No-Transaction Band Network: A Neural Network Architecture for Efficient Deep Hedging

2 code implementations • 2 Mar 2021 • Shota Imaki, Kentaro Imajo, Katsuya Ito, Kentaro Minami, Kei Nakagawa

Deep hedging (Buehler et al. 2019) is a versatile framework to compute the optimal hedging strategy of derivatives in incomplete markets.

Trader-Company Method: A Metaheuristic for Interpretable Stock Price Prediction

1 code implementation • 18 Dec 2020 • Katsuya Ito, Kentaro Minami, Kentaro Imajo, Kei Nakagawa

We show the effectiveness of our method by conducting experiments on real market data.

BIG-bench Machine Learning Stock Price Prediction

Deep Portfolio Optimization via Distributional Prediction of Residual Factors

no code implementations • 14 Dec 2020 • Kentaro Imajo, Kentaro Minami, Katsuya Ito, Kei Nakagawa

In this study, we propose a novel method of constructing a portfolio based on predicting the distribution of a financial quantity called residual factors, which is known to be generally useful for hedging the risk exposure to common market factors.

BIG-bench Machine Learning Portfolio Optimization