Computational recovery of time-dependent volatility from integral observations in option pricing

摘要

In this paper robust algorithms for numerical identification of time dependent volatility by integral observations of one- and two-asset Black-Scholes models are developed. An average linearization in time of diffusion terms of the discrete initial boundary value problems is used. Then, a decomposition with respect to the volatility of the approximate solution is applied so that the transition to a new time layer is carried out by solving standard discrete elliptic problems. Numerical experiments using simulated as well as real data confirm the effectiveness of the present approach. (C) 2019 Elsevier B.V. All rights reserved.