An agent-based model and detect price manipulation based on intraday transaction data with simulation

In this article, we propose an agent-based model for LOB markets, and by simulation, we estimate the model's parameters. This model has two interesting points. First, we divide the data transaction of 1 day into six parts. Second, we detect price manipulation by using intraday transaction data. To detect price manipulation, we simulate the model once without the price manipulator and once with the price manipulator, and then by using some statistical properties such as skewness we find relations to detect price manipulation.