Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/48596
DC FieldValueLanguage
dc.creator陳樹衡zh_TW
dc.date2003-
dc.date.accessioned2010-11-24T14:10:45Z-
dc.date.available2010-11-24T14:10:45Z-
dc.date.issued2010-11-24T14:10:45Z-
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/48596-
dc.description.abstractIn this paper we conduct two experiments within an agent-based double auction market. These two experiments allow us to see the effect of learning and smartness on price dynamics and allocative efficiency. Our results are largely consistent with the stylized facts observed in experimental economics with human subjects. From the amelioration of price deviation and allocative efficiency, the effect of learning is vividly seen. However, smartness does not enhance market performance. In fact, the experiment with smarter agents (agents without a quote limit) results in a less stable price dynamics and lower allocative efficiency. [ABSTRACT FROM AUTHOR]-
dc.languagezh_TWen
dc.language.isoen_US-
dc.relationAdvances in Complex Systems,6(3),283-302en
dc.titleTrading Restrictions Price Dynamics and Allocative Efficiency in Double Auction Markets:Analysis Based on Agent-Based Modeling and Simulationsen
dc.typearticleen
dc.identifier.doi10.1142/S021952590300089X-
dc.doi.urihttp://dx.doi.org/10.1142/S021952590300089X-
item.fulltextWith Fulltext-
item.grantfulltextopen-
item.openairetypearticle-
item.languageiso639-1en_US-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
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