DH 3rd floor SR

We develop a methodology to optimally design a financial issue to hedge

non-tradable risk on financial markets.The modeling involves a minimization

of the risk borne by issuer given the constraint imposed by a buyer who

enters the transaction if and only if her risk level remains below a given

threshold. Both agents have also the opportunity to invest all their residual

wealth on financial markets but they do not have the same access to financial

investments. The problem may be reduced to a unique inf-convolution problem

involving some transformation of the initial risk measures.

The question whether the measure of a Levy process starting from x>0 and "conditioned to stay positive" converges to the corresponding obiect for x=0 when x tends to 0 is rather delicate. I will describe work with Loic Chaumont which settles this question, essentially in all cases of interest. As an application, I will show how to use this result and excursion theory to give simpler proofs of some recent results about the exit problem for reflected processe derived from spectrally one-sided Levy processes due to Avram. Kyprianou and Pistorius.

We formulate a problem of super-hedging under gamma constraint by

taking the portfolio process as a controlled state variable. This

leads to a non-standard stochastic control problem. An intuitive

guess of the associated Bellman equation leads to a non-parabolic

PDE! A careful analysis of this problem leads to the study of the

small time behaviour of double stochastic integrals. The main result

is a characterization of the value function of the super-replication

problem as the unique viscosity solution of the associated Bellman

equation, which turns out to be the parabolic envelope of the above

intuitive guess, i.e. its smallest parabolic majorant. When the

underlying stock price has constant volatility, we obtain an

explicit solution by face-lifting the pay-off of the option.

The Brownian snake (with lifetime given by a normalized

Brownian excursion) arises as a natural limit when studying random trees. This

may be used in both directions, i.e. to obtain asymptotic results for random

trees in terms of the Brownian snake, or, conversely, to deduce properties of

the Brownian snake from asymptotic properties of random trees. The arguments

are based on Aldous' theory of the continuum random tree.

I will discuss two such situations:

1. The Wiener index of random trees converges, after

suitable scaling, to the integral (=mean position) of the head of the Brownian

snake. This enables us to calculate the moments of this integral.

2. A branching random walk on a random tree converges, after

suitable scaling, to the Brownian snake, provided the distribution of the

increments does not have too large tails. For i.i.d increments Y with mean 0,

a necessary and sufficient condition is that the tails are o(y^{-4}); in

particular, a finite fourth moment is enough, but weaker moment conditions are

not.

The celebrated Levy-Khintchine formula provides us an explicit

structure of Levy processes on $R^d$. In this talk I shall present a

structure result for quasi-regular semi-Dirichlet forms, i.e., for

those semi-Dirichlet forms which are associated with right processes

on general state spaces. The result is regarded as an extension of

Levy-Khintchine formula in semi-Dirichlet forms setting. It can also

be regarded as an extension of Beurling-Deny formula which is up to

now available only for symmetric Dirichlet forms.