Solving the Black-Scholes partial differential equation using physically - informed neural networks
Resolución de la ecuación diferencial parcial de Black-Scholes mediante redes neuronales físicamente informadas
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Abstract
Commemorative article for the 50th anniversary of the Black-Scholes model, presenting the derivation of the partial differential equation for pricing in the context of a continuous-time market model. The use of a physically informed neural network (PINN) is proposed as a resolution method, as a novel technique in the field of scientific machine learning, which allows solving these types of equations without the need for a large amount of training data. The article includes the implementation of the method and the valuation results for the case of European call options.
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