Stochastic Approaches for Forecasting and Hedging in Energy Markets

Starting date
December 1, 2016
Duration (months)
24
Departments
Computer Science
Managers or local contacts
Di Persio Luca

This project aims at exploiting recent techniques within the stochastic analysis framework, to obtain insights concerning future behavior of energy markets. Forecasted methods based on rigorous modelization of suitable stochastic partial differential equations, driven by compounded Poisson processes, will be taken into consideration.

Sponsors:

Beefree srl
Funds: assigned and managed by the department

Project participants

Luca Di Persio
Temporary Assistant Professor

Activities

Research facilities