We consider a dynamic pricing model, in which a population of customers can change contracts at any time depending on pricing conditions and customer-specific characteristics such as inertia (propensity to ...
We consider a dynamic pricing model, in which a population of customers can change contracts at any time depending on pricing conditions and customer-specific characteristics such as inertia (propensity to ...
In this work, we derive a probabilistic forecast of the solar irradiance during a day at a given location, using a stochastic differential equation (SDE for short) model. We propose ...
We study an islanded microgrid system designed to supply a small village with the power produced by photovoltaic panels, wind turbines and a diesel generator. A battery storage system device ...
In this article, we use the mean variance hedging criterion to value contracts in incomplete markets. Although the problem is well studied in a continuous and even discrete framework, very ...
Based on empirical evidence of fast mean-reverting spikes, we model electricity price processes as the sum of a continuous Itö semimartingale and a a mean-reverting compound Poisson process. In a first part, ...
Kernel density estimation and kernel regression are powerful but computationally expensive techniques: a direct evaluation of kernel density estimates at M evaluation points given N input sample points requires a ...
We extend a recently developed method to solve semi-linear PDEs to the case of a degenerated diffusion. Being a pure Monte Carlo method it does not suer from the so ...
S. Goutte, N. Oudjane, F. Russo à paraître dans Journal of Computational Finance Juin 2012