نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشجوی دکتری تخصصی مهندسی مالی، گروه مدیریت، واحد رشت، دانشگاه آزاد اسلامی، رشت، ایران
2 گروه مدیریت بازرگانی، واحد رشت، دانشگاه آزاد اسلامی، رشت، ایران (نویسنده مسئول)
3 گروه حسابداری و مالی، دانشگاه پیام نور، تهران، ایران
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
The present study offers a new interpretation of the Generalized Integral Transform Technique as a powerful numerical method called the Integral Transform method. This method transforms models of nonlinear partial differential equations into a nonlinear system paired with ordinary differential equations to be solved numerically. On the other hand, in the present study, not only pricing is discussed, but also model calibration, which is a critical process, is designed to minimize the difference between the observed prices and the model prices. In order to implement the proposed model, the present study has used the call option data offered in the Tehran Stock Exchange and as a sample, has used the call option information of SAIPA Company shares for the maturity of June 2022. First, the Conditional Probability Distribution Function for different initial values of the underlying asset was obtained by coding in Python environment, and then the model was calibrated at different maturities. The results showed that the model calibration based on the Dove Swarm Optimization algorithm is suitable for options that are in a state of At-the-Money or In-the-Money in all maturity scenarios and are in Out-of-the-Money state in the midterm and long term scenarios. Furthermore, calibration based on the ant colony optimization algorithm can be used for options that are in an Out-of-the-Money state in the short-term scenario.
کلیدواژهها [English]