There is any mathematical model that has show to be superior to do forecasting in a time series application???

Question

There is any mathematical model that has show to be better to do forecasting in the area of economic, financial, management, operations or marketing??? I was trying to do a forecast of a selling variable, and a try a lot of models. But the one that has better performanced was to cut the variable to eliminated the stationarity and then to do a moving average in every segment. A wasn´t exciting with this results because was soo simple. Then a compared this results with a model of other person and a lose, but the different was soo little that i'm not sure if that different was statistical significance.

Answer 1

One important implementation of Bayesian forecasting is the Multi-State Kalman Filter (MSKF) method. It is particularly suited for short and irregular time series data. In certain applications, time series data are available on numerous parallel observational units which, while not having cause-and-effect relationships between them, are subject to the same external forces (e.g., business cycles). Treating them separately may lose useful information for forecasting. For such situations, involving seemingly unrelated time series, this article develops a Bayesian forecasting method called C-MSKF that combines the MSKF method with the Conditionally Independent Hierarchical method