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

Walter Bazán-Palomino and Daniel Svogun

International Review of Financial Analysis, 2023, vol. 86, issue C

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.

Keywords: Technical analysis; Cryptocurrency; Transaction costs; Asset bubbles (search for similar items in EconPapers)
JEL-codes: G14 G20 G30 G32 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:86:y:2023:i:c:s1057521923000327

DOI: 10.1016/j.irfa.2023.102516

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