MARKET MAKING AND PORTFOLIO LIQUIDATION UNDER UNCERTAINTY

Robustness-based portfolio optimization under epistemic uncertainty

In this paper, we propose formulations and algorithms for robust portfolio optimization under both aleatory uncertainty (i.e., natural variability) and epistemic uncertainty (i.e., imprecise probabilistic information) arising from interval data. Epistemic uncertainty is represented using two approaches: (1) moment bounding approach and (2) likelihood-based approach. This paper first proposes a ...

Market segmentation under uncertainty

This paper proposes a general model to value different strategies to enter a market, comparing alternative sequential segmentation paths to simultaneous investment in all segments. This general model also allows demand to evolve accordingly to an endogenous regimeswitching process, under which it can behave differently before and after investment. It is shown how uncertainty, revenues and inves...

Decision making under uncertainty

Decision making under uncertainty

1 Laboratory of Computational Neuroscience, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland 2 Laboratoire de Recherché en Neuroimagerie, Le Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland 3 Information Processing and Economic Decision Making, Department of Psychology, Universität Konstanz, Konstanz, Germany 4 Economic Psychology, Department of Psychology, Univers...

Optimal Liquidation Strategies Regularize Portfolio Selection

We consider the problem of portfolio optimization in the presence of market impact, and derive optimal liquidation strategies. We discuss in detail the problem of finding the optimal portfolio under Expected Shortfall (ES) in the case of linear market impact. We show that, once market impact is taken into account, a regularized version of the usual optimization problem naturally emerges. We cha...