In this paper we consider stochastic optimization problems for an ambiguity averse decision maker who is uncertain about the parameters of the underlying process. In a first part we consider problems of optimal stopping under drift ambiguity for one-dimensional diffusion processes. Analogously to the case of ordinary optimal stopping problems for one-dimensional Brownian motions we reduce the problem to the geometric problem of finding the smallest majorant of the reward function in a two-parameter function space. In a second part we solve optimal stopping problems when the underlying process may crash down. These problems are reduced to one optimal stopping problem and one Dynkin game. Examples are discussed. \ua9 2013 Springer-Verlag Berl...
Abstract. We develop a novel framework for formulating a class of stochastic reachability problems w...
Consider a set of discounted optimal stopping problems for a one-parameter family of objective funct...
Abstract. We study stochastic motion planning problems which involve a controlled pro-cess, with pos...
In this paper we consider stochastic optimization problems for an ambiguity averse decision maker wh...
This paper studies the optimal stopping problem in the presence of model uncertainty (ambiguity). We...
This paper studies the optimal stopping problem in the presence of model uncertainty (ambiguity). We...
Cheng X, Riedel F. Optimal stopping under ambiguity in continuous time. Mathematics and Financial Ec...
Riedel F. Optimal Stopping under Ambiguity in Continuous Time. Working Papers. Institute of Mathemat...
Abstract. A new approach to the solution of optimal stopping problems for one-dimensional diffusions...
This paper studies the optimal stopping problem in the presence of model uncertainty (am-biguity). W...
This paper studies the optimal stopping problem in the presence of model uncertainty (ambiguity). We...
This thesis contains six papers on the topics of optimal stopping and stochastic games. Paper I ext...
The topic of this thesis is portfolio optimization under model ambiguity, i.e. a situation when the ...
This thesis deals with the explicit solution of optimal stopping problems with infinite time horizon...
This doctoral thesis consists of five research articles on the general topic of optimal decision mak...
Abstract. We develop a novel framework for formulating a class of stochastic reachability problems w...
Consider a set of discounted optimal stopping problems for a one-parameter family of objective funct...
Abstract. We study stochastic motion planning problems which involve a controlled pro-cess, with pos...
In this paper we consider stochastic optimization problems for an ambiguity averse decision maker wh...
This paper studies the optimal stopping problem in the presence of model uncertainty (ambiguity). We...
This paper studies the optimal stopping problem in the presence of model uncertainty (ambiguity). We...
Cheng X, Riedel F. Optimal stopping under ambiguity in continuous time. Mathematics and Financial Ec...
Riedel F. Optimal Stopping under Ambiguity in Continuous Time. Working Papers. Institute of Mathemat...
Abstract. A new approach to the solution of optimal stopping problems for one-dimensional diffusions...
This paper studies the optimal stopping problem in the presence of model uncertainty (am-biguity). W...
This paper studies the optimal stopping problem in the presence of model uncertainty (ambiguity). We...
This thesis contains six papers on the topics of optimal stopping and stochastic games. Paper I ext...
The topic of this thesis is portfolio optimization under model ambiguity, i.e. a situation when the ...
This thesis deals with the explicit solution of optimal stopping problems with infinite time horizon...
This doctoral thesis consists of five research articles on the general topic of optimal decision mak...
Abstract. We develop a novel framework for formulating a class of stochastic reachability problems w...
Consider a set of discounted optimal stopping problems for a one-parameter family of objective funct...
Abstract. We study stochastic motion planning problems which involve a controlled pro-cess, with pos...