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....

In this note we formulate an optimality problem for Stochastic process with a regime absorbing state. We present a solution for this problem as a pair of differential equations that are recusrsively linked. As an application I obtain an analytical for the Merton portfolio problem in a case for a...

Consider robust utility maximization with an irreversible consumption habit, where an agent concerned about model ambiguity is unwilling to decrease consumption and must simultaneously contend with a disutility (i.e., an adjustment cost) due to a consumption increase. While the optimization is a...

Ai and Li [2015] introduced a problem at the interface of the neoclassical investment and dynamic contract theories. Specifically, the authors consider the optimal design of a contract that provides sufficient incentives to the management for it to implement the shareholder’s investment plan...

Diversification plays an important role in financial theory and lays the foundation for financial risk management. However, its role is greatly weakened when systemic risk events occur. In this paper, we study portfolio selection against systemic risk from the perspective of individual...