Performance and learning in an ambiguous environment : A study of cryptocurrency traders

Roland GEMAYEL*, Alex PREDA

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

7 Citations (Scopus)

Abstract

We investigate the performance and learning ability of traders in an environment governed by ambiguity, such as the cryptocurrency market. Using a profit decomposition methodology, we find significant cross-sectional and temporal heterogeneity in performance. Traders do not learn to progressively increase the magnitude of returns; however, they are able to improve on their ability to realise profits as a mechanism of adaptation to survive through ambiguity. This adaptation increases as traders progress through their career. Moreover, we find evidence in support of the gambler's fallacy. We argue that learning in ambiguous environments has limitations, allowing traders primarily to survive.

Original languageEnglish
Article number101847
JournalInternational Review of Financial Analysis
Volume77
Early online date29 Jul 2021
DOIs
Publication statusPublished - Oct 2021
Externally publishedYes

Bibliographical note

Funding Information:
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. We are very grateful to the anonymous referees for their invaluable feedback and constructive suggestions.

Publisher Copyright:
© 2021 The Authors

Keywords

  • Ambiguity
  • Cryptocurrencies
  • Learning
  • Performance appraisal
  • Skill
  • Trading

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