DocumentCode
3492903
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
Volume
2
fYear
1995
fDate
5-8 Sep 1995
Firstpage
1148
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical and Computer Engineering, 1995. Canadian Conference on
Conference_Location
Montreal, Que.
ISSN
0840-7789
Print_ISBN
0-7803-2766-7
Type
conf
DOI
10.1109/CCECE.1995.526633
Filename
526633
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