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How persistent and dynamic inter-dependent are pricing of Bitcoin to other cryptocurrencies before and after 2017/18 crash?

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  • Yaya, OlaOluwa S.
  • Ogbonna, Ahamuefula E.
  • Olubusoye, Olusanya E.

Abstract

The present paper investigates persistence and inter-dependence of bitcoin on other popular alternative coins. We employ fractional integration approach in our analysis of persistence, while a more recent fractional cointegration technique in VAR set-up, proposed by Johansen (2008), is used to investigate inter-dependence in pricing of the paired cryptocurrencies. Having partitioned the series into periods before and after the 2017/2018 cryptocurrency price crash, as determined by Bitcoin pricing, we obtain some interesting results. Higher persistence of price shocks is observed after the crash, which is probably due to speculative transactions among cryptocurrency traders, and more evidences of non-mean reversions are revealed, implying chances of further price fall in cryptocurrencies. Cointegration relationships between bitcoin and alternative coins exist in both periods, with weak correlations observed mostly in the post-crash period. Our results further indicate the possibility of market efficiency between pair of cryptocurrency. Generally, we hope the findings will serve as guide to investors in cryptocurrency markets.

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  • Yaya, OlaOluwa S. & Ogbonna, Ahamuefula E. & Olubusoye, Olusanya E., 2019. "How persistent and dynamic inter-dependent are pricing of Bitcoin to other cryptocurrencies before and after 2017/18 crash?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
    • Handle: RePEc:eee:phsmap:v:531:y:2019:i:c:s0378437119309902
    DOI: 10.1016/j.physa.2019.121732
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    More about this item

    Keywords

    Cointegration; Cryptocurrency; Fractional integration; Fractional cointegration; Vector autoregression;
    All these keywords.

    JEL classification:

    • 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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