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Journal ArticleDOI

Uncertain volatility and the risk-free synthesis of derivatives

TLDR
In this paper, the authors introduce optimal and risk-free strategies for intermediaries in a multidimensional frictionless security market to meet their obligations when the volatility is unknown, and is only assumed to lie in some convex region depending on the prices of the underlying securities and time.
Abstract
To price contingent claims in a multidimensional frictionless security market it is sufficient that the volatility of the security process is a known function of price and time. In this note we introduce optimal and risk-free strategies for intermediaries in such markets to meet their obligations when the volatility is unknown, and is only assumed to lie in some convex region depending on the prices of the underlying securities and time. Our approach is underpinned by the theory of totally non-linear parabolic partial differential equations (Krylov and Safanov, 1979; Wang, 1992) and the non-stochastic approach to Ito's formation first introduced by Follmer (1981a,b). In these more general conditions of unknown volatility, the optimal risk-free trading strategy will, necessarily, produce an unpredictable surplus over the minimum assets required at any time to meet the liabilities. This surplus, which could be released to the intermediary or to the client, is not required to meet the contingent claim. One s...

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Book ChapterDOI

Towards a Theory of Volatility Trading

Peter Carr, +1 more
Abstract: White, and especially Robert Jarrow for useful discussions. They are not responsible for any errors.
Book ChapterDOI

G -Expectation, G -Brownian Motion and Related Stochastic Calculus of Itô Type

TL;DR: In this article, the authors introduce a nonlinear expectation generated by a heat equation with infinitesimal generator G. The G-standard normal distribution is introduced and the canonical process is a G-Brownian motion.
Posted Content

Nonlinear Expectations and Stochastic Calculus under Uncertainty

Shige Peng
- 24 Feb 2010 - 
TL;DR: In this paper, a new approach of sublinear expectation is introduced to deal with the problem of probability and distribution model uncertainty, and a new type of normal distributions and the related central limit theorem under sublinear expectations are presented.
Journal ArticleDOI

Function Spaces and Capacity Related to a Sublinear Expectation: Application to G -Brownian Motion Paths

TL;DR: In this article, the authors give some basic and important properties of typical Banach spaces of functions of G-Brownian motion paths induced by a sublinear expectation, which can be applied in continuous time dynamic and coherent risk measures in finance, in particular for path-dependence risky positions under situations of volatility model uncertainty.
Journal ArticleDOI

Multi-dimensional G-Brownian motion and related stochastic calculus under G-expectation

TL;DR: In this article, a notion of nonlinear expectation generated by a nonlinear heat equation with infinitesimal generator G is introduced, and the canonical process is a multi-dimensional G-Brownian motion.
References
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Journal ArticleDOI

The Pricing of Options and Corporate Liabilities

TL;DR: In this paper, a theoretical valuation formula for options is derived, based on the assumption that options are correctly priced in the market and it should not be possible to make sure profits by creating portfolios of long and short positions in options and their underlying stocks.
Book

Stochastic processes

J. L. Doob, +1 more
Book

Stochastic differential equations and diffusion processes

TL;DR: In this article, Stochastic Differential Equations and Diffusion Processes are used to model the diffusion process in stochastic differential equations. But they do not consider the nonlinearity of diffusion processes.
Journal ArticleDOI

Martingales and stochastic integrals in the theory of continuous trading

TL;DR: In this paper, a general stochastic model of a frictionless security market with continuous trading is developed, where the vector price process is given by a semimartingale of a certain class, and the general Stochastic integral is used to represent capital gains.
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