A new type of model called SCOMDY was introduced to analyze multivariate time series data. This model combines parametric and nonparametric elements to estimate the mean, variance, and distribution of the data. Researchers studied how well the model works when the assumed distribution is not exactly correct. They developed tests to compare different SCOMDY models and found that models with non-Gaussian distributions are better for analyzing multiple exchange rates. The tests are reliable and easy to use, making them useful for real-world applications.