Option Pricing Based on Modular Neural Network - Moslem Peymany Foroushani; mohamad ali dehghan dehnavi; Milad Kouhkan (تحقیقات مالی)
Objective Hedging the risk caused by price volatility using options relies on an accurate and appropriate valuation of those options. Therefore, the purpose of this research is to value the options traded on the Tehran Stock Exchange using modular neural networks. The study will also compare the performance of these modular neural networks with the most renowned options valuation models, namely the Black-Scholes-Merton model and the multi-layer perceptron neural network model.