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

Gerasimos G. Rigatos

ISBN 10: 3319850040 / ISBN 13: 9783319850047

Editore: Springer, 2018

State-Space Approaches for Modelling and Control in Financial Engineering | Systems theory and machine learning methods | Gerasimos G. Rigatos | Taschenbuch | 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 Print on Demand. Codice articolo 114227736

Riassunto:

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 differential equations. It then addresses problems associated with the control and estimation of financial systems governed by partial differential 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

Dalla quarta di copertina:

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 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.

Covering the 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

Dati bibliografici

Titolo: State-Space Approaches for Modelling and ...
Casa editrice: Springer
Data di pubblicazione: 2018
Legatura: Taschenbuch
Condizione: Neu