This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. The underlying concept is to use randomness to solve problems that might be deterministic in principle. They are often used in physical and mathematical problems and are most useful when it is difficult or impossible to use other approaches. Monte Carlo methods are mainly used in three problem classes: optimization, numerical integration, and generating draws from a probability distribution.
The search for a market design that ensures stable bank funding is at the top of regulators' policy agenda. This paper empirically shows that the central counterparty (CCP)-based euro interbank repo m
We introduce a novel class of term structure models for variance swaps. The multivariate state process is characterized by a quadratic diffusion function. The variance swap curve is quadratic in the s
Elsevier2016
The evaluation of scientific research is crucial for both the academic community and society as a whole. Numerous bibliometric indices have been proposed for the ranking of research performance, mainl