This volume selects the best contributions from the Fourth International Conference on Neural Networks in the Capital Markets (NNCM). The conference brought together academics from several disciplines with strategists and decision makers from the financial industries.
The various chapters present and compare new techniques from many areas including data mining, information systems, machine learning, and statistical artificial intelligence. The volume focuses on evaluating their usefulness for problems in computational finance and financial engineering.
Applications - risk management; asset allocation; dynamic trading and hedging; forecasting; trading cost control. Markets - equity; foreign exchange; bond; commodity; derivatives; Approaches - data mining; statistical AI; machine learning; Monte Carlo simulation; bootstrapping; genetic algorithms; nonparametric methods; fuzzy logic.
COMPUTATIONAL ECONOMICS / FINANCE MATHEMATICAL / QUANTITATIVE FINANCE NEURAL NETWORKS / NETWORKINGThe chapters emphasizes in-depth and comparative evaluation with established approaches.
"Sinopsis" puede pertenecer a otra edición de este libro.
This volume selects the best contributions from the Fourth International Conference on Neural Networks in the Capital Markets (NNCM). The conference brought together academics from several disciplines with strategists and decision makers from the financial industries.The various chapters present and compare new techniques from many areas including data mining, information systems, machine learning, and statistical artificial intelligence. The volume focuses on evaluating their usefulness for problems in computational finance and financial engineering.Applications - risk management; asset allocation; dynamic trading and hedging; forecasting; trading cost control. Markets - equity; foreign exchange; bond; commodity; derivatives; Approaches - data mining; statistical AI; machine learning; Monte Carlo simulation; bootstrapping; genetic algorithms; nonparametric methods; fuzzy logic.The chapters emphasizes in-depth and comparative evaluation with established approaches.
"Sobre este título" puede pertenecer a otra edición de este libro.
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Buch. Condición: Neu. DECISION TECH FOR FINANCIAL ENGRG (V7) | Weigend Andreas S | Buch | PROGRESS IN NEURAL PROCESSING | Englisch | 1997 | World Scientific | EAN 9789810231231 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Nº de ref. del artículo: 136336507
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Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This volume selects the best contributions from the Fourth International Conference on Neural Networks in the Capital Markets (NNCM). The conference brought together academics from several disciplines with strategists and decision makers from the financial industries.The various chapters present and compare new techniques from many areas including data mining, information systems, machine learning, and statistical artificial intelligence. The volume focuses on evaluating their usefulness for problems in computational finance and financial engineering.Applications - risk management; asset allocation; dynamic trading and hedging; forecasting; trading cost control. Markets - equity; foreign exchange; bond; commodity; derivatives; Approaches - data mining; statistical AI; machine learning; Monte Carlo simulation; bootstrapping; genetic algorithms; nonparametric methods; fuzzy logic.COMPUTATIONAL ECONOMICS / FINANCE | MATHEMATICAL / QUANTITATIVE FINANCE | NEURAL NETWORKS / NETWORKINGThe chapters emphasizes in-depth and comparative evaluation with established approaches. Nº de ref. del artículo: 9789810231231
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