The impact of imitation on long memory in an order-driven market

Blake LeBaron*, Ryuichi Yamamoto

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)


Recent research has documented that learning and evolution are capable of generating many well-known features in financial times series. We extend the results of LeBaron and Yamamoto (2007) to explore the impact of varying amounts of imitation and agent learning in a simple order-driven market. We show that in our framework, imitation is critical to the generation of long memory persistence in many financial time series. This shows that imitation across trader behavior is probably crucial for understanding the dynamics of prices and trading volume.

Original languageEnglish
Pages (from-to)504-517
Number of pages14
JournalEastern Economic Journal
Issue number4
Publication statusPublished - 2008
Externally publishedYes

ASJC Scopus subject areas

  • Economics and Econometrics


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