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A seesaw effect in the cryptocurrency market: Understanding the return cross predictability of cryptocurrencies

Author

Listed:
  • Jia, Yuecheng
  • Wu, Yangru
  • Yan, Shu
  • Liu, Yuzheng

Abstract

This paper investigates the intraday return cross-predictability of cryptocurrencies. In contrast to the positive lead–lag effect for stocks, we document a negative lead–lag effect in the cryptocurrency market. Specifically, the large coins negatively predict the other coins but the small coins rarely predict the large coins. A trading strategy that exploits the cross-predictability via the Least Absolute Shrinkage and Selection Operator (LASSO) yields highly significant profits across major cryptocurrency exchanges even in the presence of realistic transaction costs.

Suggested Citation

  • Jia, Yuecheng & Wu, Yangru & Yan, Shu & Liu, Yuzheng, 2023. "A seesaw effect in the cryptocurrency market: Understanding the return cross predictability of cryptocurrencies," Journal of Empirical Finance, Elsevier, vol. 74(C).
    • Handle: RePEc:eee:empfin:v:74:y:2023:i:c:s0927539823000956
    DOI: 10.1016/j.jempfin.2023.101428
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    Citations

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    Cited by:

    1. Timoth'ee Fabre & Ioane Muni Toke, 2024. "Neural Hawkes: Non-Parametric Estimation in High Dimension and Causality Analysis in Cryptocurrency Markets," Papers 2401.09361, arXiv.org, revised Jan 2024.

    More about this item

    Keywords

    Cryptocurrency; Cross predictability; Information spillover; Money flow;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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