Fuzzy hybrid system for forecasting financial time series

We propose a fuzzy hybrid system for forecasting time series, based on the automatic\nfitting method auto.arima included in the forecast package for R. First, we generate\npredictions and apply fuzzy clustering to identify patterns and tendencies. Then, using\ninference criteria on the centers of the clusters we end up with a mean forecast. The\nsystem allows the inclusion of expert criteria, i.e., the user can set up restrictions on\nthe clustering based on a priori knowledge of the time series. This approach can be\napplied to any financial time series meeting the requirements of Seasonal Autoregressive\nIntegrated Moving Average (SARIMA) models. The proposed method is implemented\nin R. Numerical tests on series of loans, accounts, and saving accounts demonstrate\nthe efficacy of the method