Rapid advances and diffusion of artificial intelligence (AI) technologies have the potential to
transform agriculture globally by improving measurement, prediction, and site-specific …

Goldstein et al. 2023). In this context, among many other factors, the development of
Electronic Data Gathering, Analysis, and Retrieval (EDGAR) in April 1993, has enhanced …

We consider two data-driven approaches to hedging, Reinforcement Learning and Deep
Trajectory-based Stochastic Optimal Control, under a stepwise mean-variance objective. We …

Retail banks use Asset Liability Management (ALM) to hedge interest rate risk associated
with differences in maturity and predictability of their loan and deposit portfolios. The …

An obstacle to effective teaming between humans and AI is the agent's" black box" design.
AI explanations have proven benefits, but few studies have explored the effects that …

Artificial Neural Networks (ANNs) have become a powerful tool for modeling complex
relationships in large-scale datasets. However, their black-box nature poses ethical …

In this paper, we examine the capacity of an arbitrage-free neural-SDE market model to
produce realistic scenarios for the joint dynamics of multiple European options on a single …

In this paper we examine the capacity of arbitrage-free neural stochastic differential equation
market models to produce realistic scenarios for the joint dynamics of multiple European …

The ability to construct a realistic simulator of financial exchanges, including reproducing the
dynamics of the limit order book, can give insight into many counterfactual scenarios, such …

We consider two data driven approaches, Reinforcement Learning (RL) and Deep
Trajectory-based Stochastic Optimal Control (DTSOC) for hedging a European call option …