Stochastic Calculus Under Sublinear Expectation And Volatility Uncertainty

Research Paper (postgraduate) from the year 2017 in the subject Mathematics - Stochastics, grade: 1,7, LMU Munich, language: English, abstract: Detailed results of stochastic calculus under probability model uncertainty have been proven by Shige Peng. At first, we give some basic properties of sublinear expectation E. One can prove that E has a representaion as the Supremum of a specific set of well known linear expectation. P is called uncertainty set and characterizes the probability model uncertainty. Based on the results of Hu and Peng ([HP09]) we prove that P is a weakly compact set of probability measures. Based on the work of Peng et. Al. we give the definition and properties of maximal distribution and G-normal Distribution. Furthermore, G-Brownian motion and its corresponding G-expectation will be constructed. Briefly speaking, a G -Brownian motion (Bt)t>=0 is a continuous process with independent and stationary increments under a given sublinear expectation E. In this work, we use the results in [LP11] and study Ito's integral of a step process ?. Ito's integral with respect to G-Brownian motion is constructed for a set of stochastic processes which are not necessarily quasi-continuous. Ito's integral will be defined on an interval [0, t ] where t is a stopping time. This allows us to define Ito's integral on a larger space. Finally, we give a detailed proof of Ito's formula for stochastic processes.

• | Author: Christian Bannasch
• | Publisher: Grin Verlag
• | Publication Date: Feb 05, 2020
• | Number of Pages: 68 pages
• | Language: English
• | Binding: Paperback
• | ISBN-10: 3346105253
• | ISBN-13: 9783346105257