政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/87282
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 11 |  Items with full text/Total items : 89327/119107 (75%)
Visitors : 23836363      Online Users : 184
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/87282

    Title: BPN暨RN神經網路與向量誤差修正模型對國內債券價格之預測績效
    Exploring the Relative Abilities of Neural Networks and VECM in Forecasting Taiwan's Bond Price
    Authors: 紀如龍
    Jih, Ru-Long
    Contributors: 林修葳

    Lin, Hsiou-Wei
    Tsaih, Rru--Huan

    Jih, Ru-Long
    Keywords: 公債
    Government bond
    Yield to maturity
    Neural network
    Date: 1996
    Issue Date: 2016-04-28 11:34:08 (UTC+8)
    Abstract: 本研究計畫探討以RN神經網路模型預測國內債券價格的效度。目前一般用於財務預測的神經網路論著主要為BPN模型,惟BPN模型有其限制,所以本研究計畫將(1)分析比較統計計量模型,BPN神經網路,RN神經網路系統對國內公債價格之預測績效。(2)分析不同時期的預測能力,找出景氣和預測變數的關係,同時將比較各個時期統計計量模型和神經網路模型是否同時有效, 抑或有些有效, 有些無效,以探討各工具是否具有互補性或替代性。並探討預測績效是否受到背後經濟環境的影響。
    This research project empirically investigates the accuracy of Reasoning Neural Networks (RN) in forecasting Taiwan's bond prices. We explore (1) the relative predictive abilities of Vector Error Correction Model (VECM), which serve as a representative econometric model, Back Propagation Neural Networks (BPN), which is adopted by most current studies in the application of neural networks in finance, and RN, and (2) th3 potential variations in the three models' predictive power in different phases of economic cycle. Specifically, we aim to study if the three models substitute or complementone another. In addition, we explore the extent to which the relativepredictive abilities of the three models varies with underlying macroecomonic factors. The explanatory variables adopted in this study include all potential drives to (real) risk-free rate, expected inflation rate, and riskspremiums.
    Reference: "(一)中文部份
    2、婁天威(1993),我國債券市場結構分析與問題探討,臺灣銀行季刊第四十六志第一期,pp.151-202 。
    7、葉怡成 (1993),類神經網路模式應用與實作,儒林圖書公司,1月出版。
    8、蔡瑞煌(1994),The Softening Learning Procedure for The Networks with Multiple Output Nodes,資管評論,第四期,pp.89-93。
    10、蔣廷方,(1994),類神經網路股價預測系統,企銀季刊,4月,pp .40-49。

    1、Baneljee,A. ; Dolado,J. J. ; Galbraith,J.W. ; Hendry,D. F.,(1993),Cointeration,Error Correction and the Econometric Analysis of Nonstationry Data,Published by Oxford University Press Inc.
    2、Bergerson,K. ; Wunsch,D.C.,(1991),A Commodity Trading Model Based on a Neural Networks-Expert System Hybird,Proceedings of the International Joint Conference on Neural Network 1991,pp.289-293.
    3、Elton,E. J. ; Gruber,M. J. ; Bl8ke,C. R.,(1995),Fundamental Economic Variables,Expected Returns,and Bond Fund Performance,Journal of Finance,Sep,pp.1229-1256.
    4、Engle,R. F. ; Granger,C. W. J.,(1987),Co-intergration and Error Correction : Representation,Estimation and Testing,Econometrica,Vo1.55,pp.251-276.
    5,Engle,R. F. ; Yoo,B. S.,(1987),Forecasting and Testing in Cointegrated Systems,Journal of Econometrics,Vo1.35,May,pp.143-159.
    6,Gmdnitski,G. ; Osburn,L.,(1993),Forecasting S &P500 and Gold Futures Prices: An Application of Neural Networks,Journal of Futures Markets,Vol. 13,NO.6,pp.631-643.
    7,Harvey,A. C.,(1990)The Econometric Analysis of Time Series,Second Edition,Published by Philip Allan.
    8,Jeffrey,E. S. ; Venkatachalam,A. R.,(1995),A Neural Network Approach to Forecasting Model Selection,Information & Management,Vo1.29,Dec,pp.297-303.
    9,Johansen,S. ; Juselius,K.,(1990),Maximun Likelihood Estimation and Inference on Cointegration-With Applications to the Demand for Money,Oxford Bulletin of Economics & Statistics,Vo1.52,May,pp.169-210.
    10,Judge,G. G. ; Hill,R. C. ; Griffiths,W. E. ; Lutkepohl,H. ; Lee,T. C.,(1988)Introduction to The Theoy and Practice of Econometrics,Second Edition,Published by John Wiley & Sons,Inc.
    11,Kimoto,T. ; Asakawa,K.,(1990),Stock Market Prediction System with Modular Network,IJCNN-90-Wash,Vol. 1,pp.1-6.
    12,Krugman,P. R. ; Obstfeld,M.,(1994)International Economics:Theoy and Policy, Third Edition,Published by R.R. Donnelley & Sons Company.
    13,Kryzanowski,L. ; Galler,M. ; Wright,D.W.,(1993),Using Artificial Neural Networks to Pick Stocks,Financial Analysis Journal,Jul-Aug.
    14,Lapedes,A. ; Farber,R.,(1987),Nonelinear Signal Processing using Neural Networks:Prediction and System Modeling,Los Alamos National Laboratory Report,LA-UR-87-2662.
    15,Lee,T. ; White,H.,(1993),Testing for Neglected Nonlinearity in Time Series 1vfodels,Journal of Econometrics,April,pp.269-290.
    16,Michael,G. B. ; Stephen,A. L.,(1992),The Treasury Yield Curve as a Cointegrated System,Journal of Financial and Quantitative Analysis,Vol.27,NO.3,Sep,449-464.
    17,Phillips,P. C. B. ; Perron,P.,(1988),Testing for a Unit Root in Time Series Regression,Biometrica,Vo1.75,pp.335-346.
    18,Rumelhatt,D. E. ; McClelland,1. L.,(1986),Parallel Distributed Processing,Vol. 1,Published by The Massachusetts Institute of Technology.
    19,Schoneburg,E.,(1990),Stock Price Prediction using Neural Networks:A Project Report,Neuralcomputing 2,pp.17-27.
    20,Swanson N. ; White H.,(1995),A Model-Selection Approach to Assessing the Information in the Term Structure Using Linear Models and Artificial Neural Networks,Joul11al of Business and Economic Statistics,July,pp.265-275.
    21,Tsaih,R.,(1995),The Reasoning Neural Network,Annals of Mathematics and Artificial Intelligence,accepted.
    22,Tsaih,R.,(1993),The Softening Learning Procedure,Mathematical and Computer Modelling,Vol.18,No.8,pp.61-64."
    Description: 碩士
    Source URI: http://thesis.lib.nccu.edu.tw/record/#B2002002748
    Data Type: thesis
    Appears in Collections:[Department of International Business ] Theses

    Files in This Item:

    File SizeFormat

    All items in 政大典藏 are protected by copyright, with all rights reserved.

    社群 sharing

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback