4 papers
Wasserstein Distributionally Robust Regret Optimization
Lukas-Benedikt Fiechtner, Jose Blanchet
Distributionally robust optimization (DRO) is widely used for decision-making under uncertainty, but its adversarial focus on worst-case loss can lead to overly conservative polici…
Optimal Online and Offline Algorithms for Contextual MNL with Applications to Assortment and Pricing
Yunfan Zhang, Yuxuan Han, Hongyu Shan +2
Selecting which products to display and at what prices is a central decision in retail and e-commerce operations. In many applications, these two choices must be made jointly under…
Distributionally Robust Regret Optimal LQR with Common Stage-Law Ambiguity
Lukas-Benedikt Fiechtner, Jose Blanchet
We study, to our knowledge, the first tractable multistage ex-ante distributionally robust regret optimization (DRRO) formulation for stochastic control. We consider finite-horizon…
Bayesian Distributionally Robust Merton Problem with Nonlinear Wasserstein Projections
Jose Blanchet, Jiayi Cheng, Hao Liu +1
We revisit Merton's continuous-time portfolio selection through a data-driven, distributionally robust lens. Our aim is to tap the benefits of frequent trading over short horizons…