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Ajouter au panierHardcover. Etat : Brand New. 250 pages. 9.25x6.25x0.75 inches. In Stock.
Langue: anglais
Edité par Springer-Verlag New York Inc, 2017
ISBN 10 : 3319528653 ISBN 13 : 9783319528656
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Ajouter au panierTaschenbuch. Etat : Neu. State-Space Approaches for Modelling and Control in Financial Engineering | Systems theory and machine learning methods | Gerasimos G. Rigatos | Taschenbuch | Intelligent Systems Reference Library | xxviii | Englisch | 2018 | Springer | EAN 9783319850047 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Langue: anglais
Edité par Springer International Publishing, Springer International Publishing, 2018
ISBN 10 : 3319850040 ISBN 13 : 9783319850047
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Ajouter au panierTaschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The book conclusively solves problems associated with the control and estimation of nonlinear and chaotic dynamics in financial systems when these are described in the form of nonlinear ordinary di erential equations. It then addresses problems associated with the control and estimation of financial systems governed by partial di erential equations (e.g. the Black-Scholes partial differential equation (PDE) and its variants). Lastly it an offers optimal solution to the problem of statistical validation of computational models and tools used to support financial engineers in decision making.The application of state-space models in financial engineering means that the heuristics and empirical methods currently in use in decision-making procedures for finance can be eliminated. It also allows methods of fault-free performance and optimality in the management of assets and capitals and methods assuring stability in the functioning of financial systems to be established.Coveringthe following key areas of financial engineering: (i) control and stabilization of financial systems dynamics, (ii) state estimation and forecasting, and (iii) statistical validation of decision-making tools, the book can be used for teaching undergraduate or postgraduate courses in financial engineering. It is also a useful resource for the engineering and computer science community.
Langue: anglais
Edité par Springer International Publishing, 2017
ISBN 10 : 3319528653 ISBN 13 : 9783319528656
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Ajouter au panierBuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The book conclusively solves problems associated with the control and estimation of nonlinear and chaotic dynamics in financial systems when these are described in the form of nonlinear ordinary di erential equations. It then addresses problems associated with the control and estimation of financial systems governed by partial di erential equations (e.g. the Black-Scholes partial differential equation (PDE) and its variants). Lastly it an offers optimal solution to the problem of statistical validation of computational models and tools used to support financial engineers in decision making.The application of state-space models in financial engineering means that the heuristics and empirical methods currently in use in decision-making procedures for finance can be eliminated. It also allows methods of fault-free performance and optimality in the management of assets and capitals and methods assuring stability in the functioning of financial systems to be established.Coveringthe following key areas of financial engineering: (i) control and stabilization of financial systems dynamics, (ii) state estimation and forecasting, and (iii) statistical validation of decision-making tools, the book can be used for teaching undergraduate or postgraduate courses in financial engineering. It is also a useful resource for the engineering and computer science community.
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Ajouter au panierEtat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Investigates algorithmic methods based on machine learning in order to design sequential investment strategies for financial markets. This title is suitable for researchers and graduate students in computer science, finance, statistics, mathematics, and eng.