STORM - Stochastics for Time-Space Risk Models
A Toppforsk project funded by the Norwegian Research Council in cooperation with the University of Oslo.
About the project
Phenomena that evolve in time and spread in space are overall, sourced by nature, intrinsic in life, generated by human technology and construction. Whether engendered by unknown past causes, present evaluations, or future unexpected events, randomness is a reality and it has to be properly dealt with. The overall goal in our research is to formulate and solve the key problems in stochastic modelling, analysis, and control of space-time random phenomena featuring structures well beyond the traditional.
To understand the significance of STORM we resort to illustrative examples from the energy production and markets, where the role of renewable resources is nowadays of the foremost importance. These resources depend on weather conditions: wind, cloud cover, precipitation, and temperatures, which introduce uncertainty in the production side. These environmental risk factors are clearly characterised by time-space dependences and show features that are well beyond the traditional structures: e.g. non-Gaussianity, non-Markovianity, non-semimartingality, fat-tails, jumps, and spikes. These influence the stream of production and electricity prices. STORM aims at providing a coherent framework to treat flexible classes of models able to accommodate the different features detected. For this we shall use the stochastic analysis of random fields and study problems of stochastic control, risk measurement, filtering.
STORM takes up the challenge of dealing with these unconventional models. The results will be of universal mathematical nature with wide applicability, covering not only energy, but also biology and life science, where the stylized features mentioned above are also detected.