From copy to practice: Followers' learning behavior in forex social trading

Mengli Yu, Yijing Li, Zhao Cai, Fei Liu, Chee Wee Tan

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review


Forex social trading platforms endows novice investors with opportunities to trade on foreign exchange markets by mimicking the investment strategies of sophisticated traders. But concurrently, the copy-trading mechanism underlying these platforms foster a conducive learning environment whereby inexperience followers could evolve into independent traders by observing and learning from the trading behaviors of prominent traders. Drawing on observational learning theory, we advance learning efficiency and effectiveness as focal yardsticks to encapsulate followers' learning performance and explore their effects on the profitability of followers' first independent trades. Preliminary analysis conducted on a leading forex social trading platform reveals that traders' trading consistency amplifies followers' learning efficiency whereas traders' profitability bolsters followers' learning effectiveness. Furthermore, while our empirical findings attest to the criticality of learning effectiveness on followers' ability to profit from their initial independent trades, speeding up the learning process may not guarantee better performance.

Original languageEnglish
Title of host publication40th International Conference on Information Systems, ICIS 2019
PublisherAssociation for Information Systems
ISBN (Electronic)9780996683197
Publication statusPublished - Dec 2019
Externally publishedYes
Event40th International Conference on Information Systems, ICIS 2019 - Munich, Germany
Duration: 15 Dec 201918 Dec 2019

Publication series

Name40th International Conference on Information Systems, ICIS 2019


Conference40th International Conference on Information Systems, ICIS 2019


  • Copy Trading
  • Forex Social Trading
  • Manual Trading
  • Observational Learning

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

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