4 papers
Learning Contraction Policies from Offline Data
Navid Rezazadeh, Maxwell Kolarich, Solmaz S. Kia +1
This paper proposes a data-driven method for learning convergent control policies from offline data using Contraction theory. Contraction theory enables constructing a policy that…
Decision making with dynamic probabilistic forecasts
Peter Tankov, Laura Tinsi
We consider a sequential decision making process, such as renewable energy trading or electrical production scheduling, whose outcome depends on the future realization of a random…
Price formation and optimal trading in intraday electricity markets with a major player
Olivier Féron, Peter Tankov, Laura Tinsi
We study price formation in intraday electricity markets in the presence of intermittent renewable generation. We consider the setting where a major producer may interact strategic…
Price formation and optimal trading in intraday electricity markets
Olivier Féron, Peter Tankov, Laura Tinsi
We develop a tractable equilibrium model for price formation in intraday electricity markets in the presence of intermittent renewable generation. Using stochastic control theory,…