We develop a mixed-frequency, tree-based, gradient-boosting model designed to assess the default risk of privately held firms in real time. The model uses data from publicly-traded companies to construct a probability of default (PD) function. This function integrates high-frequency,...

Learning from the past is critical for shaping the future, especially when it comes to economic policymaking. Building upon the current methods in the application of Reinforcement Learning (RL) to the large language models (LLMs), this paper introduces Reinforcement Learning from Experience...

We explore the stability properties of interest rate rules granting an explicit response to stock prices in a New-Keynesian DSGE model populated by Blanchard-Yaari non-Ricardian households. The constant turnover between long-time stock holders and asset-poor newcomers generates a financial...