This paper studies the dynamic portfolio choice problem with ambiguous jump risks in a multidimensional jump-diffusion framework. We formulate a continuoustime model of incomplete market with ...

IEMS 469: Dynamic Programming VIEW ALL COURSE TIMES AND SESSIONS Prerequisites Basic knowledge of probability (random variables, expectation, conditional probability), optimization (gradient), ...

Many sequential decision problems can be formulated as Markov decision processes (MDPs) where the optimal value function (or cost-to-go function) can be shown to satisfy a monotone structure in some ...

Dynamic Programming and Optimal Control Dynamic Programming and Optimal Control is offered within DMAVT and attracts in excess of 300 students per year from a wide variety of disciplines. It is an ...

View on Coursera Course Description This course is part three of a specialization on algorithms and data structures. It covers basic algorithm design techniques such as divide and conquer, dynamic ...