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題名 An Order-Driven Agent-Based Artificial Stock Market to Analyze Liquidity Costs of Market Orders in the Taiwan Stock Market
作者 陳樹衡
Huang, Yi-Ping ; Chen, Shu-Heng ; Hung, Min-Chin ; Yu, Tina
貢獻者 經濟系
日期 2011
上傳時間 20-Mar-2014 16:24:20 (UTC+8)
摘要 We developed an order-driven agent-based artificial stock market to analyze the liquidity costs of market orders in the Taiwan Stock Market (TWSE). The agent-based stock market was based on the DFGIS model proposed by Daniels, Farmer, Gillemot, Iori and Smith [2]. When tested on 10 stocks and securities in the market, the model-simulated liquidity costs were higher than those of the TWSE data. We identified some possible factors that have contributed to this result: 1) the overestimated effective market order size; 2) the random market orders arrival time designed in the DFGIS model; and 3) the zero-intelligence of the artificial agents in our model. We continued improving the model so that it could be used to study liquidity costs and to devise liquidation strategies for stocks and securities traded in the Taiwan Stock Market.
關聯 Natural Computing in Computational Finance Studies in Computational Intelligence Volume 380, 2012, pp 163-179
資料類型 book/chapter
DOI http://dx.doi.org/10.1007/978-3-642-23336-4_9
dc.contributor 經濟系en_US
dc.creator (作者) 陳樹衡zh_TW
dc.creator (作者) Huang, Yi-Ping ; Chen, Shu-Heng ; Hung, Min-Chin ; Yu, Tinaen_US
dc.date (日期) 2011en_US
dc.date.accessioned 20-Mar-2014 16:24:20 (UTC+8)-
dc.date.available 20-Mar-2014 16:24:20 (UTC+8)-
dc.date.issued (上傳時間) 20-Mar-2014 16:24:20 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/64745-
dc.description.abstract (摘要) We developed an order-driven agent-based artificial stock market to analyze the liquidity costs of market orders in the Taiwan Stock Market (TWSE). The agent-based stock market was based on the DFGIS model proposed by Daniels, Farmer, Gillemot, Iori and Smith [2]. When tested on 10 stocks and securities in the market, the model-simulated liquidity costs were higher than those of the TWSE data. We identified some possible factors that have contributed to this result: 1) the overestimated effective market order size; 2) the random market orders arrival time designed in the DFGIS model; and 3) the zero-intelligence of the artificial agents in our model. We continued improving the model so that it could be used to study liquidity costs and to devise liquidation strategies for stocks and securities traded in the Taiwan Stock Market.en_US
dc.format.extent 265136 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.relation (關聯) Natural Computing in Computational Finance Studies in Computational Intelligence Volume 380, 2012, pp 163-179en_US
dc.title (題名) An Order-Driven Agent-Based Artificial Stock Market to Analyze Liquidity Costs of Market Orders in the Taiwan Stock Marketen_US
dc.type (資料類型) book/chapteren
dc.identifier.doi (DOI) 10.1007/978-3-642-23336-4_9-
dc.doi.uri (DOI) http://dx.doi.org/10.1007/978-3-642-23336-4_9-