Past

Mike Giles recently came up with a very general technique that improves the fundamental complexity of Monte Carlo simulation in the context where stochastic differential equations are simulated numerically. I will discuss some work with Mike Giles and Xuerong Mao that extends the theoretical support for this approach to the case of financial options without globally Lipschitz payoff functions. I will also suggest other application areas where this multi-level approach might prove valuable, including stochastic computation in cell biology.

New techniques in cell and molecular biology have produced huge advances in our understanding of signal transduction and cellular response in many systems, and this has led to better cell-level models for problems ranging from biofilm formation to embryonic development. However, many problems involve very large numbers of cells, and detailed cell-based descriptions are computationally prohibitive at present. Thus rational techniques for incorporating cell-level knowledge into macroscopic equations are needed for these problems. In this talk we discuss several examples that arise in the context of cell motility and pattern formation. We will discuss systems in which the micro-to-macro transition can be made more or less completely, and also describe other systems that will require new insights and techniques.

14.15 - 15.00 Part I

Marc Yor : The infinite horizon case.

15.00 - 15.15 A short break for questions and answers

15.15 - 16.00 Part II

Amel Bentata : The finite horizon case.

Roughly, the Black-Scholes formula is a distribution function of the maturity. This may be explained in terms of the last passage times at a given level of the underlying Brownian motion with drift.

Conversely, starting with last passage times up to finite horizon, we obtain a 2-parameter variant of the Black-Scholes formula.

The task is to compute orthogonal eigenvectors (without Gram-Schmidt) of symmetric tridiagonals for isolated clusters of close eigenvalues. We review an "old" method, the Submatrix method, and describe an extension which significantly enlarges the scope to include several mini-clusters within the given cluster. An essential feature is to find the envelope of the associated invariant subspace.

In a financial market, the appreciate rates are very difficult to estimate precisely, and in general only some confidence interval will be estimated. This paper is devoted to the portfolio selection with the appreciation rates being in a certain closed convex set rather than some precise point. We study the problem in both expected utility framework and mean-variance framework, and robust solutions are given explicitly in both frameworks.

I will discuss some theorems of Chatzidakis, van den Dries, and Macintyre on definable sets over finite fields (Crelle 1992). This includes a geometric decomposition theorem for definable sets and a generalization of the Lang-Weil estimates, and uses model theory of finite and pseudo-finite fields.

If time permits, I shall mention a recent application of this work by Emmanuel Kowalski on new bounds for exponential sums (Israel Journal of Math 2007).

I would also like to mention some connections to the model theory of p-adic and motivic integrals and to general problems on counting and equidistribution of rational points.

I plan to discuss some aspects the mysterious relationship between the symmetries of toroidal compactifications of M-theory and helices on del Pezzo surfaces.