three ensemble-learning methods-specifically, bagging, random forest, and boosting-with those of various neural … boosting is superior to other machine-learning methods including neural networks. It is also found that the performance of …

Prediction of financial market data with deep learning models has achieved some level of recent success. However … learning. One way to overcome these limitations is to augment real market data with agent based artificial market simulation … this study we propose a framework for training deep reinforcement learning models in agent based artificial price …

We present a deep reinforcement learning framework for an automatic trading of contracts for difference (CfD) on … indices at a high frequency. Our contribution proves that reinforcement learning agents with recurrent long short-term memory … but instead uses a reinforcement learning agent to learn an overall lucrative trading policy. Therefore, we simulate a …

The coronavirus crisis that started in December 2019 was declared a pandemic by March 2020 and had devastating global …