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State-Space Approaches for Modelling and Control in Financial Engineering : Systems theory and machine learning methods /

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 di erential equations. It then addresses problems associated with the control and estimation of nancial sys...

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Bibliographic Details
Main Authors: Rigatos, Gerasimos G
Corporate Authors: SpringerLink Online service
Published: Springer International Publishing : Imprint: Springer,
Publisher Address: Cham :
Publication Dates: 2017.
Literature type: eBook
Language: English
Series: Intelligent Systems Reference Library, 125
Subjects:
Engineering
Risk management
Computational intelligence
Complexity, Computational
Control engineering
Electronics
Microelectronics
Applications of Nonlinear Dynamics and Chaos Theory
Control
Complexity
Electronics and Microelectronics, Instrumentation
Online Access: http://dx.doi.org/10.1007/978-3-319-52866-3
Summary: 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 di erential equations. It then addresses problems associated with the control and estimation of nancial 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 nancial engineers in decision making. The ap
Carrier Form: 1 online resource (XXVIII, 310 pages): illustrations.
ISBN: 9783319528663
Index Number: Q342
CLC: TP18
Contents: Systems theory and stability concepts -- Main approaches to nonlinear control -- Main approaches to nonlinear estimation -- Linearizing control and ltering for nonlinear dynamics in nancial systems -- Nonlinear optimal control and ltering for nancial systems -- Kalman Filtering Approach for detection of option mispricing in the Black-Scholes PDE -- Kalman Filtering approach to the detection of option mispricing in elaborated PDE nance models -- Corporations default probability forecasting using the Derivative-free nonlinear Kalman Filter -- Validation of nancial options models using neural n

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