Allameh Tabataba'i University Press Journal of Mathematics and Modeling in Finance 2783-0578 3 2 2023 12 01 A dynamical system model-driven approach to pricing with smart volatility: a case study of catastrophe bonds pricing for China’s flood 191 207 17001 10.22054/jmmf.2024.77890.1118 EN S. Pourmohammad Azizi Department of Electrical Engineering, National Taiwan Ocean University, Keelung, Taiwan RajabAli Ghasempour Department of Mathematics and Physics, University of Campania Luigi Vanvitelli, Caserta, Italy Amirhossein Nafei Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei, Taiwan Journal Article 2024 01 22 This study explores the application of dynamic systems for modeling and valuing catastrophe bonds to establish a more intelligent and adaptive approach to determining their volatility parameter. These financial instruments hold significant importance for insurance companies in safeguarding against the risk of insolvency stemming from the escalating frequency and severity of natural disasters worldwide. Employing mathematical principles, this research formulated a pricing partial differential equation and introduced a dynamic system for its resolution. The damage model was assumed to follow a stochastic process, and a radial basis neural network was utilized to estimate the volatility parameter of this stochastic process by leveraging historical data. The study scrutinized the pricing framework of catastrophe bonds related to floods and storms in China, ultimately demonstrating that the proposed methodology proved effective and computationally efficient when contrasted with alternative approaches. https://jmmf.atu.ac.ir/article_17001_2b0d76f0291399259a3074a90956ebea.pdf