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Nonlinear Expectations and Stochastic Calculus under Uncertainty

with Robust CLT and G-Brownian Motion

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  • 228 pages
  • 8 hours of reading

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Focusing on recent advancements in probability model uncertainty, this book explores nonlinear expectations, especially sublinear expectations. It offers a comprehensive introduction to the theory of nonlinear expectations and stochastic analysis. Key concepts such as G-normal distribution, G-Brownian motion, and the G-Martingale representation theorem are introduced, providing readers with foundational knowledge in these areas of stochastic calculus.

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Nonlinear Expectations and Stochastic Calculus under Uncertainty, Shige Peng

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Released
2020
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