Title :
Predicting short and long term financial trends
Author :
Guggenheimer, H.
Author_Institution :
Polytech. Univ., West Hempstead, NY, USA
Abstract :
For short term predictions of trends in financial statistical data, the author shows the connection between using back data and differentiability assumptions and uses the theory to present new trend extrapolation schemes. For long term prediction, Keynes´s fundamental equations are formulated in a mathematically acceptable manner and its shown how to use these equations to model economic development
Keywords :
economics; finance; forecasting theory; statistical analysis; back data; differentiability assumptions; economic development; financial statistical data; fundamental equations; long term financial trends; long term prediction; mathematically acceptable manner; short term predictions; trend extrapolation schemes; Computer crashes; Differential equations; Earth; Economic forecasting; Extrapolation; Mathematical model; Mathematics; Partial differential equations; Predictive models; Quantum mechanics;
Conference_Titel :
Artificial Intelligence Applications on Wall Street, 1991. Proceedings., First International Conference on
Conference_Location :
New York, NY
Print_ISBN :
0-8186-2240-7
DOI :
10.1109/AIAWS.1991.236573
