Date of Award
3-2019
Culminating Project Type
Thesis
Degree Name
Applied Economics: M.S.
Department
Economics
College
School of Public Affairs
First Advisor
Nimantha Manamperi
Second Advisor
Mana Komai
Third Advisor
Hung-Chih Yu
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Keywords and Subject Headings
Asset Pricing, Fama-French Three Factors model, Quantile Regression, Chinese Stock Market
Abstract
Fama-French three factors asset pricing model has been well documented for the stock market cross the world. This research will apply Fama-French model to Chinese stock market using the quantile regression approach. All the portfolios are sorted by size and book-to-market ratio to mimic the market size factor and market value factor. The regression reveal that portfolios returns are positively related with market risk and investors will make more profit by holding stocks with smaller company size and higher book-to-market ratio. With the assumption that the returns are normally distributed and expected returns are linearly dependent on three factors, existing studies on Chinese stock market have used ordinary least square (OLS) method to test asset pricing models. These assumptions are not valid in most of the markets. Thus, the present study tests the three risk factors model using quantile regression with the same data set. The results of the study reveal that the when it comes to extreme values in a distribution, the OLS method becomes inefficient. Quantile regression is a better way for investors to examine the extreme values in the distribution tails.
Recommended Citation
Tian, Feng, "The Application of Fama-French Capital Asset Pricing Model and Quantile Regression on Chinese Stock Market" (2019). Culminating Projects in Economics. 10.
https://repository.stcloudstate.edu/econ_etds/10
