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Time-varying long-term memory in Bitcoin market

Author

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  • Jiang, Yonghong
  • Nie, He
  • Ruan, Weihua

Abstract

This study attempts to investigate the time-varying long-term memory in the Bitcoin market through a rolling window approach and by employing a new efficiency index (Sensoy and Hacihasanoglu, 2014). The daily dataset for the period from 2010 to 2017 is utilized, and some interesting findings emerge that: (i) all of the generalized Hurst exponents in the Bitcoin market are above 0.5; (ii) long-term memory exists in the Bitcoin market; (iii) high degree of inefficiency ratio; (iv) the Bitcoin market does not become more efficient over time; and (v) rolling window approach can help to obtain more reliable results. Some implications for investors and policymakers are concluded.

Suggested Citation

  • Jiang, Yonghong & Nie, He & Ruan, Weihua, 2018. "Time-varying long-term memory in Bitcoin market," Finance Research Letters, Elsevier, vol. 25(C), pages 280-284.
    • Handle: RePEc:eee:finlet:v:25:y:2018:i:c:p:280-284
    DOI: 10.1016/j.frl.2017.12.009
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    More about this item

    Keywords

    Long-term memory; Bitcoin market; Generalized Hurst exponents; Rolling window;
    All these keywords.

    JEL classification:

    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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