Title :
A temperature-dependent SOFTMAX combiner
Author :
Hazarika, Neep ; Taylor, John G.
Author_Institution :
C.L. New Quant Ltd., Wargrave, UK
Abstract :
We describe a method of combining multiple market predictions using a “temperature dependent” combiner (developed at CL NewQuant Limited, UK). CL NewQuant uses a number of techniques to model markets, each of which gives their own predictions. The goal is to develop an efficient combining methodology that takes into account the recent performance of each model in an “optimal” way when calculating combiner weightings
Keywords :
financial data processing; neural nets; optimisation; combiner weightings; multiple market predictions; optimisation; temperature-dependent SOFTMAX combiner; Bonding; Data handling; Economic forecasting; History; Neural networks; Noise level; Predictive models; Singular value decomposition; Smoothing methods; Support vector machines;
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-7044-9
DOI :
10.1109/IJCNN.2001.938444
