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The Calibration of Stochastic-Local Volatility Models - An Inverse\n Problem Perspective

2017/11/08 by Yuri F. Saporito, Xu Yang, Saporito, Yuri F. +3
Economics, Econometrics and Finance · #00A20 #Computational Finance (q-fin.CP) #FOS: Economics and business #FOS: Mathematics #Financial Markets and Investment Strategies #Financial Risk and Volatility Modeling #Numerical Analysis (math.NA) #Stochastic processes and financial applications

paper · pdf · doi:10.48550/arxiv.1711.03023

openalex publication_date 2017/11/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We tackle the calibration of the so-called Stochastic-Local Volatility (SLV)\nmodel. This is the class of financial models that combines the local and\nstochastic volatility features and has been subject of the attention by many\nresearchers recently. More precisely, given a local volatility surface and a\nchoice of stochastic volatility parameters, we calibrate the corresponding\nleverage function. Our approach makes use of regularization techniques from the\ninverse-problem theory, respecting the integrity of the data and thus avoiding\ndata interpolation. The result is a stable and robust algorithm which is\nresilient to instabilities in the regions of low probability density of the\nspot price and of the instantaneous variance. We substantiate our claims with\nnumerical experiments using simulated as well as real data.\n

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