Mastering GitHub Pages (Jekyll and GitHub Pages)

This lesson will help you create entirely free, easy-to-maintain, preservation-friendly, secure website over which you have full control, such as a scholarly blog, project website, or online portfolio.

Esta lección te ayudará a crear un sitio web seguro completamente gratuito, fácil de mantener y sobre el que tendrás control total, como un blog académico, un sitio web de proyectos o un portafolio en línea.

In this paper, we present an overview of the recent developments of functional quantization of stochastic processes, with an emphasis on the quadratic case. Functional quantization is a way to approximate a process, viewed as a Hilbert-valued random variable, using a nearest neighbour projection on a finite codebook. A special emphasis is made on the computational aspects and the numerical applications, in particular the pricing of some path-dependent European options.

Technology fails – at least sometimes. This is particularly true for a modern distributed research infrastructure, such as DARIAH-DE. For the operation of this infrastructure, we have implemented a monitoring solution with Icinga. This enables us to be informed about problems and react quickly.

We study a two armed-bandit algorithm with penalty. We show the convergence of the algorithm and establish the rate of convergence. For some choices of the parameters, we obtain a central limit theorem in which the limit distribution is characterized as the unique stationary distribution of a discontinuous Markov process.

We extend to Lipschitz continuous functionals either of the true paths or of the Euler scheme with decreasing step of a wide class of Brownian ergodic diffusions, the Central Limit Theorems formally established for their marginal empirical measure of these processes (which is classical for the diffusions and more recent as concerns their discretization schemes). We illustrate our results by simulations in connection with barrier option pricing.