most citedMarkov Decision Processes with Recursive Risk Measures

27 citations · 63 across the 4 of their papers we have counts for

collaborators

5 papers

q-fin.RM2020

Dynamic Reinsurance in Discrete Time Minimizing the Insurer's Cost of Capital

Alexander Glauner

In the classical static optimal reinsurance problem, the cost of capital for the insurer's risk exposure determined by a monetary risk measure is minimized over the class of reinsu…

math.OC2020★ 18 cited

Minimizing Spectral Risk Measures Applied to Markov Decision Processes

Nicole Bäuerle, Alexander Glauner

We study the minimization of a spectral risk measure of the total discounted cost generated by a Markov Decision Process (MDP) over a finite or infinite planning horizon. The MDP i…

math.OC2020★ 27 cited

Markov Decision Processes with Recursive Risk Measures

Nicole Bäuerle, Alexander Glauner

In this paper, we consider risk-sensitive Markov Decision Processes (MDPs) with Borel state and action spaces and unbounded cost under both finite and infinite planning horizons. O…

math.OC2020★ 18 cited

Distributionally Robust Markov Decision Processes and their Connection to Risk Measures

Nicole Bäuerle, Alexander Glauner

We consider robust Markov Decision Processes with Borel state and action spaces, unbounded cost and finite time horizon. Our formulation leads to a Stackelberg game against nature.…

q-fin.RM2017

Optimal Risk Allocation in Reinsurance Networks

Nicole Bäuerle, Alexander Glauner

In this paper we consider reinsurance or risk sharing from a macroeconomic point of view. Our aim is to find socially optimal reinsurance treaties. In our setting we assume that th…