Cornell Citi Financial Data Science Seminars: Gordon Ritter (NYU Courant & Tandon) (Video)

Gordon Ritter, an adjunct professor in the department of finance and risk engineering at NYU Tandon and author of celebrated paper “Machine Learning for Trading,” spoke at the March 20 seminar that was held at the Tata Innovation Center in New York. 

Reinforcement learning is a way of training a machine to find an optimal policy for a stochastic optimal control system, without explicitly building a model for the system. In reinforcement learning, the search for optimal policies is organized around the search for the optimal value function (in the sense of the Hamilton-Jacobi-Bellman equation). We show that many problems in finance are special cases of this framework; for example, any derivative that can be priced by replication has the property that its price is given by the value function of the dynamic replicating portfolio strategy.

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