TY - JOUR
T1 - On the drivers of technical analysis profits in cryptocurrency markets
T2 - A distributed lag approach
AU - Bazán-Palomino, Walter
AU - Svogun, Daniel
N1 - Publisher Copyright:
© 2023 Elsevier Inc.
PY - 2023/3
Y1 - 2023/3
N2 - 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.
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.
KW - Asset bubbles
KW - Cryptocurrency
KW - Technical analysis
KW - Transaction costs
UR - http://www.scopus.com/inward/record.url?scp=85146060187&partnerID=8YFLogxK
U2 - 10.1016/j.irfa.2023.102516
DO - 10.1016/j.irfa.2023.102516
M3 - Article in a journal
AN - SCOPUS:85146060187
SN - 1057-5219
VL - 86
JO - International Review of Financial Analysis
JF - International Review of Financial Analysis
M1 - 102516
ER -