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Causal Relationship Between Bitcoin Price Volatility And Trading Volume: Rolling Window Approach

Author

Listed:
  • YAMAK, Nebiye

    (Karadeniz Technical University, Faculty of Economics and Administrative Sciences, Department of Economics, Trabzon, Turkey.)

  • YAMAK, Rahmi

    (Karadeniz Technical University, Faculty of Economics and Administrative Sciences, Department of Econometrics, Trabzon, Turkey.)

  • SAMUT, Serkan

    (Karadeniz Technical University, Faculty of Economics and Administrative Sciences, Department of Econometrics, Trabzon, Turkey.)

Abstract

This study investigates the causal relationship between price volatility and trading volume for bitcoin which is the first cryptocurrency. Data are daily and cover the period starting from December 27, 2013 to March 3, 2019. Price volatility series was produced by using EGARCH model. The Toda-Yamamoto causality test was applied under rolling window approach. According to the Granger causality test, there is a strong causal relationship running from the trading volume to the price volatility. There also exists a causality running from price volatility to volume. But this causality is not statistically strong. At the same time, a positive and significant contemporaneous correlation was found between the two variables. Both findings support the sequential information arrival hypothesis for the bitcoin market. Classification-JEL: C22, G14

Suggested Citation

  • YAMAK, Nebiye & YAMAK, Rahmi & SAMUT, Serkan, 2019. "Causal Relationship Between Bitcoin Price Volatility And Trading Volume: Rolling Window Approach," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 23(3), pages 6-20, September.
    • Handle: RePEc:vls:finstu:v:23:y:2019:i:3:p:6-20
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    References listed on IDEAS

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    Cited by:

    1. Adeyinka Adediran & Bola Babajide & Nataliia Osina, 2023. "Exploring the nexus between price and volume changes in the cryptocurrency market," Journal of Asset Management, Palgrave Macmillan, vol. 24(6), pages 498-512, October.

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    More about this item

    Keywords

    sequential information arrival hypothesis; Toda-Yamamoto causality; cryptocurrency;
    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
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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