Statistics Seminars: Ergodic BSDEs and risk averse networks
3 February 2014 14:00 in CM221
When studying a financial network, one is often interested in the importance of a particular node. This can be measured in various ways, for example, by the ergodic probabilities of an associated Markov chain. We consider ergodic BSDEs based on countable state Markov chains, and use these to derive nonlinear, risk-averse versions of these probabilities and similar quantities. With this machinery, one can also consider various problems in ergodic stochastic control, and can incorporate model or statistical uncertainties into the assessment of the importance of different nodes and groups of nodes.
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