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題名 應用類神經網路於預測國外股價指數期約
Forecasting Foreign Stock Index Futures: An Application of Neural Networks
作者 賴俊霖
Lai, Charles C.
貢獻者 蔡瑞煌<br>徐燕山
Ray, Tsaih<br>Hsu, Yenshan
賴俊霖
Lai, Charles C.
關鍵詞 理解神經網路
S&P 500 指數期貨
類神經網路
股價指數期貨
Reasoning neural networks
S&P 500 index futures
Artificial neural networks
Stock index futures
日期 1996
上傳時間 28-四月-2016 11:55:06 (UTC+8)
摘要 本研究嘗試整合類神經網路與法則基礎（rule-based）系統技術，以建立S&P 500指數期貨的交易策略。本研究不同於先前研究之處有下列二方面：一、本研究採用法則基礎系統的方式提供神經網路的訓練範例；二、本研究以理解神經網路（Reasoning Neural Networks）取代後向傳導網路（Back propagation networks）以解決局部最小值與隱藏結點數未知的困境，而實證結果也顯示理解神經網路之表現優於後向傳導網路。首先，由期貨的日價格資料計算出十種技術分析指標值，用這些指標值來表示期貨市場內的各種可能狀況（case）。接著，我們提出FFM（Futures Forecast Model）與EFFM（Extended Futures Forecast Model）來處理市場的各種狀況，預測出隔日的期貨價格改變方向。以法則基礎方法所建立的FFM是用來處理明顯的狀況（obvious cases），並且提供類神經網路好的訓練範例。而EFFM包括四個理解神經網路系統與一個決策機置（voting mechanism），它被用來處理那些不明顯的狀況（non-obvious
This research adopts a hybrid approach to implementing the
參考文獻 Bergerson, Karl and Donald C. Wunsch (1991), "A Commodity Trading Model Based on a Neural Network - Expert System Hybrid," Proceedings of the IEEE International Conference on Neural Networks, pp. 1289-1293.
     Blank, S. C. (1991), "Chaos` in Futures Market? A Nonlinear Dynamical Analysis," Journal of Futures Markets, Vol. 11:711-728.
     Bosarge, W. E. (1991), "Adaptive Processes to Exploit the Nonlinear Structure of Financial Markets," The Santa Fe Institute of Complexity Conference: Neural Networks and Pattern Recognition in Forecasting Financial Markets, February 15.
     Bryson, AE. and y-c. Ho (1969), Applied Optimal Control, New York: Blaisdell.
     Chande, Tushar S. and Stanley Kroll (1994), The New Technical Trader, New York: John Wiley and Sons, Inc.
     DeCoster, G, P., Labys, W.C., and Mitchell, D. W. (1992), ``Evidence of Chaos in Commodity Futures Prices," Journal of Futures A1al`kets, Vol. 12:291-305.
     Frank, M, and Stengos, T. (1989), "Measuring the Strangeness of Gold and Silver Rates of Return," Review of Economic Studies, Vol. 56:553-567.
     Freeman, James A and David M, Skapura (1992), Neural Networks Algorithms. Applications, and Programming Techniques, Addison-Wesley, Reading MA
     Grudnitski, Gary and Larry Osburn (1993), "Forecasting S&P and Gold Futures Prices:An Application of Neural Networks," Journal of Futures Markets, Vol. 13, No. 6,631-643 .
     Herbst, Anthony F. (1992), Analyzing and Forecasting Futures Prices, New York: John Wiley and Sons, Inc.
     Herbst, Anthony F. and C. W. Slinkman (1984), "Does the Evidence Support the Existence of `Political Economic` Cycles in the U.S. Stock Market?", Financial Analyst Journal, Vol. 40, No.2, March.
     Hutchinson, James M., Andrew W. Lo, and Tomaso Poggio (1994), "A N onparametric Approach to Pricing and Hedging Derivative Securities via Learning Networks,"Journal of Finance, Vol. 49, No.3, 851-889.
     Kee, Wong Yue and Annie Koh (1994), "Technical Analysis of Nikkei 225 Stock Index Futures Using an Expert System Advisor," Proceedings of the CBOT Conference.Minsky, M.L. and S.A. Papert (1969), Perceptrons, Cambridge: MIT Press.
     Parker, D.D. (1985), "Learning Logic," Technical Report TR-47, Center for Computational Research in Economics and Management Science, Massachusetts Institute of Technology, Cambridge, MA.
     Rosenblatt, F. (1958), "The Perceptron: A Probabilistic Model for Information Storage and Organization in the Brain." Psychological Review, Vol. 65, pp.3 86-408.
     Rosenblatt, F. (1962), Principles ofneurodynamics, New York: Spartan Books.
     Rumelhart, D. E., Hinton, G. E., and Williams, R. J. (1986), "Learning internal representations by error propagation," Parallel Distributed Processing, Vol. 1, pp.318-62, Cambrideg, MA: MIT Press.
     Smith, Murray (1993), Neural Networks for Statistical Modeling, New York: Van Nostrand Reinhold.
     Trippi, Robert R. and Duane DeSieno (1992), "Trading Equity Index Futures wjth a Neural Network," Journal of Portfolio Management, Fall 1992, pp. 27-33.
     Trippi, Robert R., and Turban, E. (1993), Neural Networks ill Finance and Investing, Chicago: Probus Publishing.
     Turban, E. (1990), Decision Support and Expert Systems, New York: Macmillan Publishing Company.
     Tsaih, R. (1993), "The Softening Learning Procedure," Mathematical and Computer Modebng, Vol. 18, No.8, pp. 61-64.
     Tsaih, R. (1995), "The Reasoning Neural Networks," Annals of Mathematics and Artificial Intelligence, forthcoming.
     Tsaih, R. (1996), ``Learning Procedure that Guarantees Obtaining the Desired Solution Of the 2-Classes Categorization Learning Problem," class-note.
     Werbos, P.J. (1974), "Beyond Regression: New Tools for Prediction and Analysis in the Behavioral Sciences," Ph.D. Thesis, Harvard University, Cambridge, MA.
描述 碩士
國立政治大學
資訊管理學系
83356022
資料來源 http://thesis.lib.nccu.edu.tw/record/#B2002002862
資料類型 thesis
dc.contributor.advisor 蔡瑞煌<br>徐燕山zh_TW
dc.contributor.advisor Ray, Tsaih<br>Hsu, Yenshanen_US
dc.contributor.author (作者) 賴俊霖zh_TW
dc.contributor.author (作者) Lai, Charles C.en_US
dc.creator (作者) 賴俊霖zh_TW
dc.creator (作者) Lai, Charles C.en_US
dc.date (日期) 1996en_US
dc.date.accessioned 28-四月-2016 11:55:06 (UTC+8)-
dc.date.available 28-四月-2016 11:55:06 (UTC+8)-
dc.date.issued (上傳時間) 28-四月-2016 11:55:06 (UTC+8)-
dc.identifier (其他 識別碼) B2002002862en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/87346-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊管理學系zh_TW
dc.description (描述) 83356022zh_TW
dc.description.abstract (摘要) 本研究嘗試整合類神經網路與法則基礎（rule-based）系統技術，以建立S&P 500指數期貨的交易策略。本研究不同於先前研究之處有下列二方面：一、本研究採用法則基礎系統的方式提供神經網路的訓練範例；二、本研究以理解神經網路（Reasoning Neural Networks）取代後向傳導網路（Back propagation networks）以解決局部最小值與隱藏結點數未知的困境，而實證結果也顯示理解神經網路之表現優於後向傳導網路。首先，由期貨的日價格資料計算出十種技術分析指標值，用這些指標值來表示期貨市場內的各種可能狀況（case）。接著，我們提出FFM（Futures Forecast Model）與EFFM（Extended Futures Forecast Model）來處理市場的各種狀況，預測出隔日的期貨價格改變方向。以法則基礎方法所建立的FFM是用來處理明顯的狀況（obvious cases），並且提供類神經網路好的訓練範例。而EFFM包括四個理解神經網路系統與一個決策機置（voting mechanism），它被用來處理那些不明顯的狀況（non-obviouszh_TW
dc.description.abstract (摘要) This research adopts a hybrid approach to implementing theen_US
dc.description.tableofcontents 1 Introduction
     1.1 Problem Statement..........1
     1.2 Related Researches..........2
     1.3 Proposed Approach..........2
     1.4 Dissertation Organization..........3
     2 Background Review
     2.1 The Basics of Futures Markets..........4
     2.2 The Basics of Neural Networks..........7
     2.3 Integration of Neural Networks and Rule-based Systems..........20
     3 The Design and the Evaluation
     3.1 Overview of the Hybrid System..........22
     3.2 Processing Futures Date..........22
     3.3 Futures Forecast Model(FFM)..........24
     3.4 Extended Futures Forecast Model(EFFM)..........32
     4 Futures Trading Simulation
     4.1 Integrated Futures Trading System(IFTS)..........39
     4.2 Trading Performance Evaluation..........41
     4.3Applying IFTS to Nikkei 225 Index Futures..........45
     5 Conclusions
     5.1 Summary and Discussions..........47
     5.2 Future Work..........49
     Bibliography..........51		zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#B2002002862en_US
dc.subject (關鍵詞) 理解神經網路zh_TW
dc.subject (關鍵詞) S&P 500 指數期貨zh_TW
dc.subject (關鍵詞) 類神經網路zh_TW
dc.subject (關鍵詞) 股價指數期貨zh_TW
dc.subject (關鍵詞) Reasoning neural networksen_US
dc.subject (關鍵詞) S&P 500 index futuresen_US
dc.subject (關鍵詞) Artificial neural networksen_US
dc.subject (關鍵詞) Stock index futuresen_US
dc.title (題名) 應用類神經網路於預測國外股價指數期約zh_TW
dc.title (題名) Forecasting Foreign Stock Index Futures: An Application of Neural Networksen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Bergerson, Karl and Donald C. Wunsch (1991), "A Commodity Trading Model Based on a Neural Network - Expert System Hybrid," Proceedings of the IEEE International Conference on Neural Networks, pp. 1289-1293.
     Blank, S. C. (1991), "Chaos` in Futures Market? A Nonlinear Dynamical Analysis," Journal of Futures Markets, Vol. 11:711-728.
     Bosarge, W. E. (1991), "Adaptive Processes to Exploit the Nonlinear Structure of Financial Markets," The Santa Fe Institute of Complexity Conference: Neural Networks and Pattern Recognition in Forecasting Financial Markets, February 15.
     Bryson, AE. and y-c. Ho (1969), Applied Optimal Control, New York: Blaisdell.
     Chande, Tushar S. and Stanley Kroll (1994), The New Technical Trader, New York: John Wiley and Sons, Inc.
     DeCoster, G, P., Labys, W.C., and Mitchell, D. W. (1992), ``Evidence of Chaos in Commodity Futures Prices," Journal of Futures A1al`kets, Vol. 12:291-305.
     Frank, M, and Stengos, T. (1989), "Measuring the Strangeness of Gold and Silver Rates of Return," Review of Economic Studies, Vol. 56:553-567.
     Freeman, James A and David M, Skapura (1992), Neural Networks Algorithms. Applications, and Programming Techniques, Addison-Wesley, Reading MA
     Grudnitski, Gary and Larry Osburn (1993), "Forecasting S&P and Gold Futures Prices:An Application of Neural Networks," Journal of Futures Markets, Vol. 13, No. 6,631-643 .
     Herbst, Anthony F. (1992), Analyzing and Forecasting Futures Prices, New York: John Wiley and Sons, Inc.
     Herbst, Anthony F. and C. W. Slinkman (1984), "Does the Evidence Support the Existence of `Political Economic` Cycles in the U.S. Stock Market?", Financial Analyst Journal, Vol. 40, No.2, March.
     Hutchinson, James M., Andrew W. Lo, and Tomaso Poggio (1994), "A N onparametric Approach to Pricing and Hedging Derivative Securities via Learning Networks,"Journal of Finance, Vol. 49, No.3, 851-889.
     Kee, Wong Yue and Annie Koh (1994), "Technical Analysis of Nikkei 225 Stock Index Futures Using an Expert System Advisor," Proceedings of the CBOT Conference.Minsky, M.L. and S.A. Papert (1969), Perceptrons, Cambridge: MIT Press.
     Parker, D.D. (1985), "Learning Logic," Technical Report TR-47, Center for Computational Research in Economics and Management Science, Massachusetts Institute of Technology, Cambridge, MA.
     Rosenblatt, F. (1958), "The Perceptron: A Probabilistic Model for Information Storage and Organization in the Brain." Psychological Review, Vol. 65, pp.3 86-408.
     Rosenblatt, F. (1962), Principles ofneurodynamics, New York: Spartan Books.
     Rumelhart, D. E., Hinton, G. E., and Williams, R. J. (1986), "Learning internal representations by error propagation," Parallel Distributed Processing, Vol. 1, pp.318-62, Cambrideg, MA: MIT Press.
     Smith, Murray (1993), Neural Networks for Statistical Modeling, New York: Van Nostrand Reinhold.
     Trippi, Robert R. and Duane DeSieno (1992), "Trading Equity Index Futures wjth a Neural Network," Journal of Portfolio Management, Fall 1992, pp. 27-33.
     Trippi, Robert R., and Turban, E. (1993), Neural Networks ill Finance and Investing, Chicago: Probus Publishing.
     Turban, E. (1990), Decision Support and Expert Systems, New York: Macmillan Publishing Company.
     Tsaih, R. (1993), "The Softening Learning Procedure," Mathematical and Computer Modebng, Vol. 18, No.8, pp. 61-64.
     Tsaih, R. (1995), "The Reasoning Neural Networks," Annals of Mathematics and Artificial Intelligence, forthcoming.
     Tsaih, R. (1996), ``Learning Procedure that Guarantees Obtaining the Desired Solution Of the 2-Classes Categorization Learning Problem," class-note.
     Werbos, P.J. (1974), "Beyond Regression: New Tools for Prediction and Analysis in the Behavioral Sciences," Ph.D. Thesis, Harvard University, Cambridge, MA.		zh_TW