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| Title: | 投資訊號之演化性辨識:機制設計的研究與應用 |
| Authors: | 郭子文 |
| Contributors: | 陳樹衡
郭子文 |
| Keywords: | 計算智慧
遺傳規劃
過度學習
交易策略
股票市場 |
| Date: | 2004 |
| Issue Date: | 2009-09-14 13:24:37 (UTC+8) |
| Abstract: | 隨著計算智慧(Computational Intelligence)工具的發展日益成熟, 將這些工具應用在經濟或財務問題上的文章逐漸增多, 國際上對這塊跨科際的研究領域愈來愈重視, 本論文討論和使用的工具是演化計算中的遺傳規劃(Genetic Programming)。
很多應用遺傳規劃的文章,經常被人質疑的一個問題是參數的任意設定,
參數任意或故意的設定是否會影響搜尋的速度或結果,是很多使用者所關心的; 除了參數設定的問題之外,也會有人質疑應用強大的搜尋工具是否會發生過度學習, 關於這些質疑,本論文仔細討論應用此工具時應該注意的參數設定和相關問題, 同時也討論關於過度學習和學習不足的問題,並提出一些心得,可以作為遺傳規劃使用者的參考。
除了討論這些問題之外,本論文使用這些經驗和心得,實際應用在交易策略尋找的問題上, 其中一個應用範圍是關於跨國資金流動的問題,另一個則應用在股票市場。 由以前相關的文獻可以知道,使用遺傳規劃演化出來的交易策略通常是複雜而且不易閱讀, 如果希望遺傳規劃能夠真正對投資者有所幫助,除了交易策略是否能夠獲利之外, 如何改善策略不易閱讀是很重要的問題。 本論文也針對這個問題提出方法並且實際應用在股票市場,
結果發現尋找出來的交易策略不但有超額報酬而且策略簡單易懂。 |
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| Description: | 博士
國立政治大學
經濟研究所
87258502
93 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0087258502 |
| Data Type: | thesis |
| Appears in Collections: | [經濟學系] 學位論文
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