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On the speculative nature of cryptocurrencies: A study on Garman and Klass volatility measure

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  • Tan, Shay-Kee
  • Chan, Jennifer So-Kuen
  • Ng, Kok-Haur

Abstract

We propose to measure volatilities of 102 active cryptocurrencies using Garman and Klass (GK) volatility measures and model the measures using asymmetric bilinear Conditional Autoregressive Range (ABL-CARR) model. Results reveal volatility persistence and leverage effects which can improve the predictability of volatility, reduce risk and hence lessen the level of speculation in cryptocurrency market. We further relate volatility features for the top five cryptocurrencies to their time of development and transaction speed and recommend investors to distinguish between long-term or short-term speculation in their investment profile.

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  • Tan, Shay-Kee & Chan, Jennifer So-Kuen & Ng, Kok-Haur, 2020. "On the speculative nature of cryptocurrencies: A study on Garman and Klass volatility measure," Finance Research Letters, Elsevier, vol. 32(C).
    • Handle: RePEc:eee:finlet:v:32:y:2020:i:c:s1544612318305105
    DOI: 10.1016/j.frl.2018.12.023
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    5. Cheng, Jiyang & Tiwari, Sunil & Khaled, Djebbouri & Mahendru, Mandeep & Shahzad, Umer, 2024. "Forecasting Bitcoin prices using artificial intelligence: Combination of ML, SARIMA, and Facebook Prophet models," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    6. Riccardo De Blasis, 2023. "Weighted-indexed semi-Markov model: calibration and application to financial modeling," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-16, December.
    7. Ahmed, Walid M.A., 2021. "Stock market reactions to upside and downside volatility of Bitcoin: A quantile analysis," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    8. Alexander Guzmán & Christian Pinto-Gutiérrez & María-Andrea Trujillo, 2021. "Trading Cryptocurrencies as a Pandemic Pastime: COVID-19 Lockdowns and Bitcoin Volume," Mathematics, MDPI, vol. 9(15), pages 1-15, July.
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    10. Lo, Yuen & Medda, Francesca, 2020. "Uniswap and the rise of the decentralized exchange," MPRA Paper 103925, University Library of Munich, Germany.
    11. Jinxin Cui & Aktham Maghyereh, 2022. "Time–frequency co-movement and risk connectedness among cryptocurrencies: new evidence from the higher-order moments before and during the COVID-19 pandemic," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-56, December.
    12. Filip Hampl & Lucie Gyönyörová, 2021. "Can Fiat‐backed Stablecoins Be Considered Cash or Cash Equivalents Under International Financial Reporting Standards Rules?," Australian Accounting Review, CPA Australia, vol. 31(3), pages 233-255, September.
    13. James, Nick & Menzies, Max & Chan, Jennifer, 2021. "Changes to the extreme and erratic behaviour of cryptocurrencies during COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    14. 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.
    15. Adrian Millea, 2021. "Deep Reinforcement Learning for Trading—A Critical Survey," Data, MDPI, vol. 6(11), pages 1-25, November.
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    19. Huynh, Nhan & Phan, Hoa, 2023. "Emotions in the crypto market: Do photos really speak?," Finance Research Letters, Elsevier, vol. 55(PB).

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    More about this item

    Keywords

    Volatility; GK measure; Cryptocurrencies; CARR model;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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