1 citations · 1 across the 3 of their papers we have counts for
4 papers
Finding Optimal Trading History in Reinforcement Learning for Stock Market Trading
Sina Montazeri, Haseebullah Jumakhan, Amir Mirzaeinia
This paper investigates the optimization of temporal windows in Financial Deep Reinforcement Learning (DRL) models using 2D Convolutional Neural Networks (CNNs). We introduce a nov…
Gradient Reduction Convolutional Neural Network Policy for Financial Deep Reinforcement Learning
Sina Montazeri, Haseebullah Jumakhan, Sonia Abrasiabian +1
Building on our prior explorations of convolutional neural networks (CNNs) for financial data processing, this paper introduces two significant enhancements to refine our CNN model…
CNN-DRL with Shuffled Features in Finance
Sina Montazeri, Akram Mirzaeinia, Amir Mirzaeinia
In prior methods, it was observed that the application of Convolutional Neural Networks agent in Deep Reinforcement Learning to financial data resulted in an enhanced reward. In th…
CNN-DRL for Scalable Actions in Finance
Sina Montazeri, Akram Mirzaeinia, Haseebullah Jumakhan +1
The published MLP-based DRL in finance has difficulties in learning the dynamics of the environment when the action scale increases. If the buying and selling increase to one thous…