This contribution introduces new frontier models to rate mutual funds that can simultaneously handle multiple moments and multiple times. These new models are empirically applied to hedge fund data, since this category of funds is known to be subject to non-normal return distributions. We define a simple buy-and-hold backtesting strategy to test for the impact of multiple moments and multiple times separately and jointly. The empirical results demonstrate that the proposed frontier models perform better than most financial performance measures and existing frontier models in selecting promising funds.