no code implementations • 19 May 2022 • William Lefebvre, Grégoire Loeper, Huyên Pham
Compared to existing methods, the addition of a differential loss function associated to the gradient, and augmented training sets with Malliavin derivatives of the forward process, yields a better estimation of the PDE's solution derivatives, in particular of the second derivative, which is usually difficult to approximate.
no code implementations • 19 Feb 2021 • William Lefebvre, Enzo Miller
We consider a class of stochastic control problems with a delayed control, both in drift and diffusion, of the type dX t = $\alpha$ t--d (bdt + $\sigma$dW t).
Optimization and Control Probability Computational Finance
no code implementations • 17 Sep 2020 • William Lefebvre, Gregoire Loeper, Huyên Pham
Such consideration is motivated as follows: (i) On the one hand, it is a way to robustify the mean-variance allocation in case of misspecified parameters, by "fitting" it to a reference portfolio that can be agnostic to market parameters; (ii) On the other hand, it is a procedure to track a benchmark and improve the Sharpe ratio of the resulting portfolio by considering a mean-variance criterion in the objective function.
