(2021). Deep Portfolio Optimization via Distributional Prediction of Residual Factors. In AAAI2021. (acceptance rate: 21%) https://arxiv.org/abs/2012.07245 • Ito, Minami, Imajo, Nakagawa (2021). Trader-Company Method: A Metaheuristic for Interpretable Stock Price Prediction. In AAMAS2021.(acceptance rate: 24%) https://arxiv.org/abs/2012.10215 • Liu, Ito, Minami, Imajo (2022). Power Laws and Symmetries in a Minimal Model of Financial Market Economy. Physical Review Research, No.4, e.033077. https://arxiv.org/abs/2206.06802 • Imaki, Imajo, Ito, Minami, Nakagawa (2023). No-Transaction Band Network: A Neural Network Architecture for Efficient Deep Hedging, The Journal of Financial Data Science, No.5 Vol.2, pp.84 - 99. https://arxiv.org/abs/2103.01775 • Liu, Minami, Imajo (2022). Theoretically Motivated Data Augmentation and Regularization for Portfolio Construction.In ICAIF2022. https://arxiv.org/abs/2106.04114 • Hirano, Minami, Imajo (2023). Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling, In ICAIF '23. https://arxiv.org/abs/2307.13217 国内学会・研究会
• 平野、今城、南、島田 (2022). オプションによるオプションのヘッジを可能にする二重 Deep Hedging 機構. 第28回 人工知能学会 金融情報学研究会(SIG-FIN)
• 南、今城、中川、今長谷 (2022). 予測型フルスケール最適化による資産配分. 第36回人工知能学会全国大会.
業績一覧: https://projects.preferred.jp/qfin/ja/publications.html