  The Capital Asset Pricing Model (CAPM) is one of the original models in
explaining risk-return relationship in the financial market. However, when
applying the CAPM into reality, it demonstrates a lot of shortcomings. While
improving the performance of the model, many studies, on one hand, have
attempted to apply different statistical methods to estimate the model, on the
other hand, have added more predictors to the model. First, the thesis focuses
on reviewing the CAPM and comparing popular statistical methods used to
estimate it, and then, the thesis compares predictive power of the CAPM and the
Fama-French model, which is an important extension of the CAPM. Through an
empirical study on the data set of large cap stocks, we have demonstrated that
there is no statistical method that would recover the expected relationship
between systematic risk (represented by beta) and return from the CAPM, and
that the Fama-French model does not have a better predictive performance than
the CAPM on individual stocks. Therefore, the thesis provides more evidence to
support the incorrectness of the CAPM and the limitation of the Fama-French
model in explaining risk-return relationship.
