1 0 0 0 OA 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
- 著者
- 平野 正徳 今城 健太郎 南 賢太郎 島田 拓弥
- 出版者
- 一般社団法人 人工知能学会
- 雑誌
- 人工知能学会第二種研究会資料 (ISSN:24365556)
- 巻号頁・発行日
- vol.2022, no.FIN-028, pp.27, 2022-03-12 (Released:2022-10-21)
Deep Hedging, which uses deep learning and price time-series simulations to optimize option hedging, has recently been in the spotlight because it enables more realistic hedging that can take into account frictions such as transaction fees (imperfect market). However, the situation of hedging an option by other options has never been addressed by deep hedging because of its simulation difficulties. In that situation, pricing for tradable options should also be performed via deep hedging in simulations for realizing imperfect market simulations, which has required unrealizable enormous computational resources because of the nested architecture of deep hedging. Thus, in this study, we proposed a new deep-hedging mechanism for learning hedging strategies under such a nested situation. As a result, we showed better hedging via proposed deep hedging with multiple tradable options.