< back

Concept and Practice of Artificial Market Data Mining Platform

Masanori HIRANO, Hiroki SAKAJI, Kiyoshi IZUM

2022 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr), May 5, 2022


Conference

2022 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr)

Abstract

We proposed a concept called the artificial market data mining platform and presented a practical example for it. This concept is designed to evaluate data mining methods through artificial market simulation. We believe that the proposed platform can help us conduct a fair evaluation of data mining methods for the financial market without actual data dependence, and investigate the impact of financial market factors on predictions of future market movements. In this study, as a practical example, we built a tick-time level artificial market simulation and data mining models to predict short-term price changes and investigated the effect of four financial market factors on the performance of data mining models. Through experimental analysis, we demonstrated the validity and benefits of the proposed concept and practice model. We also discussed the potential and future applications of our proposal.

Keywords

Artificial Market; Data Mining; Financial Market; Agent-based Simulation;

doi

10.1109/CIFEr52523.2022.9776095


bibtex

@inproceedings{Hirano2022-cifer,
  title={{Concept and Practice of Artificial Market Data Mining Platform}},
  autor={Masanori HIRANO and Hiroki SAKAJI and Kiyoshi IZUM},
  booktitle={2022 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr)},
  pages={1-10},
  doi={10.1109/CIFEr52523.2022.9776095},
  year={2022}
}