Title :
An outline for a Kalman filter and recursive parameter estimation approach applied to stock market forecasting
Author :
McGonigal, Denis ; Ionescu, Daniela
Author_Institution :
Dept. of Syst. Sci., Ottawa Univ., Ont., Canada
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
Keywords :
Kalman filters; adaptive estimation; autoregressive moving average processes; finance; prediction theory; recursive estimation; spectral analysis; stock markets; ARMA modelling; Gauss-Newton algorithm; Kalman filter; adaptive parameter estimation; recursive parameter estimation approach; spectral estimation; stock market forecasting; Adaptive filters; Economic forecasting; Filtering; Kalman filters; Least squares methods; Newton method; Parameter estimation; Predictive models; Recursive estimation; Stock markets;
Conference_Titel :
Electrical and Computer Engineering, 1995. Canadian Conference on
Conference_Location :
Montreal, Que.
Print_ISBN :
0-7803-2766-7
DOI :
10.1109/CCECE.1995.526633
