Noise-augmented asset pricing models : evidence from the Greater China stock markets during two major financial crises

The main contribution of the thesis is the construction of noise-augmented asset pricing models. These models are the extension of Fama & French Three Factor Model (1992,1993) and subsequent improved version of Five Factor Model (2015), by adding a behavourial factor - investor sentiment (INVSENT). To the author’s knowledge, this is one of the first attempts to quantitatively reconcile risk based theory and behavioral finance by developing parsimonious asset pricing models for explaining value premium phenomenon, especially in the context of financial crises. Little research has been carried out on the value premium phenomenon over a short horizon during high volatility period. Previous empirical results show that over the long run, value stocks outperformed growth stocks, with considerable firm size effect. There are two competing schools of thoughts that explain the value premium phenomenon - risk based theories and behavior models. However, the occurrence of the Global Financial Crisis and Eurozone Crisis has opened a new and alternative window to study the value premium phenomenon and further examine the underlying reasoning. Firstly, in examining the risk and return relationship of value stocks and growth stocks of the Greater China stock markets during the two major financial crises, it show that growth stocks outperformed value stocks during both the Global Financial Crisis and Euro Zone Crisis in the China and Hong Kong stock markets. However, value stocks outperformed the growth stocks in the Taiwan stock market during the Global Financial Crisis and Euro Zone Crisis. The small size effect did not really diminish in the Greater China stock markets during two major financial crises. Also, standard risk measures – standard deviation and Sharpe ratio do not fully explain the risk and return relationship of these two stock selection strategies. Secondly, in explaining value premium under the Banko, Conover and Jensen Model (2006), mixed results are observed. During the Global Financial Crisis, industry book-to-market ratio is a strong signal in the China and Hong Kong stock markets, whereas the firm book-to-market ratio is a strong signal in the Hong Kong and Taiwan stock markets. Further analysis at the industrial level has revealed that industry book-to-market ratio is a more prominent factor than the firm book-to-market ratio. During the Euro Zone Crisis, the firm level book-to-market ratio is significant the Hong Kong stock markets, even after controlling for market capitalisation and beta.The study under the Fama and French Three Factor Model (1992, 1993) has shown that the three risk measures - market risk premium (MRP) factor, SMB factor and HML factor are semi-strong signals in explaining value premium in the Greater China stock markets during the two major financial crises. Furthermore, the investigation under the Fama and French Five Factor Model (2015) has shed light that the five risk measures - market risk premium (MRP) factor, SMB factor, HML factor, profitability factor (RMW) and investment factor (CMA) are semi-strong signals. Considering the values of adjusted R-squared and varying signals of the risk measures, it is argued that risk factors of the three asset pricing models do not fully explain value premium phenomenon in the Greater China stock markets during the two major financial crises.Thirdly, the study under the noise-augmented capital asset pricing models reveals that the investor sentiment (INVSENT) factor is a statistically significant determinant of the stock returns in the Hong Kong stock markets during the Euro Zone Crisis. The investor sentiment (INVSENT) factor is only weakly significant or insignificant statistically in the China and Taiwan stock markets during these two financial crises. For the risk measures in the Fama and French’s models, market risk premium (MRP) factor, SMB factor, HML factor, profitability factor (RMW) and investment factor (CMA) are semi-strong signals. The adjusted R-squared values of the noise-augmented asset pricing models are higher than the original Fama and French models. The findings of this research are expected to provide a fresh insight to the investment managers in the asset allocation and portfolio management decision. The practical implication is that when investing during the period of financial crises, one has to firstly, be selectively in stocks and hence businesses involved, relying on the principles embodied in the risk based model – Fama and French Five Factor Model. Then, be aware of the mispricing caused by the investor sentiment.