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Found 5 papers, 0 papers with code
Reinforcement Learning in Agent-Based Market Simulation: Unveiling Realistic Stylized Facts and Behavior
Investors and regulators can greatly benefit from a realistic market simulator that enables them to anticipate the consequences of their decisions in real markets.
Control in Stochastic Environment with Delays: A Model-based Reinforcement Learning Approach
In this paper we are introducing a new reinforcement learning method for control problems in environments with delayed feedback.
A Sparsity Algorithm with Applications to Corporate Credit Rating
We apply the sparsity algorithm to provide a simple suggestion to publicly traded companies in order to improve their credit ratings.
Application of Deep Neural Networks to assess corporate Credit Rating
The goal of the analysis is to improve application of machine learning algorithms to credit assessment.
SHIFT: A Highly Realistic Financial Market Simulation Platform
This paper presents a new financial market simulator that may be used as a tool in both industry and academia for research in market microstructure.
