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Cryptocurrency Returns before and after the Introduction of Bitcoin Futures

Author

Listed:
  • Pinar Deniz

    (Department of Economics, Marmara University, Istanbul 34722, Turkey)

  • Thanasis Stengos

    (Department of Economics, University of Guelph, Guelph, ON N1G 2W1, Canada)

Abstract

This paper examines the behaviour of Bitcoin returns and those of several other cryptocurrencies in the pre and post period of the introduction of the Bitcoin futures market. We use the principal component-guided sparse regression (PC-LASSO) model to analyze several sample sizes for the pre and post periods. Besides the neighbourhood of the break time, the current period is also investigated as returns start to recover after some time. Search intensity is observed to be the most important variable for Bitcoin for all periods, whereas for the other cryptocurrencies there are other variables that seem more important in the pre period, while search intensity still stands out in the post period. Furthermore, GARCH analyses suggest that search intensity increases the volatility of Bitcoin returns more in the post period than it does in the pre period. Our empirical findings suggest that the top five cryptocurrencies are substitutes before the launch of Bitcoin futures. However, this effect is lost, and moreover, there are spillover effects on altcoins during both the post and the recovery period. We find a spillover effect of the introduction of bitcoin futures on altcoins and this effect seems to persist during the recovery period.

Suggested Citation

  • Pinar Deniz & Thanasis Stengos, 2020. "Cryptocurrency Returns before and after the Introduction of Bitcoin Futures," JRFM, MDPI, vol. 13(6), pages 1-21, June.
    • Handle: RePEc:gam:jjrfmx:v:13:y:2020:i:6:p:116-:d:367403
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    References listed on IDEAS

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    Cited by:

    1. Hui Xiao & Yiguo Sun, 2020. "Forecasting the Returns of Cryptocurrency: A Model Averaging Approach," JRFM, MDPI, vol. 13(11), pages 1-15, November.
    2. Thanasis Stengos, 2021. "Recent Developments in Cryptocurrency Markets: Co-Movements, Spillovers and Forecasting," JRFM, MDPI, vol. 14(3), pages 1-3, February.
    3. Beatriz Vaz de Melo Mendes & André Fluminense Carneiro, 2020. "A Comprehensive Statistical Analysis of the Six Major Crypto-Currencies from August 2015 through June 2020," JRFM, MDPI, vol. 13(9), pages 1-21, August.
    4. Weige Huang & Xiang Gao, 2023. "Forecasting Bitcoin Futures: A Lasso-BMA Two-Step Predictor Selection for Investment and Hedging Strategies," SAGE Open, , vol. 13(1), pages 21582440231, January.

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