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Taylor effect in Bitcoin time series

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  • Takaishi, Tetsuya
  • Adachi, Takanori

Abstract

This letter investigates the Taylor effect in Bitcoin time series. It is found that the Taylor effect exists in Bitcoin, and the value of the power that maximizes the autocorrelation of the power of absolute returns depends on a time lag in the autocorrelation function. While the Taylor effect of foreign exchange rates has a daily seasonality, we could not find any daily seasonality in the Taylor effect of Bitcoin.

Suggested Citation

  • Takaishi, Tetsuya & Adachi, Takanori, 2018. "Taylor effect in Bitcoin time series," Economics Letters, Elsevier, vol. 172(C), pages 5-7.
    • Handle: RePEc:eee:ecolet:v:172:y:2018:i:c:p:5-7
    DOI: 10.1016/j.econlet.2018.07.046
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    References listed on IDEAS

    as
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    Citations

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    Cited by:

    1. Corbet, Shaen & Lucey, Brian & Urquhart, Andrew & Yarovaya, Larisa, 2019. "Cryptocurrencies as a financial asset: A systematic analysis," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 182-199.
    2. Tetsuya Takaishi, 2019. "Rough volatility of Bitcoin," Papers 1904.12346, arXiv.org.
    3. Tetsuya Takaishi & Takanori Adachi, 2019. "Market efficiency, liquidity, and multifractality of Bitcoin: A dynamic study," Papers 1902.09253, arXiv.org.
    4. Aurelio F. Bariviera & Ignasi Merediz‐Solà, 2021. "Where Do We Stand In Cryptocurrencies Economic Research? A Survey Based On Hybrid Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 377-407, April.
    5. Ting-Hsuan Chen & Mu-Yen Chen & Guan-Ting Du, 2021. "The Determinants of Bitcoin’s Price: Utilization of GARCH and Machine Learning Approaches," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 267-280, January.
    6. T. Takaishi, 2021. "Power-Law Return-Volatility Cross Correlations of Bitcoin," Papers 2102.08187, arXiv.org.
    7. Huthaifa Alqaralleh & Alaa Adden Abuhommous & Ahmad Alsaraireh, 2020. "Modelling and Forecasting the Volatility of Cryptocurrencies: A Comparison of Nonlinear GARCH-Type Models," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 11(4), pages 346-356, July.
    8. Tetsuya Takaishi & Takanori Adachi, 2020. "Market Efficiency, Liquidity, and Multifractality of Bitcoin: A Dynamic Study," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(1), pages 145-154, March.
    9. de la Horra, Luis P. & de la Fuente, Gabriel & Perote, Javier, 2019. "The drivers of Bitcoin demand: A short and long-run analysis," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 21-34.
    10. Takaishi, Tetsuya, 2020. "Rough volatility of Bitcoin," Finance Research Letters, Elsevier, vol. 32(C).
    11. da Cunha, C.R. & da Silva, R., 2020. "Relevant stylized facts about bitcoin: Fluctuations, first return probability, and natural phenomena," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    12. Tetsuya Takaishi, 2021. "Time-varying properties of asymmetric volatility and multifractality in Bitcoin," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-21, February.
    13. Nikolaos A. Kyriazis, 2019. "A Survey on Efficiency and Profitable Trading Opportunities in Cryptocurrency Markets," JRFM, MDPI, vol. 12(2), pages 1-17, April.
    14. Tetsuya Takaishi, 2021. "Time-varying properties of asymmetric volatility and multifractality in Bitcoin," Papers 2102.07425, arXiv.org.

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    More about this item

    Keywords

    Taylor effect; Bitcoin; Cryptocurrency; Autocorrelation;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • G1 - Financial Economics - - General Financial Markets

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