Please use this identifier to cite or link to this item:
https://ah.lib.nccu.edu.tw/handle/140.119/64754
DC Field | Value | Language |
---|---|---|
dc.contributor | 經濟系 | en_US |
dc.creator | 陳樹衡 | zh_TW |
dc.creator | Kampouridis, Michael ; Chen, Shu-Heng ; Tsang, Edward | en_US |
dc.date | 2012 | en_US |
dc.date.accessioned | 2014-03-20T08:57:55Z | - |
dc.date.available | 2014-03-20T08:57:55Z | - |
dc.date.issued | 2014-03-20T08:57:55Z | - |
dc.identifier.uri | http://nccur.lib.nccu.edu.tw/handle/140.119/64754 | - |
dc.description.abstract | This chapter presents a market microstructure model, which investigates the behavior dynamics in financial markets. We are especially interested in examining whether the markets’ behavior is non-stationary, because this implies that strategies from the past cannot be applied to future time periods, unless they have co-evolved with the markets. In order to test this, we employ Genetic Programming, which acts as an inference engine for trading rules, and Self-Organizing Maps, which is used for clustering the above rules into types of trading strategies. The results on four empirical financial markets show that their behavior constantly changes; thus, agents’ trading strategies need to continuously adapt to the changes taking place in the market, in order to remain effective. | en_US |
dc.format.extent | 427761 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | en_US | - |
dc.relation | Natural Computing in Computational Finance Studies in Computational Intelligence Volume 380, 2012, pp 181-197 | en_US |
dc.title | Market Microstructure: A Self-Organizing Map Approach to Investigate Behavior Dynamics under an Evolutionary Environment | en_US |
dc.type | book/chapter | en |
item.languageiso639-1 | en_US | - |
item.cerifentitytype | Publications | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.grantfulltext | open | - |
item.openairetype | book/chapter | - |
item.fulltext | With Fulltext | - |
Appears in Collections: | 專書/專書篇章 |
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File | Description | Size | Format | |
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181197.pdf | 417.74 kB | Adobe PDF2 | View/Open |
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