Calibration of European option pricing model using a hybrid structure based on the optimized artificial neural network and Black-Scholes model | ||
| Journal of Mathematics and Modeling in Finance | ||
| دوره 4، شماره 1، مهر 2024، صفحه 67-82 اصل مقاله (493.29 K) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22054/jmmf.2024.78910.1128 | ||
| نویسندگان | ||
| Farshid Mehrdoust* 1؛ Maryam Noorani2 | ||
| 1Department of Applied Mathematics, Faculty of Mathematical Science, University of Guilan | ||
| 2Department of Applied Mathematics, Faculty of Mathematical Science, University of Guilan. | ||
| چکیده | ||
| This study suggests a novel approach for calibrating European option pricing model by a hybrid model based on the optimized artificial neural network and Black-Scholes model. In this model, the inputs of the artificial neural network are the Black-Scholes equations with different maturity dates and strike prices. The presented calibration process involves training the neural network on historical option prices and adjusting its parameters using the Levenberg-Marquardt optimization algorithm. The resulting hybrid model shows superior accuracy and efficiency in option pricing on both in sample and out of sample dataset. | ||
| کلیدواژهها | ||
| Artificial neural network؛ Calibration؛ Levenberg-Marquardt algorithm؛ Option pricing | ||
| مراجع | ||
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