Pagnottoni Paolo
Department of Economics and Management, University of Pavia, Pavia, Italy.
Front Artif Intell. 2019 Jul 3;2:5. doi: 10.3389/frai.2019.00005. eCollection 2019.
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.
尽管当前人们对比特币以及一般意义上的加密货币这种金融工具的兴趣日益浓厚，但与之相关的研究却相当不完善。因此，本文旨在为基于这种特殊标的资产的期权提供一个合适的定价模型。这是通过一种人工神经网络方法来实现的，其中经典定价模型——即三项式树、蒙特卡罗模拟和显式有限差分法——被用作输入层。结果表明，在考虑经典方法时，基于比特币的期权结果被系统性地高估了，而通过所提出的神经网络模型，价格预测有了显著改善。
