Valuation Models and Value Drivers of Stock Prices for the Overall Stock Market and Different Industries : The Malaysian Context - Koay, Yi Chuan (2011)
This dissertation is written to give a better guide for investors to make better-informed investment decisions based on valuation models and value drivers of stock prices. To reach this aim, there are three objectives to achieve. Firstly, the appropriate industry classification system needs to be determined to identify comparable firms. Secondly, the appropriate valuation models are evaluated based on their explanatory power in OLS cross-section regression and valuation errors coupled with the convergence analysis of market values towards the fair values. Lastly, the effects of firm-specific value drivers on the stock prices are evaluated. The last two objectives are evaluated based on the overall stock market and the different industries in Malaysia.The industry classification system is considered appropriate if its industry averages of variables have the highest explanatory power over the individual firms’ variables and has the most homogenous groups of comparable firms. Valuation models that have highest explanatory power and lowest valuation errors coupled with the highest convergence rate of market values towards their fair values are considered the most appropriate. Firm-specific value drivers that have significant t-tests and high explanatory power over stock returns are considered as having significant effects on stock prices. The findings of this study show that GICS is the most appropriate industry classification system. As for valuation models, price multiples based on earnings outperform the rest in both OLS cross-section regression test and convergence test. However, 1-year trailing earnings multiples have the best results in OLS regression test but 1-year forward earnings multiples are ranked top in convergence test. Firm-specific value drivers that have the most effects on stock returns are book-to-market ratio and market capitalization of which both are negatively correlated with stock returns. The other significant value drivers are net gearing and beta, which are positively correlated with stock returns.