My main research interest is on problems in the intersection between operations research and finance, and specifically on problems of decision-making under uncertainty in financial markets. The methodological base of my research is in the field of stochastic optimization, and specifically stochastic programming, dynamic programming and approximate dynamic programming/reinforcement learning.
The aim of my research is to support improved decisions in practice through the study of practically relevant applications as well as through methodological contributions in the field of stochastic optimization. Examples of applications in my work are in financial risk management and portfolio choice in the presence of transaction costs. My work on methodological aspects of stochastic optimization includes scenario generation through importance sampling and the study of multi-stage stochastic programming models.
Background
I hold a PhD in Financial Mathematics from the division of Production Economics at Linköping University, and master degrees in Industrial Engineering and Management as well as Economics. I have been a visiting PhD student at Chicago Booth School of Business.