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政大機構典藏 > 商學院 > 國際經營與貿易學系 > 期刊論文 > Item 140.119/78855

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/78855

Title:	Symposium on Agent-Based Computational Economics: The Impact of Imitation on Long Memory in an Order-Driven Market
Authors:	LeBaron, Blake;Yamamoto, Ryuichi 山本竜市
Contributors:	國貿系
Keywords:	learning;evolution;market microstructure;long memory
Date:	2008
Issue Date:	2015-10-02 16:43:42 (UTC+8)
Abstract:	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.
Relation:	Eastern Economic Journal, 34(4), 504-517
Data Type:	article
Appears in Collections:	[國際經營與貿易學系 ] 期刊論文

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File	Description	Size	Format
504-517(2).pdf		150Kb	Adobe PDF2	703	View/Open

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