系統識別號 U0026-0812200915152618
論文名稱(中文) 非線性模型應用於Nasdaq 電信指數之研究
論文名稱(英文) An Investigation of The Trend of Nasdaq Telecommunication Index: Application of Nonlinear Model
校院名稱 成功大學
系所名稱(中) 電信管理研究所
系所名稱(英) Institute of Telecommunications and Management
學年度 97
學期 2
出版年 98
研究生(中文) 林勇智
研究生(英文) Yung-Chih Lin
學號 r9694102
學位類別 碩士
語文別 英文
論文頁數 46頁
口試委員 指導教授-張瀞之
中文關鍵字 Hodrick-Prescot Filter  非線性模型  納斯達克電信指數  X-12-ARIMA 
英文關鍵字 Nasdaq Telecomminications Index  Hodrick-Prescot Filter  Non-linear model  X-12-ARIMA 
中文摘要 過去許多學者的研究發現電信產業的發展與投資對總體經濟成長有正面的影響並且可視為的一項重要驅動因素,而股價或指數可以反映一產業為的發展及獲利情形。因此回顧過去,電信業在經歷民營化開放的繁榮、網路泡沫化的崩跌,以及現今面對新技術發展及營運模式的不確定性都可以由代表美國電信的納斯達克電信指數(Nasdaq Telecommunications Index, IXUT)漲跌得知。亦因為電信產業與總體經濟活動的關係緊密,因此本研究將考量總體經濟指標,建立納斯達克電信指數預測迴規模型。
本研究採用的總體經濟指標有消費者物價指數(Consumer price index),消費者信心指數Consumer confidence index),匯率(Exchange rate),30年美國公債殖利率(30-year T-bond yield),工業生產指數(Industrial production index),貨幣供給量(Money quantity)。研究期間為2002年6月至2008年9月,共76筆月資料。
資料處理上先利用X-12-ARIMA及頻譜分析法中的HP濾波法(Hodrick-Prescot Filter)得到循環性資料,以利了解自變數對應變數的關係。接著利用所有可能迴歸法(All Possible Regression)並經由Cp、AIC、MSE及SBC等法則選出對納斯達克電信指數的顯著變數。經實證後發現,消費者物價指數對納斯達克電信指數的解釋力最高並利用其建立非線性預測模式。模型經平均絕對誤差率(Mean absolute percentage error, MAPE)檢測後值為12.04%,顯示具有良好的預測能力。
英文摘要 The telecommunications industry has played an essential role and impacted on macro activities. Based on previous research, it is the engine which could stimulate and carry the economic growth forward. Stock prices usually reflects the current conditions, future profits and perspective for an industry. As a result, the history of the telecommunications is also evidenced by the U.S. Nasdaq Telecommunications Index (IXUT), including the prosperity caused by privatization acts, internet bubble collapse, and the uncertainty of 3G business model and new technologies. Due to the importance of the development of telecommunications industry and the closer linkage with other industries, this research would develop a predictive model of IXUT according to macroeconomic indicators.
In this research, consumer price index, consumer confidence index, exchange rate (USD/CAD), 30-year T-bond yield, industrial production index, money quantity (M2) is considered from 2002.06-2008.09, a total 76 observations, respectively. The cyclical data is gained to make a clear picture of raw data after the seasonal adjustment and Hodrick-Prescot Filter. Then, consumer price index is chosen to build a nonlinear forecasting model subsequent to the all possible regression and variables selection. The predictive model performs well by means of MAPE.
The result could provide managerial or investment information to stakeholders including U.S. governments, bankers, investors and hedgers.
論文目次 Content
摘要 I
謝 誌 III
Content IV
Tables List V
Figures List VI
Chapter 1 Introduction 1
1.1 Background 1
1.2 Motivation 3
1.3 Objectives 4
1.4 Structure of This Research 5
1.5 Research Flow Path 5
Chapter 2 Literature Review 6
2.1 Macroeconomic Variables 6
2.2 Seasonality and X-12- ARIMA Decomposition Method 10
2.3 Detrending Method-Hodrick-Prescot Filter 13
2.4 Mean Absolute Percentage Error (MAPE) 14
2.5 Summary 17
Chapter 3 Methodology 18
3.1 Data Collection 18
3.2 Seasonal Adjustment and X-12 ARIMA 19
3.3 Hodrick-Prescott Filter 21
3.4 Variables Selection Criteria 22
3.5 A Novel Nonlinear Prediction Model 24
3.6 Mean Absolute Percentage Error (MAPE) 27
Chapter 4 Empirical Analysis 29
4.1 Data Description 29
4.2 Seasonal Adjustment and De-trending Data 30
4.3 Multiple Regression and Variable Selection 33
4.4 Regression Model Development 36
4.5 Discussions 38
4.6 Summary 40
Chapter 5 Conclusion and Futurework 41
5.1 Conclusion 41
5.2 Research Limitation and Future Work 42
Reference 43
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