An artificial neural network representation of the SABR stochastic volatility model
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An artificial neural network representation of the SABR stochastic volatility model. / McGhee, William A.
I: Journal of Computational Finance, Bind 25, Nr. 2, 2021.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - An artificial neural network representation of the SABR stochastic volatility model
AU - McGhee, William A.
N1 - Publisher Copyright: © 2021 Infopro Digital Risk (IP) Limited.
PY - 2021
Y1 - 2021
N2 - In this paper, the universal approximation theorem of artificial neural networks (ANNs) is applied to the stochastic alpha beta rho (SABR) stochastic volatility model in order to construct highly efficient representations. Initially, the SABR approximation of Hagan et al is considered, followed by the more accurate integration scheme of McGhee as well as a two-factor finite-difference scheme. The resulting ANN cal-culates 10 000 times faster than the finite-difference scheme while maintaining a high degree of accuracy. As a result, the ANN dispenses with the need for the commonly used SABR approximation.
AB - In this paper, the universal approximation theorem of artificial neural networks (ANNs) is applied to the stochastic alpha beta rho (SABR) stochastic volatility model in order to construct highly efficient representations. Initially, the SABR approximation of Hagan et al is considered, followed by the more accurate integration scheme of McGhee as well as a two-factor finite-difference scheme. The resulting ANN cal-culates 10 000 times faster than the finite-difference scheme while maintaining a high degree of accuracy. As a result, the ANN dispenses with the need for the commonly used SABR approximation.
KW - artificial neural network
KW - SABR approximation
KW - SABR integration scheme
KW - stochastic alpha beta rho (SABR) model
KW - stochastic volatility
KW - universal approximation theorem
U2 - 10.21314/JCF.2021.007
DO - 10.21314/JCF.2021.007
M3 - Journal article
AN - SCOPUS:85127611862
VL - 25
JO - Journal of Computational Finance
JF - Journal of Computational Finance
SN - 1460-1559
IS - 2
ER -
ID: 306673106