盤價格作為預測目標,預測日期從 2010/1/4~2011/10/31 日,共 453 個天數。先 探討會對台股表現造成影響的國際主要股市、原油價格走向、總體經濟因素變化
‧
‧ 國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
65
參考文獻
[中央大學管理學院 ERP 中心,2010] 中央大學管理學院 ERP 中心,” 商業智慧”,中 壢, 滄海書局 2010.
[余世昌, 2002] 「台灣貨幣政策指標之研究」,政治大學行政管理碩士學程論文, 2002
[吳津苗, 2008] 「台灣、美國總經月數據與台股股價指數之關聯性」,中央大學產 業經濟研究所碩士論文, 2008
[蔡曉玲, 1993] 「台灣地區貨幣供給、匯率、分類股價因果關係實證分析」,淡江 大學金融研究所碩士論文, 1993
[邱建良, 1998] 「油價、貨幣供給及利率差對實質變數之影響」,淡江大學金融研 究所碩士論文, 1993
[鄭婉秀,吳佩珊,陳君達,陳玉瓏, 2005] 「貨幣政策、匯率與股價關連性之探討:
GARCH-IRF 模型之應用」,朝陽商管評論 4(2), p.73-92, 2005
[聶建中, 2005] 「美國油價期貨報酬與股市報酬率之非線性關係」,淡江大學金融 研究所碩士論文, 2005
[陳芝瑋, 2009] 「原油價格與國際主要股價相依結構之研究」,臺灣海洋大學應用 經濟研究所論文, 2009
[黃姿穎, 2009] 「油價、金價、匯率與國際股市之關聯性研究」,義守大學財務金 融所論文, 2009
[鄭鳳媚, 2010] 「國際油價波動下美股對臺股的非線性帄滑移轉關係探討」,淡江 大學金融研究所碩士論文, 2010
[張尹華, 2008] 「油價衝擊與股市績效:國際資金流動之跨國分析」,東海大學財 務金融學所碩士論文, 2008
[田宸瑄, 2007] 「國際油價、股市與景氣循環之相關分析-馬可夫轉換向量 誤差修正模型的運用」,世新大學財務金融學系碩士論文, 2007
‧
*Kohonen, 2001+ Teuvo Kohonen, “Self-organizing map” Springer,2001.
*Kohonen, Somervuo, 2002+ Teuvo Kohonen, Panu Somervuo, “How to make large self-organizing maps for nonvectorial data” Neural Networks, Vol.15, pp.945-952, 2002.
[Kosko, 1991] Bart Kosko, "Neural Networks and Fuzzy Systems: A Dynamical Systems Approach to Machine Intelligence" Prentice Hall, pp.145-152, 1991
*Kohonen, 2006+ Teuvo Kohonen, “Self-organizing neural projections” Neural Networks, Vol.19, pp.723-733, 2006.
[Jang, Sun, Mizutani, 1996] J.-S. R. Jang,C.-T. Sun,E. Mizutani, “Neuro-Fuzzy and soft computing: A Computational Approach to Learning and Machine Intelligence”
Prentice Hall, pp.301-308, 1996
*Kohonen, 1998+ Teuvo Kohonen, “The self-organizing map” Journal of Neurocompuging, Vol.21, pp.1-6, 1998.
[Rumelhart, McClelland, PDP, 1989] David E. Rumelhart, James L. McClelland ,PDP Research Group "Parallel Distributed Processing" MIT press, Vol.1,pp.444-459, 1989.
[Elman, 1990] Jeffrey L. Elman (1990). Finding structure in time. Cognitive Science, Vol.14, pp.79-211, 1990.
[Pearlmutter, 1990] Barak A. Pearlmutter (1990). Dynamic Recurrent Neural Networks. CMU-CS-88191, Carnegie Mellon University, 1990.
[Psent, Llut, 1996] D. T. Psent, X. Llut. "Training of Elman networks and dynamic system modeling" International Journal of Systents Science, Vol.27, pp.221-226, 1996.
[Park, Sandberg, 1991] Jooyoung Park, Irwin W. Sandberg "Universal approximation using radial-basis-function networks" Journal Neural Computation, Vol.3, Issue 2, pp.246-257, 1991.
‧ 國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
67
[Park, Sandberg, 1993] Jooyoung Park, Irwin W. Sandberg "Approximation and radial-basis-function networks" Journal Neural Computation, Vol.5, Issue 2, pp.305-316, 1993.
*Specht, 1990+ Donald F. Specht, “Probabilistic neural networks” Neural Networks Journal, Vol.3, pp.109-118, 1990.
*Specht, 1991+ Donald F. Specht, “A general regression neural network” Neural Networks Journal, Vol.2, pp.568-576, 1991.
*Cortes, Vapnik, 1995+ Corinna Cortes Vladimir Vapnik, “Support-Vector networks”
Machine Learning, pp.273-297, 1995.
[Yao, Tan, Poh, 1999] Jingtao Yao, Chew-Lim Tan, Hean-Lee Poh, “Neural Networks for technical Analysis: A Study on KLCI”International Journal of Theoretical and Applied Finance,Vol.2, pp.221-241, 1999.
*Tsaiha, Hsub, Laia, 1998+ Ray Tsaiha, Yenshan Hsub, Charles C. Laia, “Forecasting S&P 500 stock index futures with a hybrid AI system”Decision Support Systems, Vol.23,pp.161-174, 1998.
[Tsang, Ng, Kwan, Mak, Choy, 2007] Philip M. Tsang, Sin-Chun Ng, Reggie Kwan, Jacky Mak, Sheung-On Choy, “An empirical examination of the use of NN5 for Hong Kong stock price forecasting”Journal of Electronic Finance, Vol.1, pp.373-388, 2007.
[Tsang, Ng, Kwan, Mak, Choy, 2007] Philip M. Tsanga, Paul Kwoka, S.O. Choya, Reggie Kwanb, S.C. Nga, Jacky Maka, Jonathan Tsangc, Kai Koongd, Tak-Lam Wonge
“Design and implementation of NN5 for Hong Kong stock price forecasting”
Engineering Applications of Artificial Intelligence, Vol.20, pp.453-461, 2007.
[Jang, Lai, Jiang, Parng, Chien, 2004] Gia-Shuh Jang, Feipei Lai, Bor-Wei Jiang, Tai-Ming Parng, Li-Hua Chien, "Intelligent stock trading system with price trend prediction and reversal recognition using dual-module neural networks" Applied Intelligence, Vol. 3, pp.225-248, 2004.
‧
[Huang, Nakamori, Wang, 2005] Wei Huang, Yoshiteru Nakamori, Shou-Yang Wang,
"Forecasting stock market movement direction with support vector machine"
Computers & Operations Research, Vol.32, pp.2513-2522, 2005.
[Simila, Laine, 2005] Simila, T., & Laine, S., Visual approach to supervised variableselection by self-organizing map. International Journal of Neural Systems, 15(1-2), 101-110, 2005.
[Laine, Simila, 2004] Laine, S., & Simila, T. , Using SOM-based data binning tosupport supervised variable selection. In Pal, N. R., Kasabov, N.,Mudi, R. K., Pal, S.
& Parui, S. K. (Eds.), Neural InformationProcessing (Vol. 3316, pp. 172-180). Berlin, 2004.
[Bollinger, 2001] John A. Bollinger, "Bollinger on Bollinger Bands" McGraw-Hill, 2001.
[Mathworks] MathWorks - MATLAB and Simulink for Technical Computing
http://www.mathworks.com/help/toolbox/nnet/ug/bss36ea-1.html
[4] 中華民國經濟部(Ministry of Economic Affairs, R.O.C.)全球資訊網
http://www.moea.gov.tw/Mns/populace/home/Home.aspx
[5] 台灣證券交易所 - 公開資訊觀測站
http://newmopsov.twse.com.tw/
[6] Yahoo! Finance
http://finance.yahoo.com/
‧ 國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
69
[7] 鉅亨網 - 經濟指標預告_金融中心
http://www.cnyes.com/economy/indicator/Page/schedule.aspx
[8] MoneyCafe.com