Value relevance of cross-sectional earnings forecast model and the expected returns

Purpose The study assessed the value relevance of residual income (RI) model of Li and Mohanram (2014) in terms of bias and accuracy in Indian stock market. In addition, it examined whether value-to-price (V/P), which operationalises intrinsic value (V) using cross-sectional earnings projections, can account for the distribution of contemporaneous stock returns. Design/methodology/approach The paper employs asset pricing regression to analyse the excess risk-adjusted returns and a panel regression model (fixed estimates) to estimate the earnings for a cross-section of Bombay Stock Exchange listed equities from 2003 to 2020. In addition, the robustness is evaluated using Monte-Carlo simulation. Findings The results demonstrate that the RI model provides accurate forecasts for periods ranging from one to three years. Earnings are found to be highly persistent, whereas book value and accruals have little value significance for Indian investors. The highest V/P quintile portfolio is found to be capable of generating substantial four-factor alpha, and its performance is consistent throughout the study period including market downturns. Practical implications The study lends credence to the notion that investors can reliably determine a company’s true value using only publicly available information. Market participants and experts can also benefit from the findings by effectively incorporating the V/P measure into their portfolio allocation. Originality/value To the best of our knowledge, this study is a first attempt to compute intrinsic value estimates for a large set of Indian companies using a cross-sectional model. In addition, this study provides out-of-sample evidence to validate strategy’s success in an emerging market context.