Please use this identifier to cite or link to this item:
https://ah.lib.nccu.edu.tw/handle/140.119/54182| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | 廖四郎 | zh_TW |
| dc.contributor.author | 戴維志 | zh_TW |
| dc.creator | 戴維志 | zh_TW |
| dc.date | 2011 | en_US |
| dc.date.accessioned | 2012-10-30T02:14:54Z | - |
| dc.date.available | 2012-10-30T02:14:54Z | - |
| dc.date.issued | 2012-10-30T02:14:54Z | - |
| dc.identifier | G0099352002 | en_US |
| dc.identifier.uri | http://nccur.lib.nccu.edu.tw/handle/140.119/54182 | - |
| dc.description | 碩士 | zh_TW |
| dc.description | 國立政治大學 | zh_TW |
| dc.description | 金融研究所 | zh_TW |
| dc.description | 99352002 | zh_TW |
| dc.description | 100 | zh_TW |
| dc.description.abstract | 近年來，在財務領域中，有越來越多的人想藉助人工智慧系統來幫助我們做預測與處理最佳化的問題，而類神經網路與基因演算法為兩種最常見的處理系統，可幫助我們監控與做出適當的決策。而本文特別針對以上兩種系統，分別在不同的領域中，做出適當的應用。\n\n在類神經網路方面，本文試圖結合配對交易來建構出一套能獲利的交易模式。由於在配對交易的部分，進出場時機的門檻值是影響獲利的一大重要關鍵，因此若能利用類神經網路輔佐我們的交易並預測適當的進出場時機，或許可提高我們的交易績效與報酬。\n\n而在基因演算法的部分，由於此演算法的最主要功能是處理最佳化問題，因此本文試圖用基因演算法建構最佳化的投資組合，結果指出，利用此方法所得之投資組合在單位風險值的衡量之下，有較好的報酬表現。 | zh_TW |
| dc.description.tableofcontents | 1.序論 6\n1.1研究動機與目的 6\n1.2研究架構 7\n2.文獻回顧 8\n2.1類神經網路相關文獻整理 8\n2.2基因演算法相關文獻整理 10\n3.研究方法 13\n3.1類神經網路相關介紹 13\n3.1.1簡介 13\n3.1.2處理模型 15\n3.1.3學習策略 17\n3.1.4倒傳遞類神經網路 18\n3.2配對交易簡介 22\n3.3基因演算法相關介紹 24\n3.3.1簡介 24\n3.3.2演算法則 25\n3.3.3模仿機制的運作過程 27\n3.3.4最佳化範例 30\n4.實證研究 33\n4.1類神經網路結合配對交易 33\n4.1.1資料選取與樣本期間 33\n4.1.2實證流程 33\n4.1.3價差計算與價差平均值、標準差的決定 34\n4.1.4類神經網路的訓練與預測 38\n4.1.4交易邏輯與績效 40\n4.2基因演算法建構最佳投資組合 42\n4.2.1資料選取與樣本期間 42\n4.2.2實證流程 42\n4.2.3編碼方式的決定與相關參數的設定 43\n4.2.4適應函數的決定 44\n4.2.5建構投資組合並檢視其績效 44\n5.結論 47\n參考文獻 48 | zh_TW |
| dc.language.iso | en_US | - |
| dc.source.uri | http://thesis.lib.nccu.edu.tw/record/#G0099352002 | en_US |
| dc.subject | 類神經網路 | zh_TW |
| dc.subject | 基因演算法 | zh_TW |
| dc.title | 類神經網路與基因演算法在投資策略上的應用 | zh_TW |
| dc.title | The application of artificial neural network and genetic algorithm on investment strategy | en_US |
| dc.type | thesis | en |
| dc.relation.reference | 李忠和 (2007) , 相對價值套利法則－台灣股市之配對交易績效分析 , 逢甲大學經濟學系碩士班碩士論文。\n\n林萍珍 (2008) , 投資分析:含Matlab應用、類神經網路與遺傳演算法模型 , 新陸書局出版。\n\n林逸塵 (2002) , 類神經網路應用於空氣品質預測之研究 , 國立中山大學環境工程研究所碩士論文。\n\n羅華強 (2005) , 類神經網路 - MATLAB的應用 , 高立圖書出版。\n\n蘇木春、張孝德 (2004) , 機器學習:類神經網路、模糊系統以及基因演算法則 , 全華圖書出版。\n\nChang, P. C., Liu, C. H., Lin, J. L., Fan, C.Y., and Celeste S.P. Ng. (2009)\nA neural network with a case based dynamic window for stock trading prediction. Expert Systems with Applications 36, 6889–6898.\n\nChavarnakul, T and Enke, D. (2008) Intelligent technical analysis based equivolume charting for stock trading using neural networks. Expert Systems with Applications 34, 1004–1017.\n\nFaria, E. L., Albuquerque, M. P., Gonzalez, J.L., Cavalcante, J.T.P., and Albuquerque, M. P. (2009) Predicting the Brazilian stock market through neural networks and adaptive exponential smoothing methods. Expert Systems with Applications, 36, 12506–12509.\n\nHuang, C. F. (2012) A hybrid stock selection model using genetic algorithms and support vector regression. Applied Soft Computing , 12 , 807–818.\n\nJasemi, M., Kimiagari, A. M. and Memariani, A. (2011) A modern neural network model to do stock market timing on the basis of the ancient investment technique of Japanese Candlestick. Expert Systems with Applications 38, 3884–3890.\n\nLiao, Z. and Wang, J.(2010) Forecasting model of global stock index by stochastic time effective neural network. Expert Systems with Applications 37, 834–841.\n\nLin, C. C. and Liu, Y. T. (2008) Genetic algorithms for portfolio selection problems with minimum transaction lots. European Journal of Operational Research , 185 , 393–404.\n\nLin, P. C. and Ko, P. C. (2009) Portfolio value-at-risk forecasting with GA-based extreme value theory. Expert Systems with Applications 36, 2503–2512.\n\n\nOh, K. J., Kim, T. Y., Min, S. H. and Lee H.Y. (2006) Portfolio algorithm based on portfolio beta using genetic algorithm. Expert Systems with Applications 30, 527–534.\n\nPotvina, J. Y., Sorianoa P. and Vall`ee, M. (2004) Generating trading rules on the stock markets with genetic programming. Computers & Operations Research 31, 1033–1047.\n\nVidyamurthy, G. (2004) Pairs Trading: Quantitative Methods and Analysis, John Wiley & Sons. | zh_TW |
| item.grantfulltext | none | - |
| item.openairecristype | http://purl.org/coar/resource_type/c_46ec | - |
| item.fulltext | No Fulltext | - |
| item.languageiso639-1 | en_US | - |
| item.cerifentitytype | Publications | - |
| item.openairetype | thesis | - |
| Appears in Collections: | 學位論文 | |
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