Pricing options with exponential Lévy neural network. - Jeonggyu Huh (Expert Syst. Appl., 2019)

Pricing path-dependent exotic options with flow-based generative networks. - Hyun-Gyoon Kim; Se-Jin Kwon; Jeong-Hoon Kim; Jeonggyu Huh (Appl. Soft Comput., 2022)

Large-scale online learning of implied volatilities. - Tae-Kyoung Kim; Hyun-Gyoon Kim; Jeonggyu Huh (Expert Syst. Appl., 2022)

Extensive networks would eliminate the demand for pricing formulas. - Jaegi Jeon; Kyunghyun Park; Jeonggyu Huh (Knowl. Based Syst., 2022)

Tighter 'uniform bounds for Black-Scholes implied volatility' and the applications to root-finding. - Jaehyuk Choi 003; Jeonggyu Huh; Nan Su (Oper. Res. Lett., 2024)

Improved accuracy of an analytical approximation for option pricing under stochastic volatility models using deep learning techniques. - Donghyun Kim; Jeonggyu Huh; Ji-Hun Yoon (Comput. Math. Appl., 2025)

Deep learning of optimal exercise boundaries for American options. - Hyun-Gyoon Kim; Jeonggyu Huh (Int. J. Comput. Math., 2025)