Nonlinear expectations and stochastic calculus under uncertainty : with robust CLT and G-Brownian motion / Shige Peng.
2019
QA274.75
Linked e-resources
Linked Resource
Concurrent users
Unlimited
Authorized users
Authorized users
Document Delivery Supplied
Can lend chapters, not whole ebooks
Details
Title
Nonlinear expectations and stochastic calculus under uncertainty : with robust CLT and G-Brownian motion / Shige Peng.
Author
ISBN
9783662599037 (electronic book)
3662599031 (electronic book)
9783662599020
3662599031 (electronic book)
9783662599020
Publication Details
Berlin, Germany : Springer, 2019.
Language
English
Description
1 online resource (216 pages).
Item Number
10.1007/978-3-662-59
Call Number
QA274.75
Dewey Decimal Classification
519.2/33
Summary
This book is focused on the recent developments on problems of probability model uncertainty by using the notion of nonlinear expectations and, in particular, sublinear expectations. It provides a gentle coverage of the theory of nonlinear expectations and related stochastic analysis. Many notions and results, for example, G-normal distribution, G-Brownian motion, G-Martingale representation theorem, and related stochastic calculus are first introduced or obtained by the author. This book is based on Shige Pengs lecture notes for a series of lectures given at summer schools and universities worldwide. It starts with basic definitions of nonlinear expectations and their relation to coherent measures of risk, law of large numbers and central limit theorems under nonlinear expectations, and develops into stochastic integral and stochastic calculus under G-expectations. It ends with recent research topic on G-Martingale representation theorem and G-stochastic integral for locally integrable processes. With exercises to practice at the end of each chapter, this book can be used as a graduate textbook for students in probability theory and mathematical finance. Each chapter also concludes with a section Notes and Comments, which gives history and further references on the material covered in that chapter. Researchers and graduate students interested in probability theory and mathematical finance will find this book very useful.
Access Note
Access limited to authorized users.
Source of Description
Description based on print version record.
Series
Probability theory and stochastic modelling ; v. 95.
Available in Other Form
Linked Resources
Record Appears in