1. Neural Network Learning of Black-Scholes Equation for Option Pricing
- Author
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Santos, Daniel de Souza and Ferreira, Tiago Alessandro Espinola
- Subjects
Computer Science - Machine Learning ,Quantitative Finance - Computational Finance ,Quantitative Finance - Pricing of Securities - Abstract
One of the most discussed problems in the financial world is stock option pricing. The Black-Scholes Equation is a Parabolic Partial Differential Equation which provides an option pricing model. The present work proposes an approach based on Neural Networks to solve the Black-Scholes Equations. Real-world data from the stock options market were used as the initial boundary to solve the Black-Scholes Equation. In particular, times series of call options prices of Brazilian companies Petrobras and Vale were employed. The results indicate that the network can learn to solve the Black-Sholes Equation for a specific real-world stock options time series. The experimental results showed that the Neural network option pricing based on the Black-Sholes Equation solution can reach an option pricing forecasting more accurate than the traditional Black-Sholes analytical solutions. The experimental results making it possible to use this methodology to make short-term call option price forecasts in options markets., Comment: 15 pages and 8 figures
- Published
- 2024