Bitcoin?," Finance Research Letters, Elsevier, vol. 29(C), pages 255-265.
    14. Adam S. Hayes, 2019. "Bitcoin price and its marginal cost of production: support for a fundamental value," Applied Economics Letters, Taylor & Francis Journals, vol. 26(7), pages 554-560, April.
    15. MacKinnon, James G. & White, Halbert, 1985. "Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties," Journal of Econometrics, Elsevier, vol. 29(3), pages 305-325, September.
    16. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Podhorsky, Andrea, 2023. "Taxing bitcoin: Incentivizing the difficulty adjustment mechanism to reduce electricity usage," International Review of Financial Analysis, Elsevier, vol. 86(C).
    2. Jiri Kukacka & Ladislav Kristoufek, 2023. "Fundamental and speculative components of the cryptocurrency pricing dynamics," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    3. Kim, Daehan & Ryu, Doojin & Webb, Robert I., 2023. "Determination of equilibrium transaction fees in the Bitcoin network: A rank-order contest," International Review of Financial Analysis, Elsevier, vol. 86(C).

    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. Russell Davidson & Victoria Zinde‐Walsh, 2017. "Advances in specification testing," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 50(5), pages 1595-1631, December.
    2. 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.
    3. John E. Marthinsen & Steven R. Gordon, 2022. "The Price and Cost of Bitcoin," Papers 2204.13102, arXiv.org.
    4. Kristoufek, Ladislav & Bouri, Elie, 2023. "Exploring sources of statistical arbitrage opportunities among Bitcoin exchanges," Finance Research Letters, Elsevier, vol. 51(C).
    5. 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).
    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. Guilhem Bascle, 2008. "Controlling for endogeneity with instrumental variables in strategic management research," Post-Print hal-00576795, HAL.
    8. 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.
    9. Jiri Kukacka & Ladislav Kristoufek, 2023. "Fundamental and speculative components of the cryptocurrency pricing dynamics," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    10. Haffar, Adlane & Le Fur, Eric, 2021. "Structural vector error correction modelling of Bitcoin price," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 170-178.
    11. 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.
    12. Doko Tchatoka, Firmin Sabro, 2012. "Specification Tests with Weak and Invalid Instruments," MPRA Paper 40185, University Library of Munich, Germany.
    13. 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.
    14. Sapkota, Niranjan, 2022. "News-based sentiment and bitcoin volatility," International Review of Financial Analysis, Elsevier, vol. 82(C).
    15. Leilane de Freitas Rocha Cambara & Roberto Meurer, 2023. "News sentiment and foreign portfolio investment in Brazil," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 3332-3348, July.
    16. Mohammad Reza Farzanegan & Hassan F. Gholipour & Mostafa Javadian, 2023. "Air pollution and internal migration: evidence from an Iranian household survey," Empirical Economics, Springer, vol. 64(1), pages 223-247, January.
    17. Xun Zhang & Fengbin Lu & Rui Tao & Shouyang Wang, 2021. "The time-varying causal relationship between the Bitcoin market and internet attention," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-19, December.
    18. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2022. "Cryptocurrency returns under empirical asset pricing," International Review of Financial Analysis, Elsevier, vol. 82(C).
    19. Michael O'Connor Keefe & David Gallagher, 2014. "Does the effect of revealed private information on initial public offering (IPO) first trading day return differ by IPO market heat?," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 54(3), pages 921-964, September.
    20. Geweke, J. & Joel Horowitz & Pesaran, M.H., 2006. "Econometrics: A Bird’s Eye View," Cambridge Working Papers in Economics 0655, Faculty of Economics, University of Cambridge.

    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:eee:finana:v:84:y:2022:i:c:s1057521922003258. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620166 .

    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.