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Neural Networks - originally inspired from Neuroscience - provide powerful models for statistical data analysis. Their most prominent feature is their ability to "learn" dependencies based on a finite number of observations.
Then we gave an overview of existing economic applications of neural networks, where we distinguished between three types: Classification of economic agents, time series prediction and the modelling of bounded rational agents.
Neural Networks – originally inspired from Neuroscience – provide powerful models for statistical data analysis. Their most prominent feature is their ability to “learn” dependencies based on a finite number of observations.
1 Ιαν 1999 · We discuss the possibility of applying neural networks for the analysis of financial markets. We consider simple forecasting and more complicated devising of trading rules.
31 Αυγ 1998 · Neural Networks – originally inspired from Neuroscience – provide powerful models for statistical data analysis. Their most prominent feature is their ability to “learn” dependencies based ...
23 Μαρ 2021 · Our study uses the grey relational analysis (GRA) and artificial neural network (ANN) models for the prediction of consumer exchange-traded funds (ETFs). We apply eight variables, including the put/call ratio, the EUR/USD exchange rate, the volatility index, the Commodity Research Bureau Index (CRB), the short-term trading index, the New York ...
Neural Networks, Genetic Algorithms and Economic Models: An Introduction -- 1. Artificial neural networks and genetic algorithms -- 2. Economic models and decision-making -- Pt.
