Random Dynamical Systems in Finance

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A01=Anatoliy Swishchuk
A01=Shafiqul Islam
advanced financial system stability
Author_Anatoliy Swishchuk
Author_Shafiqul Islam
Banach Space
Category=KCH
Category=KF
Category=PBT
Category=PBW
Category=UR
Category=UY
chain
Cox Ingersoll Ross Model
delayed differential equations
Deterministic Dynamical Systems
differential
Diffusion Approximation
Dw
Dynkin Formula
eq_bestseller
eq_business-finance-law
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
equation
Ergodic Classes
ergodic theory applications
financial mathematics
formula
Frobenius Perron Operator
HJB Equation
Infinitesimal Operator
Invariant Density
Invariant Measures
markov
Markov Control
Markov Renewal Processes
Markov Switching
Martingale Problem
optimal control in economics
Optimal Portfolio Selection Problem
option
Option Pricing Formula
pricing
process
Random Dynamical Systems
Random Maps
regime switching models
renewal
semi-Markov Process
stochastic
Stochastic Differential Delay Equations
Stochastic Differential Equations
stochastic modeling
Stochastic Stability
Weak Infinitesimal Operator

Product details

  • ISBN 9780367380144
  • Weight: 453g
  • Dimensions: 156 x 234mm
  • Publication Date: 23 Sep 2019
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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The theory and applications of random dynamical systems (RDS) are at the cutting edge of research in mathematics and economics, particularly in modeling the long-run evolution of economic systems subject to exogenous random shocks. Despite this interest, there are no books available that solely focus on RDS in finance and economics. Exploring this emerging area, Random Dynamical Systems in Finance shows how to model RDS in financial applications.

Through numerous examples, the book explains how the theory of RDS can describe the asymptotic and qualitative behavior of systems of random and stochastic differential/difference equations in terms of stability, invariant manifolds, and attractors. The authors present many models of RDS and develop techniques for implementing RDS as approximations to financial models and option pricing formulas. For example, they approximate geometric Markov renewal processes in ergodic, merged, double-averaged, diffusion, normal deviation, and Poisson cases and apply the obtained results to option pricing formulas.

With references at the end of each chapter, this book provides a variety of RDS for approximating financial models, presents numerous option pricing formulas for these models, and studies the stability and optimal control of RDS. The book is useful for researchers, academics, and graduate students in RDS and mathematical finance as well as practitioners working in the financial industry.

Swishchuk, Anatoliy ; Islam, Shafiqul

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