184 citations · 540 across the 36 of their papers we have counts for
7 papers · 1 filter
A Machine Learning Approach to Adaptive Robust Utility Maximization and Hedging
Tao Chen, Michael Ludkovski
We investigate the adaptive robust control framework for portfolio optimization and loss-based hedging under drift and volatility uncertainty. Adaptive robust problems offer many a…
Statistical Learning for Probability-Constrained Stochastic Optimal Control
Alessandro Balata, Michael Ludkovski, Aditya Maheshwari +1
We investigate Monte Carlo based algorithms for solving stochastic control problems with probabilistic constraints. Our motivation comes from microgrid management, where the contro…
Inventory Management with Partially Observed Nonstationary Demand
Erhan Bayraktar, Mike Ludkovski
We consider a continuous-time model for inventory management with Markov modulated non-stationary demands. We introduce active learning by assuming that the state of the world is u…
Finite Horizon Decision Timing with Partially Observable Poisson Processes
Michael Ludkovski, Semih Sezer
We study decision timing problems on finite horizon with Poissonian information arrivals. In our model, a decision maker wishes to optimally time her action in order to maximize he…
Stochastic Switching Games and Duopolistic Competition in Emissions Markets
Michael Ludkovski
We study optimal behavior of energy producers under a CO_2 emission abatement program. We focus on a two-player discrete-time model where each producer is sequentially optimizing h…
Optimal Risk Sharing under Distorted Probabilities
M. Ludkovski, V. R. Young
We study optimal risk sharing among agents endowed with distortion risk measures. Our model includes market frictions that can either represent linear transaction costs or risk…