Under multiple linear regression models, there's always the risk of overestimating the impact of additional variables on the explanatory power of the resulting model, which is why most researchers recommend using the adjusted R², $\overline{R}^2$, instead of R² itself. This adjusted R²: | Financial Risk Manager Part 1 Quiz - LeetQuiz