We develop a deep reinforcement learning (RL) framework for an optimal market-making (MM) trading problem, specifically focusing on price processes with semi-Markov and Hawkes Jump-Diffusion dynamics. We begin by discussing the basics of RL and the deep RL framework used; we deployed the...

This paper investigates the relationship among transaction taxes, high-frequency trading (HFT), and market quality. We use the agent-based modeling (ABM) approach to dynamically assess the impact of transaction taxes on market quality with and without high-frequency trading. Preliminary tests...

In this research, we attempted to fit a trading system based on polynomial moving regression bands (MRB) to Nasdaq100 stocks from 2017 till the end of March 2024. Since stocks movement does not follow a linear behavior, we used multiple degree polynomial regression models to identify the stocks'...