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https://ah.lib.nccu.edu.tw/handle/140.119/37087
題名: | 多變量模糊時間數列在財務上的應用 An Application of Multivariate Fuzzy Time Series on Financial Markets. |
作者: | 呂冠宏 | 貢獻者: | 吳柏林 呂冠宏 |
關鍵詞: | 模糊時間數列 模糊關係矩陣 預測 |
日期: | 2007 | 上傳時間: | 19-Sep-2009 | 摘要: | 股票是許多人採取投資的項目。若能準確預測股價的漲跌,則可以有效地降低投資風險,賺取利潤。然而,有許多因素會影響股票走勢,例如政治因素,匯率變化,天災人禍。因此,股票走勢很難被精確預測。我們嘗試用模糊統計來解決股價預測的問題。本論文藉由模糊相關矩陣來建立多變量模糊時間數列,以便用來預測股票趨勢。實證研究則以台灣加權股價指數為對象,對每日的收盤價進行模糊時間數列分析與預測,還計算誤差與準確率。實證研究顯示,能降低投資者的風險。 | 參考文獻: | 中文部份 [1] 吳柏林;林玉鈞, (2002), \"模糊時間數列分析與預測:以台灣地區加權股價指數 為例,\" 中國統計學報, Vol.25, No.1, pp.67-76. [2] 吳柏林 (2005), 模糊統計導論, 方法與應用. 台北:五南書局 [3] 吳柏林 (1995), 時間序列分析導論. 台北:華泰書局 [4] 陳蒼山 (2006),模糊時間數列分析與預測—以石油價格為例(碩士論文) 英文部分 [5] Dug Hun Hong (2005), A note on fuzzy time-series model. Fuzzy Sets and Systems, 155, 309-316. [6] Diebold F. X. and Lindner P. (1996), Fractional integration and interval prediction. Economics Letters, 50, 305-313. [7] Li, H., Miao, Z., Han, S. and Wang, J. (2005), A new kind of fuzzy relation equations based on inner transformation. Computers and Mathematics with Applications, 50, 623-636. [8] Huarng, K. (2001), Effective lengths of intervals to improve forecasting in fuzzy time series. Fuzzy Sets and Systems, 123, 387-394. [9] Huarng, K. (2001), Heuristic models of fuzzy time series for forecasting. Fuzzy Sets and Systems, 123, 369-386. [10] Huarng, K. and Yu T. H. (2006), The application of neural networks to forecast fuzzy time series. Physica A, 363, 481-491. [11] Koutroumanidis T., Iliadis L. and Sylaios G. K. (2006), Time-series modeling of fishery landings using ARIMA models and fuzzy expected intervals software. Environmental Modeling & Software, 21, 1711-1721. [12] Ramsés H. Mena and Sephen G. Walker (2005), Stationary autoregressive models via a Bayesian nonparametric approach. Journal of Time Series Analysis, 26, 789-805. [13] Rob J. H, Anne B.K, J. Keith Ord and Ralph D. S (2005), Prediction intervals for exponential smoothing using two new classes of state space models. Journal of Forecasting, 24, 17-37. [14] Song, Q. and Chissom, B.S. (1993a), Forecasting enrollments with fuzzy time series – part I. Fuzzy Sets and Systems, 54, 1-9. [15] Song, Q. and Chissom, B.S. (1993b), Fuzzy time series and its models. Fuzzy Sets and Systems, 54, 269-277. [16] Song, Q. and Chissom, B.S. (1994), Forecasting enrollments with fuzzy time series – part II. Fuzzy Sets and Systems, 62, 1-8. [17] Song, Q., Leland, R. P. and Chissom, B. S. (1995), A new fuzzy time-series model of fuzzy number observations. Fuzzy Sets and Systems, 73, 341-348. [18] Song, Q., Leland, R. P. and Chissom, B. S. (1997), Fuzzy stochastic fuzzy time series and its models. Fuzzy Sets and Systems, 62, 1-8. [19] Chen, S. (1996), Forecasting enrollments based on fuzzy time series. Fuzzy Sets and Systems, 81, 311-319. [20] Wu, B. and Chen, M. (1999), Use of fuzzy statistical technique in change periods detection of nonlinear time series. Applied Mathematics and Computation, 99, 241-254. [21] Zimmermann, H.J. (1991), Fuzzy Set Theory and Its Applications. Boston:Kluwer Academi. |
描述: | 碩士 國立政治大學 應用數學研究所 93751009 96 |
資料來源: | http://thesis.lib.nccu.edu.tw/record/#G0093751009 | 資料類型: | thesis |
Appears in Collections: | 學位論文 |
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