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研究生:洪俊瑋
研究生(外文):Chun-Wei Hung
論文名稱:以建諸於移動平均法之類神經模糊系統預測股價指數之變動
論文名稱(外文):Using the Moving Average Based Neuro Fuzzy System to Forecast the Change of Stock Index
指導教授:林金賢林金賢引用關係
指導教授(外文):Chin-Shien Lin
學位類別:碩士
校院名稱:靜宜大學
系所名稱:企業管理研究所
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:2004
畢業學年度:92
語文別:中文
論文頁數:77
中文關鍵詞:類神經模糊移動平均法拔靴法股價指數
外文關鍵詞:Moving AverageNeuro FuzzyBootstrap MethodStock Index
相關次數:
  • 被引用被引用:6
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  • 下載下載:104
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許多學者對「效率市場假說(EMH)」說提出質疑,而以各種不同的技術交易法則(technical trading rule)來檢驗證券價格的可預測性,進一步說明弱效率市場(weak form market)並不存在。而本研究的目的在比較買入持有、移動平均法、移動平均法含門檻值、結合移動平均法之類神經模糊系統等四種交易策略,在預測包括道瓊工業指數、那斯達克指數、英國FT100指數、法國SBF250以及台灣加權股價指數等五個大盤股價指數變動之績效。而透過模擬交易,研究結果發現加入門檻值的移動平均法能在那斯達克指數、英國FT100指數、法國SBF250三個市場得到最高的報酬率;以類神經模糊系統的預測結果進行交易則可以在道瓊工業指數與台灣加權股價指數兩個市場得到最高的報酬率。而風險的部分則以包含門檻值的移動平均法表現最好,在所有的市場皆能得到最小的值。

而類神經模糊系統在變化較劇烈的台灣加權股價指數預測績效特別出色,因此我們分別以AR(1)、GARCH-M、EGARCH等時間序列模型進行拔靴法來模擬產生新的數列,驗證此系統並非只有在樣本期間內才能獲得較其他方法更高的報酬率。由結果可以看出此系統確實在所有的模擬數列皆可得到最高的報酬,且落差值的表現也相當出色,顯示出此結合移動平均法之類神經模糊系統確實在預測台灣加權股價指數與模擬數列都能得到不錯的機效。
The purpose of this research is examining the profitability of technical trading rules in Dow Jones Industry Index, NASDAQ Index, FT 100, SBF 250 and Taiwan Weighted Stock Index. The strategies we used are buy and hold, moving average, moving average containing threshold and moving average based neuro fuzzy system. According to result, we find out that the contained threshold’s moving average can earn the highest return in NASDAQ Index, FT 100 and SBF 250, it also has the lowest risk value in all index.

Although the contained threshold’s moving average has better utility then other strategies, we find that the moving average based neuro fuzzy system had higher forecasting power in changeable series than other strategies, such as Taiwan Weighted Stock Index. As Brock et al. did in 1992; we use the bootstrap method to generate some simulated series to examine the robustness of our finding. And the results show this neuro fuzzy system has highest positive return in all artificial series, and the risk of this system are also very low. This means this neuro fuzzy system really has forecasting power in Taiwan Weight Stock Index, not just by chance.
中文摘要 I
英文摘要 II
目錄 III
表目錄 IV
圖目錄 V
第一章 緒論 1
第一節 研究動機 1
第二節 研究目的 2
第三節 研究限制 4
第四節 研究流程 5
第二章 文獻探討 7
第一節 效率市場的探討 7
第二節 技術分析理論 10
第三節 移動平均指標 20
第四節 類神經模糊理論 22
第五節 拔靴法 35
第三章 研究方法 40
第一節 研究樣本與期間 40
第二節 建構類神經模糊預測系統 44
第三節 拔靴法的操作 52
第四節 模擬交易 55
第五節 獲利能力與風險衡量指標 56
第四章 實證結果 58
第一節 模擬交易結果之報酬率比較 58
第二節 模擬交易的風險衡量 60
第三節 模型的檢定與估計 62
第四節 拔靴法之實證結果 64
第五章 結論與建議 71
第一節 研究結論 71
第二節 研究建議 72
參考書目 73
參考書目
壹、中文部分
一、書籍
葉怡成,「類神經網路模式應用與時作」,台北市:儒林圖書有限公司,民國八十四年,四版。
孫宗瀛、楊英魁,「Fuzzy 控制:理論、實做與應用」,台北市:金華科技圖書股份有限公司,民國八十三年,初版。
陳進忠,「證券投資技術分析」,台灣台北:台灣實業文化出版,民國八十八年,初版。
秉昱科技,「模糊邏輯與類神經模糊在商業和財政的應用」,台北:儒林,民國九十年,二版。
Murphy, J.J.,「金融市場技術分析」,台北市:寰宇出版股份有限公司,民國八十九年。

二、期刊
黃彥聖,民國八十四年一月,移動平均法的投資績效,管理評論第十四卷 第一期,47-68。



貳、西文部份
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Wolberg, R.J. “Expert trading systems: modeling financial markets with kernel regression,” New York: Wiley, 2000.

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