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On the drivers of technical analysis profits in cryptocurrency markets: A Distributed Lag approach

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  • Bazán-Palomino, Walter
  • Svogun, Daniel

Abstract

The cryptocurrency literature on technical analysis has largely ignored drivers of technical analysis return adjusted by transaction costs (i.e., adjusted returns). To that end, we propose a Heterogeneous Autoregressive Distributed Lag Model of Returns (HARDL-R) to examine the impact from EPU, VIX, and SP500 returns to adjusted returns. We provide evidence that these three drivers matter during bubble periods compared to non-bubble periods. When not differentiating bubble periods, we find that VIX is the only driver influencing the dynamics of adjusted returns from 2016 to 2021. These findings remain relatively stable after controlling for the volume of transactions.

Suggested Citation

  • Bazán-Palomino, Walter & Svogun, Daniel, 2023. "On the drivers of technical analysis profits in cryptocurrency markets: A Distributed Lag approach," International Review of Financial Analysis, Elsevier, vol. 86(C).
    • Handle: RePEc:eee:finana:v:86:y:2023:i:c:s1057521923000327
    DOI: 10.1016/j.irfa.2023.102516
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    Cited by:

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    More about this item

    Keywords

    Technical analysis; Cryptocurrency; Transaction costs; Asset bubbles;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G30 - Financial Economics - - Corporate Finance and Governance - - - General
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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