The article compares different methods for predicting the risk of hedge fund investments. By using various models, the researchers found that certain models can better predict the likelihood of losses in hedge fund strategies. They discovered that models considering factors like autocorrelation and fat tails in returns can improve the accuracy of predicting potential losses. Additionally, they found that the accuracy of predicting losses is more influenced by the type of distribution model used rather than the specific mean/variance model.