93 research outputs found
Some non monotone schemes for Hamilton-Jacobi-Bellman equations
We extend the theory of Barles Jakobsen to develop numerical schemes for
Hamilton Jacobi Bellman equations. We show that the monotonicity of the schemes
can be relaxed still leading to the convergence to the viscosity solution of
the equation. We give some examples of such numerical schemes and show that the
bounds obtained by the framework developed are not tight. At last we test some
numerical schemes.Comment: 24 page
Optimal Liquidity Management and Hedging in the presence of a non predictable investment opportunity
In this paper, we develop a dynamic model that captures the interaction between the cash reserves, the risk management policy and the profitability of a non-predictable irreversible investment opportunity. We consider a firm that has assets in place generating a stochastic cash- ow stream. The firm has a non-predictable growth opportunity to expand its operation size by paying a sunk cost. When the opportunity is available, the firm can finance it either by cash or by costly equity issuance. We provide an explicit characterization of the firm strategy in terms of investment, hedging, equity issuance and dividend distribution.
A Probabilistic Numerical Method for Fully Nonlinear Parabolic PDEs
We consider the probabilistic numerical scheme for fully nonlinear PDEs
suggested in \cite{cstv}, and show that it can be introduced naturally as a
combination of Monte Carlo and finite differences scheme without appealing to
the theory of backward stochastic differential equations. Our first main result
provides the convergence of the discrete-time approximation and derives a bound
on the discretization error in terms of the time step. An explicit
implementable scheme requires to approximate the conditional expectation
operators involved in the discretization. This induces a further Monte Carlo
error. Our second main result is to prove the convergence of the latter
approximation scheme, and to derive an upper bound on the approximation error.
Numerical experiments are performed for the approximation of the solution of
the mean curvature flow equation in dimensions two and three, and for two and
five-dimensional (plus time) fully-nonlinear Hamilton-Jacobi-Bellman equations
arising in the theory of portfolio optimization in financial mathematics
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