Empirical Analysis of Stock Patterns in the Hong Kong Stock Market Based on Asset Pricing Models and Prospect Theory

Abstract

COVID-19 impacts hundreds and thousands of people globally while increasing volatility in the Hong Kong stock market, Asia’s financial hub. This paper aims to investigate whether prospect theory and COVID-19 can help illustrate variations in stock returns on the market based on asset pricing models. The empirical findings demonstrate that the pandemic triggers volatility in the Hong Kong stock market. The return of Portfolios is highly correlated to Hong Kong’s broad stock market. Five factors of Fama French models help improve the model’s performance by capturing cross-sectional anomalies such as firms’ size, profitability, etc. Prospect theory reinforces the accuracy of the model’s prediction, although explanatory power is minimal. Stocks with the highest previous monthly returns have higher returns in the current month. Momentum exists in the Hong Kong stock market, particularly stocks with large market capitalization. Value-weighted portfolios perform better than equal-weighted. Asset pricing models reach precise results because of R-square and are applicable to reflect stock returns’ patterns in the Chinese stock market.