STBM+: Advanced Stochastic Trading Behavior Model for Financial Markets based on Residual Blocks or Transformers [in Japanese]

Masanori HIRANO, Kiyoshi IZUMI, Hiroki SAKAJI

The 35th Annual Conference of the Japanese Society for Artificial Intelligence, p. 2N1-IS-2a-03, June 9, 2021

Conference

The 35th Annual Conference of the Japanese Society for Artificial Intelligence (JSAI2021)

Abstract

This paper proposes a new model to reverse engineer and predict traders' behaviors for financial market. In this model, we used an architecture based on the transformer and residual block, and a loss function based on Kullback-Leibler divergence. In addition, we established a new evaluation metric, and consequently, succeeded in constructing a model that outperforms conventional methods and has an efficient architecture. In the future, we will build a model with higher performance and versatility. Moreover, we will introduce this model to financial simulations.

Keywords

Financial Market; Machine learning; Trader behavior;

doi

10.11517/pjsai.JSAI2021.0_2N1IS2a03

bibtex

@inproceedings{Hirano2021-jsai35,
  title={{STBM+: Advanced Stochastic Trading Behavior Model for Financial Markets based on Residual Blocks or Transformers [in Japanese]}},
  author={Masanori HIRANO and Kiyoshi IZUMI and Hiroki SAKAJI},
  booktitle={The 35th Annual Conference of the Japanese Society for Artificial Intelligence},
  pages={2N1-IS-2a-03},
  doi={10.11517/pjsai.JSAI2021.0_2N1IS2a03},
  year={2021}
}