12 citations · 20 across the 4 of their papers we have counts for
4 papers
Uncertainty Aware Trader-Company Method: Interpretable Stock Price Prediction Capturing Uncertainty
Yugo Fujimoto, Kei Nakagawa, Kentaro Imajo +1
Machine learning is an increasingly popular tool with some success in predicting stock prices. One promising method is the Trader-Company~(TC) method, which takes into account the…
No-Transaction Band Network: A Neural Network Architecture for Efficient Deep Hedging
Shota Imaki, Kentaro Imajo, Katsuya Ito +2
Deep hedging (Buehler et al. 2019) is a versatile framework to compute the optimal hedging strategy of derivatives in incomplete markets. However, this optimal strategy is hard to…
Trader-Company Method: A Metaheuristic for Interpretable Stock Price Prediction
Katsuya Ito, Kentaro Minami, Kentaro Imajo +1
Investors try to predict returns of financial assets to make successful investment. Many quantitative analysts have used machine learning-based methods to find unknown profitable m…
Deep Portfolio Optimization via Distributional Prediction of Residual Factors
Kentaro Imajo, Kentaro Minami, Katsuya Ito +1
Recent developments in deep learning techniques have motivated intensive research in machine learning-aided stock trading strategies. However, since the financial market has a high…