Language:
English
繁體中文
Help
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
State-space approaches for modelling...
~
Rigatos, Gerasimos G.
State-space approaches for modelling and control in financial engineering = systems theory and machine learning methods /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
State-space approaches for modelling and control in financial engineering/ by Gerasimos G. Rigatos.
Reminder of title:
systems theory and machine learning methods /
Author:
Rigatos, Gerasimos G.
Published:
Cham :Springer International Publishing : : 2017.,
Description:
xxviii, 310 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:
Springer eBooks
Subject:
Financial engineering - Mathematics. -
Online resource:
http://dx.doi.org/10.1007/978-3-319-52866-3
ISBN:
9783319528663
State-space approaches for modelling and control in financial engineering = systems theory and machine learning methods /
Rigatos, Gerasimos G.
State-space approaches for modelling and control in financial engineering
systems theory and machine learning methods /[electronic resource] :by Gerasimos G. Rigatos. - Cham :Springer International Publishing :2017. - xxviii, 310 p. :ill. (some col.), digital ;24 cm. - Intelligent systems reference library,v.1251868-4394 ;. - Intelligent systems reference library ;v. 3..
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. Covering the 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.
ISBN: 9783319528663
Standard No.: 10.1007/978-3-319-52866-3doiSubjects--Topical Terms:
1141446
Financial engineering
--Mathematics.
LC Class. No.: HG176.7
Dewey Class. No.: 658.15
State-space approaches for modelling and control in financial engineering = systems theory and machine learning methods /
LDR
:02455nam a2200313 a 4500
001
884770
003
DE-He213
005
20171103154401.0
006
m d
007
cr nn 008maaau
008
180530s2017 gw s 0 eng d
020
$a
9783319528663
$q
(electronic bk.)
020
$a
9783319528656
$q
(paper)
024
7
$a
10.1007/978-3-319-52866-3
$2
doi
035
$a
978-3-319-52866-3
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
HG176.7
072
7
$a
UYQ
$2
bicssc
072
7
$a
COM004000
$2
bisacsh
082
0 4
$a
658.15
$2
23
090
$a
HG176.7
$b
.R565 2017
100
1
$a
Rigatos, Gerasimos G.
$3
784210
245
1 0
$a
State-space approaches for modelling and control in financial engineering
$h
[electronic resource] :
$b
systems theory and machine learning methods /
$c
by Gerasimos G. Rigatos.
260
$a
Cham :
$c
2017.
$b
Springer International Publishing :
$b
Imprint: Springer,
300
$a
xxviii, 310 p. :
$b
ill. (some col.), digital ;
$c
24 cm.
490
1
$a
Intelligent systems reference library,
$x
1868-4394 ;
$v
v.125
520
$a
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. Covering the 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.
650
0
$a
Financial engineering
$x
Mathematics.
$3
1141446
650
0
$a
Finance
$x
Decision making.
$3
867591
650
0
$a
Kalman filtering.
$3
579841
650
1 4
$a
Engineering.
$3
561152
650
2 4
$a
Computational Intelligence.
$3
768837
650
2 4
$a
Risk Management.
$3
569483
650
2 4
$a
Applications of Nonlinear Dynamics and Chaos Theory.
$3
1113607
650
2 4
$a
Control.
$3
782232
650
2 4
$a
Complexity.
$3
669595
650
2 4
$a
Electronics and Microelectronics, Instrumentation.
$3
670219
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer eBooks
830
0
$a
Intelligent systems reference library ;
$v
v. 3.
$3
775129
856
4 0
$u
http://dx.doi.org/10.1007/978-3-319-52866-3
950
$a
Engineering (Springer-11647)
based on 0 review(s)
Multimedia
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login