Investigating Inverse Reinforcement Learning from Human Behavior: Effect of Demonstrations with Temporal Biases on Learning Rewards using Inverse Reinforcement Learning

Inverse Reinforcement Learning (IRL) is a machine learning technique used for learning rewards from the behavior of an expert agent. With complex agents, such as humans, the maximized reward may not be easily retrievable. This is because humans are prone to cognitive biases. Cognitive biases are a form of deviation from rationality that affects...

Optimal Pairs Trading Strategies: A Stochastic Mean–Variance Approach

In this paper, we consider optimal pairs trading strategies in terms of static optimality and dynamic optimality under mean–variance criterion. The spread of the entity pairs is assumed to be mean-reverting and follows an Ornstein–Uhlenbeck process. A constrained optimal control problem is considered, and the Lagrange multiplier technique is...