Examination of trading algorithm applying geometry characteristics for foreign exchange data

Abstract

In this paper, we examined a new method to predict fluctuation of foreign exchange rate. We input information extracted from historical data into PointNet++, which is proposed by C.R.Qi et al.[3] and predicted US Dollar to Yen Exchange rate 5 minutes later. The results implied that although there was tendency of overfitting, our method might capture a part of some structured factors of foreign exchange fluctuation. It is suggested that various range of approach related to machine learning could be useful for financial problems.