Regardless as to the robustness and strength of any forecast, without the addition
of new information a limit of model accuracy will always be reached. A study of the
behavior of a series can in many cases be broken down to ‘grass roots’ levels.
Below the analysis of a total or accumulated position could, for instance, be strong
underlying counterparty trends. Their behavior could be of the nature of having
regular, payment structures, transaction openings or of a trend in the portfolio itself.
In line with this is the study of any correlation existing between more than one time
series. The detection of one or both of these behavioral features leads to the logical
progression of the modeling procedure.
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