Risk aversion and Bitcoin returns in extreme quantiles

Elie Bouri, Rangan Gupta, Chi Keung Marco Lau, David Roubaud

Research output: Contribution to journalArticlepeer-review

52 Downloads (Pure)

Abstract

We study whether level of risk aversion can be used to predict Bitcoin returns using copulas and quantile-based models. We find evidence of predictability when the market return is at extreme quantiles. Further analyses show that the cross-quantilogram is similar when risk aversion is at the low or medium level for various quantiles of Bitcoin returns. The predictability is positive when the risk aversion is at very low level. However, predictability becomes negative when both the risk aversion and Bitcoin returns are very high, suggesting that when risk aversion and Bitcoin returns are at very high levels, Bitcoin is less likely to have large gains.
Original languageEnglish
JournalEconomics Bulletin
Publication statusAccepted/In press - 23 Jul 2021

Fingerprint

Dive into the research topics of 'Risk aversion and Bitcoin returns in extreme quantiles'. Together they form a unique fingerprint.

Cite this