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20072026
most citedPractical heteroskedastic Gaussian process modeling for large simulation experiments

184 citations · 540 across the 36 of their papers we have counts for

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7 papers · 1 filter

math.OC2019★ 1 cited

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…

math.OC2019★ 14 cited

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…

math.OC2012

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…

math.OC2011★ 19 cited

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…

math.OC2010

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…

math.OC2008★ 49 cited

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…