Host: The Japanese Society for Artificial Intelligence
Name : The 35th Annual Conference of the Japanese Society for Artificial Intelligence
Number : 35
Location : [in Japanese]
Date : June 08, 2021 - June 11, 2021
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.