This article proposes a novel valuation model, growth and value hybrid model, to estimate the stock price. This proposed model combines the essence of the asset-based approach, the income-based approach, and the principle of mean reversion to develop the theoretical closed-form formula consisting of three coefficients: value coefficient, value support coefficient, and growth coefficient. Regression analysis is employed to fit market data to determine these coefficients. Moreover, this study proposes the double sorting method to build the quantile regression models of the formula to estimate the stock price at a specific quantile. The results show that the predictive capability of the hybrid valuation model is superior to the model without using value support coefficient, which supports the assumption that the PBR is not associated with the ROE when the ROE is less than a threshold. In different time periods of the stock market, no significant difference exists on the value support coefficient. However, the variations of the value coefficient and the growth coefficient are significant.
