An outline for a Kalman filter and recursive parameter estimation approach applied to stock market forecasting

Abstract

An outline of a system that models and forecasts stock market processes is described. The method involves a spectral estimation approach to ARMA modelling, forecasting is performed through Kalman filtering, and adaptive parameter estimation performed via the Gauss-Newton algorithm.