NGHIÊN CỨU BÀI TOÁN ĐỊNH GIÁ QUYỀN CHỌN SỬ DỤNG CÁC KĨ THUẬT MÁY HỌC

Abstract

Option pricing is  significant and has a long history in the field of quantitative financial research. In recent years, because of the rapid development of machine learning techniques, option pricing can be studied from building machine learning models. This study considers option pricing using Black-Scholes formula by some supervised machine learning algorithms. The performance of the models using several publicly shared options price datasets was then evaluated. Empirical results show that machine learning models are more likely to estimate option prices with high accuracy.