| 研究生: |
廖士仁 Liao, Shih-Jen |
|---|---|
| 論文名稱: |
資本資產定價模型與三因子模型之分析與比較 Some Aspects about the Capital Asset Pricing Model and Three-factor Model |
| 指導教授: |
鄭宗記
Cheng, Tsung-Chi |
| 學位類別: |
碩士
Master |
| 系所名稱: |
商學院 - 統計學系 Department of Statistics |
| 論文出版年: | 2005 |
| 畢業學年度: | 93 |
| 語文別: | 英文 |
| 論文頁數: | 52 |
| 中文關鍵詞: | 資本資產定價模型 、三因子模型 、線性混合效應模型 、時間序列迴歸 、橫斷面迴歸 |
| 外文關鍵詞: | Capital Asset Pricing Model, Three-factor Model, linear mixed-effects model, time-series regression, cross-sectional regression |
| 相關次數: | 點閱:513 下載:0 |
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資本資產定價模型已被廣泛使用於分析股票風險與要求報酬率之間的關係。然而,個別股票風險Beta是否足以解釋其報酬,也受到愈來愈多的質疑。Fama和French在1993年提出額外兩個因子來解釋股票報酬。我們將應用資本資產定價模型和三因子模型來分析1963年7月至2002年12月之美國的三大股票交易所上市公司。藉由一次改變分析過程中的一部分,以觀察參數估計值是否穩定。結果發現Beta_HML總是顯著且最為穩定,而Beta_SMB並不顯著。Beta經常顯著,但變動情況較大。另外,我們將考慮個別股票本身的變異,亦即將隨機效果納入考量。
The Capital Asset Pricing Model (CAPM) has been widely used to analyze the relationship between risk and required rate of return on a stock, while it is doubted that individual stock's risk Beta has enough explanatory power for it's returns. Fama and French (1993) proposed two more factors to help explaining stock returns. We use the CAPM and the three-factor model to analyze listed companys in American stock exchanges, during the period from July 1963 to December 2002. We change part of the analyzing process a time to see if the estimates of the parameters are stable. The risk-premium Beta_HML is always significant and it performs most stable, while another risk-premium Beta_SMB is never significant. Beta is usually significant but it varies. Furthermore, we take within-stock variation into account, so random effects are considered.
1.Introduction 1
2.The Capital Asset Pricing Model 2
2.1.Systematic and Unsystematic Risk 2
2.2.The Capital Asset Pricing Model 3
2.3.Capital Market Line and Security Market Line 4
3.Fama and French Three-Factor Model 8
3.1.Three Common Risk Factors 8
3.2.Fama and MacBeth Two-stage Procedure 9
3.2.1.5x5 Size-BE/ME Portfolios 9
3.2.2.First-stage: Time-series Regression 10
3.2.3.Second-stage: Cross-sectional Regression 10
4.Longitudinal Data Analysis 11
4.1.Linear Mixed-effects Model 11
4.2.Parameter Estimation 12
5.Empirical Study 15
5.1.Data Description 15
5.2.Descriptive Statistics 15
5.3.Time-series Regression Analysis 19
5.4.Cross-sectional Regression Analysis 23
5.5.Linear Mixed-effects Analysis 24
6.Conclusion 25
Appendix 26
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