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GARCH Modelling of Cryptocurrencies

Author

Listed:
  • Jeffrey Chu

    () (School of Mathematics, University of Manchester, Manchester M13 9PL, U.K.)

  • Stephen Chan

    () (Department of Mathematics and Statistics, American University of Sharjah, Sharjah P.O. Box 26666, UAE)

  • Saralees Nadarajah

    () (School of Mathematics, University of Manchester, Manchester M13 9PL, U.K.)

  • Joerg Osterrieder

    () (School of Engineering, Zurich University of Applied Sciences, 8400 Winterthur, Switzerland)

Abstract

With the exception of Bitcoin, there appears to be little or no literature on GARCH modelling of cryptocurrencies. This paper provides the first GARCH modelling of the seven most popular cryptocurrencies. Twelve GARCH models are fitted to each cryptocurrency, and their fits are assessed in terms of five criteria. Conclusions are drawn on the best fitting models, forecasts and acceptability of value at risk estimates.

Suggested Citation

  • Jeffrey Chu & Stephen Chan & Saralees Nadarajah & Joerg Osterrieder, 2017. "GARCH Modelling of Cryptocurrencies," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 10(4), pages 1-15, October.
  • Handle: RePEc:gam:jjrfmx:v:10:y:2017:i:4:p:17-:d:113895
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Saha, Kunal, 2018. "An investigation into the dependence structure of major cryptocurrencies," EconStor Preprints 181878, ZBW - Leibniz Information Centre for Economics.
    2. Charles Shaw, 2018. "Conditional heteroskedasticity in crypto-asset returns," Papers 1804.07978, arXiv.org, revised Dec 2018.
    3. repec:eee:phsmap:v:514:y:2019:i:c:p:105-120 is not listed on IDEAS
    4. Sovbetov, Yhlas, 2018. "Factors Influencing Cryptocurrency Prices: Evidence from Bitcoin, Ethereum, Dash, Litcoin, and Monero," MPRA Paper 85036, University Library of Munich, Germany.
    5. Christian Hotz‐Behofsits & Florian Huber & Thomas Otto Zörner, 2018. "Predicting crypto‐currencies using sparse non‐Gaussian state space models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(6), pages 627-640, September.
    6. Marian Gidea & Daniel Goldsmith & Yuri Katz & Pablo Roldan & Yonah Shmalo, 2018. "Topological recognition of critical transitions in time series of cryptocurrencies," Papers 1809.00695, arXiv.org.
    7. Klein, Tony & Pham Thu, Hien & Walther, Thomas, 2018. "Bitcoin is not the New Gold – A comparison of volatility, correlation, and portfolio performance," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 105-116.
    8. Shaw, Charles, 2018. "Conditional heteroskedasticity in crypto-asset returns," MPRA Paper 90437, University Library of Munich, Germany.
    9. repec:gam:jjrfmx:v:12:y:2019:i:1:p:25-:d:203633 is not listed on IDEAS
    10. Thomas Walther & Tony Klein, 2018. "Exogenous Drivers of Cryptocurrency Volatility - A Mixed Data Sampling Approach To Forecasting," Working Papers on Finance 1815, University of St. Gallen, School of Finance.
    11. Guglielmo Maria Caporale & Timur Zekokh, 2018. "Modelling Volatility of Cryptocurrencies Using Markov-Switching Garch Models," CESifo Working Paper Series 7167, CESifo Group Munich.
    12. repec:eee:ecolet:v:164:y:2018:i:c:p:109-111 is not listed on IDEAS
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    14. Chappell, Daniel, 2018. "Regime heteroskedasticity in Bitcoin: A comparison of Markov switching models," MPRA Paper 90682, University Library of Munich, Germany.
    15. repec:kap:fmktpm:v:32:y:2018:i:4:d:10.1007_s11408-018-0320-9 is not listed on IDEAS
    16. repec:trp:01jefa:jefa0016 is not listed on IDEAS
    17. repec:eee:ecolet:v:173:y:2018:i:c:p:138-142 is not listed on IDEAS
    18. Cuneyt Akcora & Matthew Dixon & Yulia Gel & Murat Kantarcioglu, 2018. "Bitcoin Risk Modeling with Blockchain Graphs," Papers 1805.04698, arXiv.org.

    More about this item

    Keywords

    exchange rate; maximum likelihood; value at risk;

    JEL classification:

    • C - Mathematical and Quantitative Methods
    • E - Macroeconomics and Monetary Economics
    • F2 - International Economics - - International Factor Movements and International Business
    • F3 - International Economics - - International Finance
    • G - Financial Economics

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