Neural Network Models for Bitcoin Option Pricing

Abstract

Despite the current growing interest in Bitcoins-and cryptocurrencies in general-financial instruments, as well as studies related to them, are quite underdeveloped. Therefore, this article aims to provide a suitable pricing model for options written on this peculiar underlying. This is done through an artificial neural network approach, where classical pricing models-namely the trinomial tree, Monte Carlo simulation, and explicit finite difference method-are used as input layers. Results show that options written on Bitcoin turn out to be systematically overpriced when considering classical methods, whereas a noticeable improvement in price predictions is achieved by means of the proposed neural network model.