Dynamic hedging of SSE 50ETF options based on deep reinforcement learning TD3 fusing curriculum learning
How to conduct dynamic hedging to manage position risk is extremely crucial in option trading,but there is no standard answer for perfect hedging in the actual market environment.Therefore,seeking better hedging strat-egies has always been a hot demand and research focus in the investment field.Using the deep reinforcement learn-ing algorithm TD3 and the concept of curriculum learning,a dynamic hedging strategy for the Shanghai Stock Ex-change 50 ETF options has been developed.This strategy guides the agent from simulation to real-world learning to achieve dynamic hedging tasks,reducing learning difficulty and alleviating the issue of insufficient option data.The results showed that the hedging effect of the deep reinforcement learning algorithm far exceeded that of tradi-tional hedging strategies,verifying the effectiveness and advantages of the reinforcement learning algorithm in the field of option hedging.
国家科技期刊平台
NSTL
万方数据
