On the drivers of technical analysis profits in cryptocurrency markets: A distributed lag approach

Walter Bazán-Palomino; Daniel Svogun

doi:10.1016/j.irfa.2023.102516

On the drivers of technical analysis profits in cryptocurrency markets: A distributed lag approach

Walter Bazán-Palomino, Daniel Svogun

Universidad del Pacífico

Producción científica: Contribución a una revista › Artículo de revista › revisión exhaustiva

7 Citas (Scopus)

Resumen

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.

Idioma original	Inglés
Número de artículo	102516
Publicación	International Review of Financial Analysis
Volumen	86
Fecha en línea anticipada	11 ene. 2023
DOI	https://doi.org/10.1016/j.irfa.2023.102516
Estado	Publicada - mar. 2023

Nota bibliográfica

Funding Information:
We gratefully acknowledge Dr. Richard Gallenstein for his helpful comments and feedback on early versions of this paper. as well as other guidance from colleagues at CUA and Universidad del Pacífico.

Publisher Copyright:
© 2023 Elsevier Inc.

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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.",

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AB - 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.

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On the drivers of technical analysis profits in cryptocurrency markets: A distributed lag approach

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