Experienced Researcher - 1 for the project Non-Gaussian self-similar processes

At the Bucharest University of Economic Studies, the position of an Experienced Researcher with 12,50% of the regular working time is to be filled as soon as possible, for the project Non-Gaussian self-similar processes : Enhancing mathematical tools and financial models for capturing complex market dynamics .

Assets, principal investigator Prof. Dr. Ciprian Andrei Tudor. The position is limited until 30/06/2026.

Applicants with a solid practical experience in statistics and stochastic modeling with applicability in microeconomics, macroeconomie and sustainability are particularly welcome, Experience in previous similar projects will be considered a major advantage.

You should have a university degree at PhD level in the field of economics or similar with above-average success.

Our team offers flexible working hours and intensive cooperation in a committed team.

The application deadline is Mars 18, 2024. If you have any questions, please contact Maria Cristina Pădure (cristina.padure@ase.ro).  

You can find more details below, as well a short presentation of the project.

Non-Gaussian self-similar processes : Enhancing mathematical tools and financial models for capturing complex market dynamics  - presentation

The proposal concerns a particular class of self-similar stochastic processes, the so-called Hermite processes. Self-similar processes are stochastic processes that are invariant in distribution under a suitable time scaling. The purpose is to offer a deeper analysis of this class of stochastic processes concerning their stochastic and statistical analysis and to propose some non-Gaussian stochastic models, based on (generalized) Hermite processes in mathematical finance. Traditional financial models often rely on the simplifying assumption of Gaussian (normal) distributions, despite the fact that financial data frequently exhibits complexities that cannot be fully captured by such assumptions. We believe that the Hermite processes and some related self-similar stochastic processes can offer a viable alternative for modelling purposes. We actually intend to develop a strong theoretical component based on the systemic study of stochastic models with Hermite random perturbation and also with a significant practical part, related to the effective computation of the data and numerical simulation.