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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.

Suggested Citation

  • 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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    References listed on IDEAS

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    Cited by:

    1. Lo, Yuen & Medda, Francesca, 2020. "Uniswap and the rise of the decentralized exchange," MPRA Paper 103925, University Library of Munich, Germany.
    2. 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).
    3. Wang, Yang & Xiuping, Sui & Zhang, Qi, 2021. "Can fintech improve the efficiency of commercial banks? —An analysis based on big data," Research in International Business and Finance, Elsevier, vol. 55(C).

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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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