Exploring the growth value equity valuation model with data visualization

The Growth Value Model(GVM)proposed theoretical closed form formulas consist-ing of Return on Equity(ROE)and the Price-to-Book value ratio(P/B)for fair stock prices and expected rates of return.Although regression analysis can be employed to verify these theoretical closed form formulas,they cannot be explored by classical quintile or decile sorting approaches with intuition due to the essence of multi-factors and dynamical processes.This article uses visualization techniques to help intuitively explore GVM.The discerning findings and contributions of this paper is that we put forward the concept of the smart frontier,which can be regarded as the reasonable lower limit of P/B at a specific ROE by exploring fair P/B with ROE-P/B 2D dynamical process visualization.The coefficients in the formula can be determined by the quantile regression analysis with market data.The moving paths of the ROE and P/B in the cur-rent quarter and the subsequent quarters show that the portfolios at the lower right of the curve approaches this curve and stagnates here after the portfolios are formed.Furthermore,exploring expected rates of return with ROE-P/B-Return 3D dynamical process visualization,the results show that the data outside of the lower right edge of the“smart frontier”has positive quarterly return rates not only in the t+1 quarter but also in the t+2 quarter.The farther away the data in the t quarter is from the“smart frontier”,the larger the return rates in the t+1 and t+2 quarter.

BM(book-to-market ratio) factor: mediumterm momentum and long-term reversal

To explain medium-term momentum and long-term reversal,we use the difference between the optional model and the CAPM model to construct a winner-loser portfolio.According to the CAPM model’s zero explanatory ability with respect to stock market anomalies,we obtain an anomaly interpretative model.This study shows that this anomaly interpretative model can explain stock market perceptions and medium-term momentum.Most importantly,BM is a critical factor in the model’s explanatory ability.We present a robustness test,which includes selecting new sample data,adding new auxiliary variables,changing sample years,and adding industry fixed effects.In general,the BM effect does have considerable explanatory power in medium-term momentum and long-term reversal.