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Are Bitcon returns predictable?: Evidence from technical indicators

Author

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  • Liu, Li

Abstract

We examine the predictive ability of technical indicators for excess returns to Bitcoin prices. Our out-of-sample evidence suggests the existence of significant return predictability. Combining all technical information results in out-of-sample R2 as high as 0.523%. The dynamic strategy based on the return forecasts from combining technical information achieves the CER gains greater than 130%.

Suggested Citation

  • Liu, Li, 2019. "Are Bitcon returns predictable?: Evidence from technical indicators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 533(C).
  • Handle: RePEc:eee:phsmap:v:533:y:2019:i:c:s0378437119311380
    DOI: 10.1016/j.physa.2019.121950
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    Citations

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    Cited by:

    1. David L. John & Sebastian Binnewies & Bela Stantic, 2024. "Cryptocurrency Price Prediction Algorithms: A Survey and Future Directions," Forecasting, MDPI, vol. 6(3), pages 1-35, August.
    2. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2022. "Cryptocurrency returns under empirical asset pricing," International Review of Financial Analysis, Elsevier, vol. 82(C).
    3. Yuze Li & Shangrong Jiang & Xuerong Li & Shouyang Wang, 2022. "Hybrid data decomposition-based deep learning for Bitcoin prediction and algorithm trading," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-24, December.

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