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Nonlinear Expectations and Stochastic Calculus under Uncertainty

with Robust CLT and G-Brownian Motion

Shige Peng

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Springer Berlin Heidelberg img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik

Beschreibung

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 Peng’s 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.

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Schlagwörter

G-Brownian motion, stochastic differential equations driven by G-Brownian motion, quantitative finance, stochastic analysis, central limit theorem, G-martingale representation theorem, maximal distribution, probability theory, stochastic integral of G-Brownian motion, uncertainty of probabilities, law of large numbers, G-martingale, G-normal distribution, nonlinear Feynman-Kac formula, mathematical statistics, quadratic variation process of G-Brownian motion, nonlinear expectations, independence and identical distribution under uncertainty