Navigating the uncertainty landscape
Using probability theory and stochastic analysis to understand and predict the behaviour of complex systems, from financial markets to physical systems
About
Probability theory analyses random events and the mathematical rules that govern their outcome.
Stochastic analysis is the branch of probability theory focusing on the study of random phenomena driven by a random process, such as Brownian motion, using stochastic calculus, for example Itô’s or Malliavin calculus.
At DMATH, we use the full strength of probability theory and stochastic analysis to understand and predict the behaviour of complex systems, ranging from financial markets to physical systems.
The following scientist contribute to the research in this area: Yannick Baraud, Ivan Nourdin, Giovanni Peccati, Mark Podolskij
