The study introduces a new way to estimate changing betas and alpha in the CAPM model using a functional coefficient regression technique. This method combines predictors into an index, allowing for more flexible assumptions. By selecting appropriate index variables with a specific penalty, the model can estimate and choose variables at the same time. The results show that this new model outperforms other models in explaining asset returns, and there is no strong evidence to reject the conditional CAPM.