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Option pricing and hedging are fundamental components of financial decision-making that have important implications for investors and economic firms. Traditional methods for predicting option prices and managing their risk rely on statistical models and financial analytics. However, recent advances in artificial intelligence have opened up new opportunities for more accurate and efficient forecasting and risk management of this important financial indicator. In this study, we have used the capabilities of artificial neural networks (ANN) to develop a new model for option pricing and hedging. Artificial neural networks are a class of machine learning algorithms that are able to understand complex patterns and relationships in data by mimicking the biological behavior of the human brain in learning topics.Using an artificial neural network model, we have attempted to improve the accuracy and reliability of option price predictions and also enhance hedging strategies. Our approach to developing and implementing an artificial neural network model for option pricing and hedging is systematic and follows a rigorous methodology that includes data collection, preprocessing, model training, evaluation, and optimization. By identifying a suitable architecture and fine-tuning the neural network parameters, a model was proposed that can analyze the dynamics of options market data and provide the necessary insights to investors and financial institutions. Option pricing and hedging are essential components of financial decision-making that have important implications for investors and economic firms.Traditional methods for predicting option prices and managing their risk rely on statistical models and financial analytics. However, recent advances in artificial intelligence have opened up new opportunities for more accurate and efficient forecasting and risk management of this important financial indicator. In this study, we have used the capabilities of artificial neural networks (ANN) to develop a new model for option pricing and hedging. Artificial neural networks are a class of machine learning algorithms that, by mimicking the biological behavior of the human brain in learning topics, are able to understand patterns and complex relationships in data. Using an artificial neural network model, we have attempted to improve the accuracy and reliability of option price forecasts and also strengthen hedging strategies.Our approach to developing and implementing an artificial neural network model for option pricing and hedging is systematic and follows a rigorous methodology that includes data collection, preprocessing, model training, evaluation, and optimization. By identifying a suitable architecture and fine-tuning the neural network parameters, a model was proposed that can analyze the dynamics of options market data and provide the necessary insights to investors and financial institutions

Keywords: Financial decision making, statistical risk, artificial neural networks, pricing

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