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題名:柔性演算法在臺指選擇權之投資應用
書刊名:明新學報
作者:徐志明 引用關係徐瑞民
作者(外文):Hsu, Chih-mingHsu, Jui-min
出版日期:2013
卷期:39:2
頁次:頁157-178
主題關鍵詞:基因規劃倒傳遞類神經網路支援向量迴歸臺指選擇權Genetic programmingBackpropagation neural networkSupport vector regressionOptions
原始連結:連回原系統網址new window
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  • 共同引用共同引用:0
  • 點閱點閱:5
期刊論文
1.Ciglarič, I.、Kidrič, A.(2006)。Computer-Aided Derivation of the Optimal Mathematical Models to Study Gear-Pair Dynamic by Using Genetic Programming。Structural and Multidisciplinary Optimization,32(2),153-160。  new window
2.Koza, J. R.、Streeter, M. J.、Keane, M. A.(2008)。Routine High-Return Human-Competitive Automated Problem-Solving by Means of Genetic Programming。Information Sciences,178(73),4434-4452。  new window
3.Ben, K. I.、Weihs, C.、Limam, M.(2010)。Support vector regression control charts for multivariate nonlinear autocorrelated processes。Chemometrics and Intelligent Laboratory Systems,103(1),76-81。  new window
4.Chiang, M. H.、Huang, H. Y.(2011)。Stock market momentum, business conditions, and GARCH option pricing models。Journal of Empirical Finance,18(3),488-505。  new window
5.Kavaklioglu, K.(2011)。Modeling and prediction of Turkey's electricity consumption using support vector regression。Applied Energy,88(1),368-375。  new window
6.Li, D. C.、Liu, C. W.、Fang, Y. H.、Chen, C. C.(2010)。A yield forecast model for pilot products using support vector regression and manufacturing experience-the case of large-size polarizer。International Journal of Production Research,48(18),5481-5496。  new window
7.Liang, X.、Zhang, H. S.、Mao, J. G.、Chen, Y.(2009)。Improving option price forecasts with neural networks and support vector regressions。Neurocomputing,72(13-15),3055-3065。  new window
8.Park, H.、Lee, J.(2012)。Forecasting nonnegative option price distributions using Bayesian kernel methods。Expert Systems with Applications,39(18),13243-13252。  new window
9.Stentoft, L.(2011)。American option pricing with discrete and continuous time models: an empirical comparison。Journal of Empirical Finance,18(5),880-902。  new window
10.Tseng, C. H.、Cheng, S. T.、Wang, Y. H.、Peng, J. T.(2008)。Artificial neural network model of the hybrid EGARCH volatility of the Taiwan stock index option prices。Physica A; Statistical Mechanics and its Applications,387(13),3192-3200。  new window
11.Wang, Y. H.(2009)。Using neural network to forecast stock index option price: a new hybrid GARCH approach。Quality Quantity,43(5),833-843。  new window
12.Wang, C. P.、Lin, S. H.、Huang, H. H.、Wu, P. C.(2012)。Using neural network for forecasting TXO price under different volatility models。Expert Systems with Applications,39(5),5025-5032。  new window
13.Yang, C. C.、Shieh, M. D.(2010)。A support vector regression based prediction model of affective responses for product form design。Computers & Industrial Engineering,59(4),682-689。  new window
14.Zhang, H. Y.(2012)。Research on factors influencing European option price by using hybrid neural network。Advances in Intelligent and Soft Computing,144(10),247-252。  new window
15.Zapart, Christopher A.(2003)。Beyond Black-Scholes; a neural networks-based approach to options pricing。International Journal of Theoretical and Applied Finance,6(5),469-489。  new window
16.Meissner, Gunter、Kawano, Noriko(2001)。Capturing the Volatility Smile of Options on High-tech Stocks: A Combined GARCH-neural Network Approach。Journal of Economics and Finance,25(3),276-292。  new window
17.Cortes, Corinna、Vapnik, Vladimir N.(1995)。Support-Vector Networks。Machine Learning,20(3),273-297。  new window
圖書
1.Koza, J. R.、Keane, M. A.、Streeter, M. J.、Mydlowec, W.、Yu, J.、Lanza, G.(2005)。Genetic Programming IV: Routine Human-Competitive Machine Intelligence。New York:Springer。  new window
2.Kumar, S.(2004)。Neural Networks: A Classroom Approach。New Delhi:Tata McGraw-Hill。  new window
3.Koza, John R.(1992)。Genetic Programming: On the Programming of Computer by Natural Selection。Cambridge, Mass.:MIT Press。  new window
4.Fausett, L. V.(1994)。Fundamentals of Neural Networks: Architecture, Algorithms, and Applications。Englewood Cliffs, New Jersey:Prentice-Hail。  new window
5.Vapnik, V. N.(1995)。The Nature of Statistical Learning Theory。Springer-Verlag。  new window
6.Vapnik, Vladimir N.(1998)。Statistical Learning Theory。John Wiley and Sons, Inc.。  new window
7.Holland, J. H.(1975)。Adaptation in Natural and Artificial Systems: An Introductory Analysis with Application to Biology, Control, and Artificial Intelligence。MI:University of Michigan Press。  new window
其他
1.Hsu, C.-W.,Chang, C.-C.,Lin, C.-J.(2003)。A practical guide to support vector classification,Taipei。,http://www.csie.ntu.edu.tw/~cjlin/papers/guide/guide.pdf。  new window
圖書論文
1.Drucker, Harris、Burges, Christopher J. C.、Kaufman, Linda、Smola, Alex J.、Vapnik, Vladimir N.(1997)。Support vector regression machines。Advances in Neural Information Processing Systems。Cambridge, Massachusetts:MIT Press。  new window
2.Vapnik, V. N.、Golowich, S.、Smola, A.(1997)。Support Vector Method for Function Approximation, Regression Estimation, and Signal Processing。Neural Information Processing Systems。Cambridge, MA:MIT Press。  new window
 
 
 
 
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