Optional Processes

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A01=Alexander Melnikov
A01=Mohamed Abdelghani
advanced graduate textbook
Author_Alexander Melnikov
Author_Mohamed Abdelghani
Borel Subsets
Category=PBK
Category=PBT
Category=PBW
Choquet's Theorem
Choquet’s Theorem
Conditional Expectation
Continuous Local Martingale
Default Events
Default Process
Default Time
Defaultable Claim
Defaultable Markets
Doob Decomposition
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
Ex-dividend Price
filtering theory
financial mathematics
Finite Variation Process
Gronwall lemma
Integrable Random Variables
Local Martingale
mathematical finance
Measurable Space
Monotone Class Theorem
optional processes
Paved Set
probability theory
Reduced Form Models
Risk Neutral Valuation Formula
Section Theorem
Self-financing Trading Strategy
semimartingale decomposition
Snell Envelope
stochastic analysis
stochastic calculus
stochastic differential equations
stochastic process applications
strong martingales
supermartingales
Topological Space
Uniformly Integrable
unusual probability spaces
Usual Conditions

Product details

  • ISBN 9781138337268
  • Weight: 843g
  • Dimensions: 191 x 235mm
  • Publication Date: 14 Jul 2020
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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It is well-known that modern stochastic calculus has been exhaustively developed under usual conditions. Despite such a well-developed theory, there is evidence to suggest that these very convenient technical conditions cannot necessarily be fulfilled in real-world applications.

Optional Processes: Theory and Applications seeks to delve into the existing theory, new developments and applications of optional processes on "unusual" probability spaces. The development of stochastic calculus of optional processes marks the beginning of a new and more general form of stochastic analysis.

This book aims to provide an accessible, comprehensive and up-to-date exposition of optional processes and their numerous properties. Furthermore, the book presents not only current theory of optional processes, but it also contains a spectrum of applications to stochastic differential equations, filtering theory and mathematical finance.

Features

  • Suitable for graduate students and researchers in mathematical finance, actuarial science, applied mathematics and related areas
  • Compiles almost all essential results on the calculus of optional processes in unusual probability spaces
  • Contains many advanced analytical results for stochastic differential equations and statistics pertaining to the calculus of optional processes
  • Develops new methods in finance based on optional processes such as a new portfolio theory, defaultable claim pricing mechanism, etc.

Mohamed Abdelghani completed his PhD in Mathematical Finance from the University of Alberta. He is currently working as a V.P. in quantitative finance and machine learning at Morgan Stanley, New York, USA.

Alexander Melnikov is a Professor in Mathematical Finance at the University of Alberta, Edmonton, Canada. His research interests belong to the area of contemporary stochastic analysis and its numerous applications in Mathematical Finance, Statistics and Actuarial Science. He has written six books as well as over one hundred research papers in leading academic journals.

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