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@article{Radu:2016:10.1137/15M1035215,
author = {Radu, Baltean-Lugojany and Parpas, P},
doi = {10.1137/15M1035215},
journal = {SIAM Journal on Financial Mathematics},
pages = {917--946},
title = {Robust numerical calibration for implied volatility expansion models},
url = {http://dx.doi.org/10.1137/15M1035215},
volume = {7},
year = {2016}
}

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TY  - JOUR
AB  - Implied volatility expansions allow calibration of sophisticated volatility models.  They provide anaccurate  t and parametrization of implied volatility surfaces that is consistent with empirical ob-servations.  Fine-grained higher order expansions o er a better  t but pose the challenge of  nding arobust, stable and computationally tractable calibration procedure due to a large number of marketparameters and nonlinearities.  We propose calibration schemes for second order expansions that takeadvantage of the model's structure via exact parameter reductions and recoveries, reuse and scalingbetween expansion orders where permitted by the model asymptotic regime and numerical iterationover bounded signi cant parameters.  We perform a numerical analysis over 12 years of real S&P 500index options data for both multiscale stochastic and general local-stochastic volatility models.  Ourmethods are validated empirically by obtaining stable market parameters that meet the qualitativeand numerical constraints imposed by their functional forms and model asymptotic assumptions.
AU  - Radu,Baltean-Lugojany
AU  - Parpas,P
DO  - 10.1137/15M1035215
EP  - 946
PY  - 2016///
SN  - 1945-497X
SP  - 917
TI  - Robust numerical calibration for implied volatility expansion models
T2  - SIAM Journal on Financial Mathematics
UR  - http://dx.doi.org/10.1137/15M1035215
UR  - http://hdl.handle.net/10044/1/41194
VL  - 7
ER  -

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