TESTING OF CAPITAL ASSET PRICING MODEL: AN EMPIRICIAL ANALYSIS BASED ON THE SHANGHAI AND HONG KONG STOCK MAEKETS

Tian, Xinqi (2022) TESTING OF CAPITAL ASSET PRICING MODEL: AN EMPIRICIAL ANALYSIS BASED ON THE SHANGHAI AND HONG KONG STOCK MAEKETS. [Dissertation (University of Nottingham only)]

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Abstract

The CAPM model attempts to represent people's complex investment decisions through a series of rigorous assumptions about the real stock market. The CAPM model attempts to express people's complex investment decisions in terms of numerically calculated utility values. However, the conditional assumptions of the CAPM model cannot really be met, even in more mature equity markets. As an important theory of financial asset pricing, the applicability of the CAPM model in real capital markets is naturally attracted to research. In this paper, the Shanghai and Hong Kong stock markets are used as the subject of study to test the validity of the CAPM model for the period 27 November 2016 - 21 November 2021. The test is based on the Fama-Macbeth Approach, in which the portfolios are no longer grouped in order of β size, but a representative market portfolio is selected as the portfolio for time series regression and cross-sectional regression on market indicators (method from Wei, 2016). The regression results show that in the time series regression, both the Shanghai equity market and the Hong Kong equity market exhibit a linear relationship between the excess returns of the portfolio and the excess returns of the market, but in the cross-sectional regression, the linear relationship shown by the CAPM model exists in the Shanghai equity market for only one time period, while in the analysis of the Hong Kong equity market, there are two time periods that conform to the CAPM model. In contrast, the CAPM model is more valid in the Hong Kong market than in the Shanghai equity market, but overall, the CAPM model is not applicable to both markets.

Item Type: Dissertation (University of Nottingham only)
Depositing User: Tian, Xinqi
Date Deposited: 27 Apr 2023 15:17
Last Modified: 27 Apr 2023 15:17
URI: https://eprints.nottingham.ac.uk/id/eprint/68062

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