Behavioral model

The analysis of an existing time series for the construction of a forward projection is
a means of determining the ‘behavior’ of the series. This is the investigation of
historical data for the existence of trends, periodicity or frequencies of specific events,
the correlation to other time series and the autocorrelation to itself. We can look at
any portfolio of non-maturing assets and liabilities as such a series. The balance of
customer sight deposits is an appropriate example, as neither payment dates nor
amounts are known in advance and the correlation to existing interest rate curves is
negligible.
The general tendency of the data can be used not only to interpolate between data
points but also to extrapolate beyond the data sequence. Essentially, this is the
construction of a projected forecast or ‘behavioral model’ of the series itself.
An understanding of the trends in a broad sense is an answer to ‘What is the
behavior of the time series?’ The investigation as to ‘why’ it is the behavior leads to
an understanding of other stochastic processes driving the evolution of the series
itself and is the logical progression towards ELaR/DyLaR.