  This paper describes the practical application of causal extrapolation of
sequences for the purpose of forecasting. The methods and proofs have been
applied to simulations to measure the range which data can be accurately
extrapolated. Real world data from the Australian Stock exchange and the
Australian Bureau of Meteorology have been tested and compared with simple
linear extrapolation of the same data. In a majority of the tested scenarios
casual extrapolation has been proved to be the more effective forecaster.
