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題名 Bounded Rationality and Market Micro-Behaviors: Case Studies Based on Agent-Based Double Auction Markets
作者 陳樹衡
Chen, Shu-Heng ; Zeng, Ren-Jie ; Yu, Tina ; Wang, Shu G.
貢獻者 經濟系
日期 2011
上傳時間 20-Mar-2014 16:24:33 (UTC+8)
摘要 We investigate the dynamics of trader behaviors using an agent-based genetic programming system to simulate double-auction markets. The objective of this study is two-fold. First, we seek to evaluate how, if any, the difference in trader rationality/intelligence influences trading behavior. Second, besides rationality, we also analyze how, if any, the co-evolution between two learnable traders impacts their trading behaviors. We have found that traders with different degrees of rationality may exhibit different behavior depending on the type of market they are in. When the market has a profit zone to explore, the more intelligent trader demonstrates more intelligent behaviors. Also, when the market has two learnable buyers, their co-evolution produced more profitable transactions than when there was only one learnable buyer in the market. We have analyzed the trading strategies and found the learning behaviors are very similar to humans in decision-making. We plan to conduct human subject experiments to validate these results in the near future.
關聯 Multi-Agent Applications with Evolutionary Computation and Biologically Inspired Technologies: Intelligent Techniques for Ubiquity and Optimization, IGI Global, 78-94
資料類型 book/chapter
DOI http://dx.doi.org/10.4018/978-1-60566-898-7.ch005
dc.contributor 經濟系en_US
dc.creator (作者) 陳樹衡zh_TW
dc.creator (作者) Chen, Shu-Heng ; Zeng, Ren-Jie ; Yu, Tina ; Wang, Shu G.en_US
dc.date (日期) 2011en_US
dc.date.accessioned 20-Mar-2014 16:24:33 (UTC+8)-
dc.date.available 20-Mar-2014 16:24:33 (UTC+8)-
dc.date.issued (上傳時間) 20-Mar-2014 16:24:33 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/64746-
dc.description.abstract (摘要) We investigate the dynamics of trader behaviors using an agent-based genetic programming system to simulate double-auction markets. The objective of this study is two-fold. First, we seek to evaluate how, if any, the difference in trader rationality/intelligence influences trading behavior. Second, besides rationality, we also analyze how, if any, the co-evolution between two learnable traders impacts their trading behaviors. We have found that traders with different degrees of rationality may exhibit different behavior depending on the type of market they are in. When the market has a profit zone to explore, the more intelligent trader demonstrates more intelligent behaviors. Also, when the market has two learnable buyers, their co-evolution produced more profitable transactions than when there was only one learnable buyer in the market. We have analyzed the trading strategies and found the learning behaviors are very similar to humans in decision-making. We plan to conduct human subject experiments to validate these results in the near future.en_US
dc.format.extent 146 bytes-
dc.format.mimetype text/html-
dc.language.iso en_US-
dc.relation (關聯) Multi-Agent Applications with Evolutionary Computation and Biologically Inspired Technologies: Intelligent Techniques for Ubiquity and Optimization, IGI Global, 78-94en_US
dc.title (題名) Bounded Rationality and Market Micro-Behaviors: Case Studies Based on Agent-Based Double Auction Marketsen_US
dc.type (資料類型) book/chapteren
dc.identifier.doi (DOI) 10.4018/978-1-60566-898-7.ch005en_US
dc.doi.uri (DOI) http://dx.doi.org/10.4018/978-1-60566-898-7.ch005en_US