This paper employs the PPO(Proximal Policy Optimization) algorithm to study the risk hedging problem of the Shanghai Stock Exchange(SSE) 50ETF options. First, the action and state spaces were designed based on the cha...This paper employs the PPO(Proximal Policy Optimization) algorithm to study the risk hedging problem of the Shanghai Stock Exchange(SSE) 50ETF options. First, the action and state spaces were designed based on the characteristics of the hedging task, and a reward function was developed according to the cost function of the options. Second, combining the concept of curriculum learning, the agent was guided to adopt a simulated-to-real learning approach for dynamic hedging tasks, reducing the learning difficulty and addressing the issue of insufficient option data. A dynamic hedging strategy for 50ETF options was constructed. Finally, numerical experiments demonstrate the superiority of the designed algorithm over traditional hedging strategies in terms of hedging effectiveness.展开更多
In this paper,we present a new precipitation model based on a multi-factor Ornstein-Uhlenbeck approach of pure-jump type.In this setup,we derive a representation for the related precipitation swap price process and in...In this paper,we present a new precipitation model based on a multi-factor Ornstein-Uhlenbeck approach of pure-jump type.In this setup,we derive a representation for the related precipitation swap price process and infer its risk-neutral time dynamics.We further deduce a pricing formula for European options written on the prccipitation swap and obtain the minimal variance hedging portfolio in the underlying weather market.In the second part of the paper,we provide a precipitation swap price representation under future information modeled by an initially enlarged filtration.We finally derive a formula for the associated information premium and investigate minimal variance hedging of prccipitation dcrivatives undcr futurc information.展开更多
基金supported by the Foundation of Key Laboratory of System Control and Information Processing,Ministry of Education,China,Scip20240111Aeronautical Science Foundation of China,Grant 2024Z071108001the Foundation of Key Laboratory of Traffic Information and Safety of Anhui Higher Education Institutes,Anhui Sanlian University,KLAHEI18018.
文摘This paper employs the PPO(Proximal Policy Optimization) algorithm to study the risk hedging problem of the Shanghai Stock Exchange(SSE) 50ETF options. First, the action and state spaces were designed based on the characteristics of the hedging task, and a reward function was developed according to the cost function of the options. Second, combining the concept of curriculum learning, the agent was guided to adopt a simulated-to-real learning approach for dynamic hedging tasks, reducing the learning difficulty and addressing the issue of insufficient option data. A dynamic hedging strategy for 50ETF options was constructed. Finally, numerical experiments demonstrate the superiority of the designed algorithm over traditional hedging strategies in terms of hedging effectiveness.
文摘In this paper,we present a new precipitation model based on a multi-factor Ornstein-Uhlenbeck approach of pure-jump type.In this setup,we derive a representation for the related precipitation swap price process and infer its risk-neutral time dynamics.We further deduce a pricing formula for European options written on the prccipitation swap and obtain the minimal variance hedging portfolio in the underlying weather market.In the second part of the paper,we provide a precipitation swap price representation under future information modeled by an initially enlarged filtration.We finally derive a formula for the associated information premium and investigate minimal variance hedging of prccipitation dcrivatives undcr futurc information.
