An Empirical Analysis of Fama and French Three Factor Model－An Application of GARCH Model and Quantile Regression

• Main Authors: Cheng-Hsun Lin, 林政勳
• Other Authors: Nai-Fong Kuo Ph.D.
• Format: Others
• Language: zh-TW
• Published: 2004
• Online Access: http://ndltd.ncl.edu.tw/handle/02509182326551912666

碩士 === 真理大學 === 管理科學研究所 === 92 === This research we apply GARCH model proposed by Bollerslev（1986） and quantile regression proposed by Koenker and Bassett(1978), to survey the cross section ability of Fama－French three factor model.Our finding is as follows. When error term is taken into account together with first order autocorrelation and GARCH model, Fama－French three factor model exists size effect and book-to-market effect to Taiwan stock market. However, market factor also has quite explaining importance that we couldn’t ignore. Furthermore, most models can explain the return of Taiwan stock market , and this kind of explaining ability means that Fama－French three factor model can explain domestic security return completely in extent well. The empirical result from quantile regression is found that, excepted for median quantile, at other quantile points show that there are still some factors omitted to consider in Fama－French three factor model. In big-size/median-book to market portfolio, size factor only can explain returns at higher point even although coefficient is negative. In big-size/low-book to market portfolio, the estimated result of OLS exhibit size factor is insignificant, but is significant at 70 percent quantile. Under the condition of that the error term can’t follow normality and size factor is heteroskedasticity, the result is found that quantile regression could retrieve the shortage of OLS. Finally, with the respect to the model explaining ability, Pseudo R2 of all models, has the phenomenon of increasing from lower quantile to higher quantile, which means that at higher quantile, Fama－French three factors can explain stock average returns more.