Based on empirical evidence, a simple model of oil exploration and discovery is deyeloped, which emphasizes the stochastics of the discovery process and its informational aspects. Open-loop-feedback, m-measurement-feedback and closed-loop optimal exploratory strategies are derived. In...

We consider two data-driven approaches to hedging, Reinforcement Learning and Deep Trajectory-based Stochastic Optimal Control, under a stepwise mean-variance objective. We compare their performance for a European call option in the presence of transaction costs under discrete trading schedules....

When an economic agent makes a choice, stochastic models predicting those choices can be updated. The structural assumptions embedded in the prior model condition the updated one, to the extent that the same evidence produces different predictions even when previous ones were identical. We...