Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Neural Networks: Tricks of the Trade, this book is an outgrowth of a 1996 NIPS workshop
Financial Risk Manager Handbook (Wiley Finance)
Financial Risk Manager Handbook (Wiley Finance)
Recurrent neural networks are universal approximators
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
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In econometrics, the behaviour of financial markets is described by quantitative variables. Mathematical and statistical methods are used to explore economic relationships and to forecast the future market development. However, econometric modeling is often limited to a single financial market. In the age of globalisation financial markets are highly interrelated and thus, single market analyses are misleading. In this paper we present a new way to model the dynamics of coherent financial markets. Our approach is based on so-called dynamical consistent neural networks (DCNN), which are able to map multiple scales and different sub-dynamics of the coherent market movement. Unlikely to standard econometric methods, small market movements are not treated as noise but as valuable market information. We apply the DCNN to forecast monthly movements of major foreign exchange (FX) rates. Based on the DCNN forecasts we develop a technical trading indicator to support investment decisions.