Does CAPM Accurately Predict Expected Returns of Nifty 50 Stocks? An Empirical Investigation Using 2022-2025 Data

The Capital Asset Pricing Model (CAPM), developed by Sharpe (1964) and Lintner (1965), posits a linear relationship between an asset's systematic risk, measured by beta, and its expected return. Despite its foundational status in financial economics, the empirical validity of CAPM has been extensively challenged, with particular scepticism directed at emerging equity markets. This study empirically investigates whether CAPM accurately predicts the expected returns of Nifty 50 stocks using daily return data for ten index constituents over the period January 2022 to March 2025, comprising 804 daily observations per security. Beta coefficients are estimated through Ordinary Least Squares (OLS) regression using the excess return market model in Gretl, with robustness evaluated through Breusch-Pagan heteroskedasticity tests, Ramsey RESET specification tests, Durbin-Watson autocorrelation diagnostics, and normality of residuals tests. The results indicate that while beta is statistically significant for all 10 sample stocks, CAPM demonstrates limited predictive accuracy, the single market factor explains an average of only 28.42% of return variation, and the model systematically overestimates returns for 6 out of 10 stocks. Heteroskedasticity is detected in 7 out of 10 stocks and model misspecification in 3 out of 10, consistent with the theoretical critique of Lai and Stohs (2015) regarding CAPM's inherent endogeneity. These findings extend the prior Indian evidence of Chaudhary (2016) to the post-pandemic market environment of 2022-2025.