Title: Reflections on robustness in stochastic programs with risk constraints
Speaker: Dr. Milos Kopa
Affiliation: Department of Probability and Mathematical Statistics – Charles University in Prague
Location: Room 301 William Penney
Time: 3:00pm
Abstract. This paper is a contribution to the robustness analysis for stochastic programs whose set of feasible solutions depends on the probability distribution P. For various reasons, probability distribution P may not be precisely specified and we study robustness of results with respect to perturbations of P. The main tool is the contamination technique. For the optimal value, local contamination bounds are derived and applied to robustness analysis of the optimal value of a portfolio performance under risk-shaping constraints. To illustrate the theoretical results, numerical examples for several mean-risk models are presented. Finally, under suitable conditions on the structure of the problem and for discrete distributions we shall suggest a new robust portfolio efficiency test with respect to the first (second) order stochastic dominance criterion and we shall exploit the contamination technique to analyze the resistance with respect to additional scenarios.
About the speaker. Dr. Milos Kopa is an assistant professor at Charles University in Prague. He received his Ph.D. degree in Econometrics and Operations research in 2006 (supervisor: Prof. Jitka Dupacova, Charles University in Prague).
He is a member of several scientific societies: Stochastic Programming Community, EURO working group on financial modelling, EUROPT. Recently he has become an elected member (and secretary) of Managerial Board of new EURO working group on stochastic programming. He is vice-head of the Center of Excellence “Dynamic models in economics” that comprises about 40 leading researchers (in quantitative economics and finance) from Czech Republic.
The research of Milos Kopa is focused on: stochastic programming theory and applications, especially financial applications. In recent years he has published several papers dealing with portfolio efficiency with respect to stochastic dominance criteria; data envelopment analysis and its relation to stochastic dominance; robustness (contamination) in stochastic programs with risk constraints, etc.