2. Abstract  The volatility ambiguity is a major model of risk in Black-Scholes pricing formula.  We will study, from the point of view of a supervising angent, how to provide a coherent and dynamic monetory risk measure for margin requirements of a composition of different types of risky positions.

3.  Theoretically, we have devoloped a new notion sublinear, or coherent, expectation --G-Expenctation derived by a nonlinear heat equation. Random variables with G-normal distributions are then defined and, accordingly, we introduce the so-called G-normal Brownian.  We then establish the related stochastic calculus, especially stochastic integrals of Itô's type with respect to a G-Brownian motion and derive the related Itô's formula. We have also proved the existence and uniqueness of stochastic differential equation under this new stochastic calculus.

4.  The whole framework is out of Wiener probability measure based on the foundation of probability theory established by Kolmogorov 1933.  It is in fact a new theory of nonlinear probability. Moreover, the above Wiener probability space as well as many other types of spaces of risk measures, or sublinear expectations, can be treated universally in our new framework.

5.  Practically, we have developed an algorithm for the numerical calculation of G-expectation generalied the well-known risk measure SPAN (System of Portfolio Analysis) to a dynamically consistent risk measure.

6. (g – Expectation) Model without Ambiguity

11.  To use the language of the nonlinear expectation, instead of probability 1933 Foundation of Prob. Kolmogorov 1918-1921 1925 Daniell Wiener Sublinear expextation Interagal Wiener measure Coherent Risk Measure

13. Workshop 3 talks: 2006

14. Random Variable Space of Lipschitz functions

15. [Lyons1995AMF] Uncertain volatility and the risk free synthesis of derivatives.

18. Coherent Risk Measure

29. (Bounded)