Optimization of Risk Measures
Alexander Shapiro
Industrial and Systems Engineering, Georgia Tech.
| Time:
01:00pm - 02:00pm |
Location: MP 401 |
Abstract:
Mean-risk approach to optimization under uncertainty is going back to the pioneering work of
Markowitz (1952) and is routinely used in portfolio selections. More recently an axiomatic approach
to the mean-risk analysis was suggested by Artzner et al (1999), which started an intensive
development of a mathematical theory of risk measures. In this talk we discuss the mean-risk
methodology from an optimization point of view. We show that the min-max, utility and mean-risk
approaches to stochastic optimization, in a sense, are equivalent to each other. We also formulate
mean-risk measures in a multi-stage setting and derive dynamic programming type equations.
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