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

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.

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