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In this book, we introduce a new approach of sublinear expectation to deal with the problem of probability and distribution model uncertainty. We a new type of (robust) normal distributions and the related central limit theorem under…

Probability · Mathematics 2010-02-25 Shige Peng

We introduce a notion of nonlinear expectation --G--expectation-- generated by a nonlinear heat equation with infinitesimal generator G. We first discuss the notion of G-standard normal distribution. With this nonlinear distribution we can…

Probability · Mathematics 2007-05-23 Shige Peng

We develop a notion of nonlinear expectation --G-expectation-- generated by a nonlinear heat equation with infinitesimal generator G. We first study multi-dimensional G-normal distributions. With this nonlinear distribution we can introduce…

Probability · Mathematics 2007-05-23 Shige Peng

We describe a new framework of a sublinear expectation space and the related notions and results of distributions, independence. A new notion of G-distributions is introduced which generalizes our G-normal-distribution in the sense that…

Probability · Mathematics 2008-03-19 Shige Peng

Based on law of large numbers and central limit theorem under nonlinear expectation, we introduce a new method of using G-normal distribution to measure financial risks. Applying max-mean estimators and small windows method, we establish…

Mathematical Finance · Quantitative Finance 2021-07-28 Shige Peng , Shuzhen Yang

G-Brownian motion has a very rich and interesting new structure which nontrivially generalizes the classical one. Its quadratic variation process is also a continuous process with independent and stationary increments. We prove a…

Probability · Mathematics 2020-05-08 Li-Xin Zhang

The law of large numbers (LLN) and central limit theorem (CLT) are long and widely been known as two fundamental results in probability theory. Recently problems of model uncertainties in statistics, measures of risk and superhedging in…

Probability · Mathematics 2007-05-23 Shige Peng

The sub-linear expectation or called G-expectation is a nonlinear expectation having advantage of modeling non-additive probability problems and the volatility uncertainty in finance. Let $\{X_n;n\ge 1\}$ be a sequence of independent random…

Probability · Mathematics 2016-08-03 Li-Xin Zhang

The classical law of the iterated logarithm (LIL for short)as fundamental limit theorems in probability theory play an important role in the development of probability theory and its applications. Strassen (1964) extended LIL to large…

Probability · Mathematics 2021-07-02 Panyu Wu , Zengjing Chen

We introduce a notion of volatility uncertainty in discrete time and define the corresponding analogue of Peng's G-expectation. In the continuous-time limit, the resulting sublinear expectation converges weakly to the G-expectation. This…

Probability · Mathematics 2011-03-04 Yan Dolinsky , Marcel Nutz , H. Mete Soner

In this paper we give some basic and important properties of several typical Banach spaces of functions of $G$-Brownian motion pathes induced by a sublinear expectation--G-expectation. Many results can be also applied to more general…

Probability · Mathematics 2010-01-15 Laurent Denis , Mingshang Hu , Shige Peng

In this paper, we consider the stochastic optimal control problems under model risk caused by uncertain volatilities. To have a mathematical consistent framework we use the notion of G-expectation and its corresponding G-Brwonian motion…

Optimization and Control · Mathematics 2014-04-18 Zhongyang Sun , Xin Zhang , Junyi Guo

We investigate financial markets under model risk caused by uncertain volatilities. For this purpose we consider a financial market that features volatility uncertainty. To have a mathematical consistent framework we use the notion of…

Pricing of Securities · Quantitative Finance 2010-12-16 Joerg Vorbrink

The $G$-expectation framework is a generalization of the classical probabilistic system motivated by Knightian uncertainty, where the $G$-normal plays a central role. However, from a statistical perspective, $G$-normal distributions look…

Probability · Mathematics 2021-10-19 Yifan Li , Reg Kulperger , Hao Yu

In this paper we consider a sequence of random variables with mean uncertainty in a sublinear expectation space. Without the hypothesis of identical distributions, we show a new central limit theorem under the sublinear expectations.

Probability · Mathematics 2015-05-19 Min Li , Yufeng Shi

In this paper, we consider the stochastic optimal control problems under G-expectation. Based on the theory of backward stochastic differential equations driven by G-Brownian motion, which was introduced in [10.11], we can investigate the…

Probability · Mathematics 2013-08-19 Zhonghao Zheng , Xiuchun Bi , Shuguang Zhang

In this paper, we study the pricing of contracts in fixed income markets under volatility uncertainty in the sense of Knightian uncertainty or model uncertainty. The starting point is an arbitrage-free bond market under volatility…

Pricing of Securities · Quantitative Finance 2021-11-09 Julian Hölzermann

In this paper, we consider the sublinear expectation on bounded random variables. With the notion of uncorrelatedness for random variables under the sublinear expectation, a weak law of large numbers is obtained. With the notion of…

Probability · Mathematics 2023-11-17 Wenhao Li , Chuanfeng Sun

The objective of this paper is to derive a representation of symmetric G-martingales as stochastic integrals with respect to the G-Brownian motion. For this end, we first study some extensions of stochastic calculus with respect to…

Probability · Mathematics 2010-03-17 Qian Lin

Model uncertainty is a type of inevitable financial risk. Mistakes on the choice of pricing model may cause great financial losses. In this paper we investigate financial markets with mean-volatility uncertainty. Models for stock markets…

Pricing of Securities · Quantitative Finance 2014-07-31 Yuhong Xu
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