NN de-Americanization: A Fast and Efficient Calibration Method for American-Style Options

Abstract

Neural network (NN) de-Americanization produces fast and accurate pseudo-European option prices from American option market prices, facilitating the calibration of derivative models. The industry approach binomial de-Americanization takes a flat volatility surface as input. In contrast, the NN de-Americanization method takes the detailed shape of the volatility surface as an input; this is critical for the accurate evaluation of the early exercise premium (EEP) when interest rates are not close to zero.

Keywords: Option theory, American-style options, fast calibration, deep learning, local volatility model

JEL Classification: G13, C45, C61, C63, C10