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博碩士論文 etd-0701109-182706 詳細資訊
Title page for etd-0701109-182706
論文名稱
Title
從隨機共整合角度檢驗股利評價模型—以臺灣股市為例
Re-examining the Dividend Valuation Model by Stochastic Cointegration — the Evidence from Taiwan Stock Market
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
72
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2009-06-25
繳交日期
Date of Submission
2009-07-01
關鍵字
Keywords
股利評價模型、台灣股票市場、異質自積、單根檢定、共整合、隨機共整合
Dividend Valuation Model, Taiwan Stock Market, Cointegration, Unit Root Tests, Heteroskedastically Integrated, Stochastic Cointegration
統計
Statistics
本論文已被瀏覽 5827 次,被下載 3808
The thesis/dissertation has been browsed 5827 times, has been downloaded 3808 times.
中文摘要
股利評價模型是一個廣為人知的股票定價模型, 但是國外卻有許多研究股市的實證文獻並不支持股利評價模型, 這些研究多半皆認為股價太過波動而無法經由預期股利來解釋。因此, 本文想經由隨機共整合這樣一個寬鬆的共整合設定來重新檢驗台灣的股市, 觀察台灣股市是否支持股利評價模型。實證結果發現塑膠業、鋼鐵業、資訊電子業與金融保險業均支持股價與股利有正向的連動關係, 但實證結果不全然支持共整合向量的理論值。因此, 本研究最終並沒有得到足夠的證據支持台灣股市是有效率的。
Abstract
Dividend Valuation Model is a well-known stock pricing model. However, many empirical studies of foreign stock markets do not support the Dividend Valuation Model; most of these studies think stock price is too volatile to explain by expected dividend. Therefore, this article would like to use Stochastic Cointegration to reexamining Taiwan stock market, and observe whether Taiwan stock market supports
Dividend Valuation Model. The empirical results showed that stock price and dividends exist a positive comovements relationship in the plastic, steel, electronic, and the banking & insurance industries, but empirical results does not completely support the theoretical value of cointegration vector. Therefore, this study has not been sufficient evidence to support Taiwan stock market is efficient.
目次 Table of Contents
1 緒論 1
1.1 研究動機與目的. . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 本文架構. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2 理論模型與文獻回顧 4
2.1 股利折現模型. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.2 國外文獻回顧. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.3 國內文獻回顧. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
3 研究方法 13
3.1 單根檢定. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
3.1.1 Dickey-Fuller 單根檢定(DF 檢定) . . . . . . . . . . . . . 15
3.1.2 Augmented Dickey-Fuller 單根檢定(ADF 檢定) . . . . . 16
3.1.3 Phillips-Perron 單根檢定(PP 檢定) . . . . . . . . . . . . 19
3.1.4 KPSS 單根檢定. . . . . . . . . . . . . . . . . . . . . . . 21
3.1.5 ERS Point-Optimal 單根檢定. . . . . . . . . . . . . . . 22
3.1.6 Ng-Perron 單根檢定(NP 檢定) . . . . . . . . . . . . . . 23
3.2 傳統共整合檢定. . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
3.2.1 Engle & Granger 兩階段估計法. . . . . . . . . . . . . . 26
3.2.2 Johansen 最大概似法檢定. . . . . . . . . . . . . . . . . 27
3.3 隨機共整合檢定. . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3.3.1 模型設定(Models) . . . . . . . . . . . . . . . . . . . . . 33
3.3.2 迴歸(Regression) . . . . . . . . . . . . . . . . . . . . . 36
3.3.3 假設檢定及檢定統計量. . . . . . . . . . . . . . . . . . . 38
4 實證結果與分析 42
4.1 資料說明. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
4.1.1 資料來源. . . . . . . . . . . . . . . . . . . . . . . . . . 42
4.1.2 資料處理. . . . . . . . . . . . . . . . . . . . . . . . . . 42
4.1.3 樣本選取. . . . . . . . . . . . . . . . . . . . . . . . . . 44
4.1.4 資料期間. . . . . . . . . . . . . . . . . . . . . . . . . . 45
4.2 敘述統計量. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
4.3 單根檢定. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
4.4 Johansen 共整合檢定. . . . . . . . . . . . . . . . . . . . . . . . . 49
4.5 隨機共整合檢定. . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
5 結論 54
附錄A 56
參考文獻 58
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