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研究生:洪行春
研究生(外文):Hsing Chun Hung
論文名稱:應用類神經模糊技術預測台灣證劵市場-以高價股為例
論文名稱(外文):Using Neural-fuzzy Network Technology to Forecast Taiwan Stock Market:Case of the Higher Price Stocks
指導教授:盧建旭盧建旭引用關係李家豪李家豪引用關係
指導教授(外文):Lancelot LuChia -Hao Lee
學位類別:碩士
校院名稱:明道大學
系所名稱:企業高階管理碩士班
學門:商業及管理學門
學類:企業管理學類
論文種類:學術論文
論文出版年:2011
畢業學年度:99
語文別:中文
論文頁數:49
中文關鍵詞:類神經網路模糊邏輯高價股技術指標
外文關鍵詞:forecastingstock priceneural networkfuzzy logicNeuro-Fuzzy
相關次數:
  • 被引用被引用:1
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  • 下載下載:22
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本研究的主要目的在應用類神經模糊技術(Neuro-Fuzzy)結合RSI技術指標來找出股票最適之交易系統,以98年12月31日當日上市公司股價前四名的高價股為研究對象。以投資報酬率、累積財富與風險程度三項指標來衡量Neuro-Fuzzy交易系統。實證結果顯示,傳統RSI技術指標投資報酬無法超越買入持有策略,結合類神經模糊技術所依循之交易系統,不僅優於傳統RSI技術指標,同時也超越了買入持有策略投資績效。在累積財富的變化情形與風險指標上,也顯示類神經模糊交易系統的風險程度較RSI傳統技術指標與買入持有策略低。本研究的結果,顯現出類神經模糊對股價趨勢預測之準確性與穩定性。
關鍵字:類神經網路、模糊邏輯、高價股、技術指標
This paper aims to apply neuro-fuzzy to refine the RSI technical trading rules to forecast the Taiwan's stock market. Essentially in this hybrid technique, fuzzy logic plays the role to formulate the relationship among the RSI indexes and stock price changes by using knowledge base. Neural network is used to tune the formulated knowledge base based on historical data. The empirical results show that this hybrid technique could capture the relationship among the RSI indexes and stock price changes very effectively. The rate of return of this proposed trading system is significantly greater than that of both buy and hold strategy and traditional RSI trading system.
Key words: forecasting, stock price, neural network, fuzzy logic, Neuro-Fuzzy
摘 要 ...................................................................I
Abstract ...................................................................II
誌 謝 辭 ...................................................................III
表 目 錄 ...................................................................VI
圖 目 錄 ...................................................................VII
第一章 緒 論 ..........................................................1
第一節 研究背景與動機 .................................................1
第二節 研究目的 ..........................................................4
第三節 研究範圍與對象 .................................................5
第四節 章節架構 ..........................................................13
第二章 文獻探討 ..........................................................15
第一節 效率市場假說 .................................................15
第二節 類神經網路 ...........................................17
第三節 模糊邏輯 .......................................................18
第四節 類神經模糊邏輯 .................................................19
第五節 RSI技術指標 .......................................20
第三章 研究方法 ..........................................................24
第一節 研究樣本 ........................................................24
第二節 RSI技術指標模型 .................................................24
第三節 研究架構 .....................................................25
第四章 實證結果 ..........................................................40
第一節 投資報酬率 ................................................40
第二節 風險衡量 .....................................................41
第三節 累積財富變化 .................................................42
第五章 結論與建議 ..........................................................46
參考文獻 ...................................................................48
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