State-Space Approaches for Modelling and Control in Financial Engineering

Lieferzeit: Lieferbar innerhalb 14 Tagen

106,99 

Systems theory and machine learning methods, Intelligent Systems Reference Library 125

ISBN: 3319528653
ISBN 13: 9783319528656
Autor: Rigatos, Gerasimos G
Verlag: Springer Verlag GmbH
Umfang: xxviii, 310 S., 26 s/w Illustr., 88 farbige Illustr., 310 p. 114 illus., 88 illus. in color.
Erscheinungsdatum: 13.04.2017
Auflage: 1/2018
Produktform: Gebunden/Hardback
Einband: Gebunden

Presents new findings useful for academic teaching and research and to develop systematic methods for management and risk minimization in financial systemsSolves in a conclusive manner problems associated with the control and stabilization of nonlinear and chaotic dynamics in financial systemsContains innovative results in control and estimation problems for financial systems and for statistical validation of computational tools used for financial decision makingIncludes supplementary material: sn.pub/extras

Artikelnummer: 840022 Kategorie:

Beschreibung

The book conclusively solves problems associated with the control and estimation of nonlinear and chaotic dynamics in nancial systems when these are described in the form of nonlinear ordinary dierential equations. It then addresses problems associated with the control and estimation of nancial systems governed by partial dierential 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 nancial engineers in decision making.The application of state-space models in nancial engineering means that the heuristics and empirical methods currently in use in decision-making procedures for nance 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 nancial systems to be established.Coveringthe following key areas of nancial engineering: (i) control and stabilization of nancial 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 nancial engineering. It is also a useful resource for the engineering and computer science community

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