# PAMS: Platform for Artificial Market Simulations

arXiv: https://arxiv.org/abs/2309.10729 · HTML: https://mlsanity.com/paper/2309.10729/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 41 references that are in the map.
- First posted on arXiv 19 Sep 2023.

## Builds on (most cited first, 2 of 2)

- [Layer Normalization](https://mlsanity.com/paper/1607.06450/) (2016)
- [Deep Learning for Spatio-Temporal Modeling: Dynamic Traffic Flows and High Frequency Trading](https://mlsanity.com/paper/1705.09851/) (2017)

## Built on by (most cited first, 1 of 1)

- [Experimental Analysis of Deep Hedging Using Artificial Market Simulations for Underlying Asset Simulators](https://mlsanity.com/paper/2404.09462/) (2024)

## Abstract (arXiv)

This paper presents a new artificial market simulation platform, PAMS: Platform for Artificial Market Simulations. PAMS is developed as a Python-based simulator that is easily integrated with deep learning and enabling various simulation that requires easy users' modification. In this paper, we demonstrate PAMS effectiveness through a study using agents predicting future prices by deep learning.