Crossref Citations
This article has been cited by the following publications. This list is generated based on data provided by
Crossref.
Feng, Liming
Kovalov, Pavlo
Linetsky, Vadim
and
Marcozzi, Michael
2007.
Financial Engineering.
Vol. 15,
Issue. ,
p.
301.
Pironneau, Olivier
and
Achdou, Yves
2009.
Special Volume: Mathematical Modeling and Numerical Methods in Finance.
Vol. 15,
Issue. ,
p.
369.
Ballestra, Luca Vincenzo
and
Sgarra, Carlo
2010.
The evaluation of American options in a stochastic volatility model with jumps: An efficient finite element approach.
Computers & Mathematics with Applications,
Vol. 60,
Issue. 6,
p.
1571.
Reich, Nils
2010.
Wavelet compression of anisotropic integrodifferential operators on sparse tensor product spaces.
ESAIM: Mathematical Modelling and Numerical Analysis,
Vol. 44,
Issue. 1,
p.
33.
Achdou, Yves
and
Pironneau, Olivier
2010.
Encyclopedia of Quantitative Finance.
Miglio, E.
and
Sgarra, C.
2011.
A finite element discretization method for option pricing with the Bates model.
SeMA Journal,
Vol. 55,
Issue. 1,
p.
23.
Andalaft-Chacur, A.
Montaz Ali, M.
and
González Salazar, J.
2011.
Real options pricing by the finite element method.
Computers & Mathematics with Applications,
Vol. 61,
Issue. 9,
p.
2863.
Rambeerich, N.
Tangman, D.Y.
Lollchund, M.R.
and
Bhuruth, M.
2013.
High-order computational methods for option valuation under multifactor models.
European Journal of Operational Research,
Vol. 224,
Issue. 1,
p.
219.
Jeong, Darae
Li, Yibao
Choi, Yongho
Moon, Kyoung-Sook
and
Kim, Junseok
2013.
AN ADAPTIVE MULTIGRID TECHNIQUE FOR OPTION PRICING UNDER THE BLACK-SCHOLES MODEL.
Journal of the Korea Society for Industrial and Applied Mathematics,
Vol. 17,
Issue. 4,
p.
295.
Hilber, Norbert
Reichmann, Oleg
Schwab, Christoph
and
Winter, Christoph
2013.
Computational Methods for Quantitative Finance.
p.
105.
Jeong, Darae
Seo, Seungsuk
Hwang, Hyeongseok
Lee, Dongsun
Choi, Yongho
and
Kim, Junseok
2015.
Accuracy, Robustness, and Efficiency of the Linear Boundary Condition for the Black-Scholes Equations.
Discrete Dynamics in Nature and Society,
Vol. 2015,
Issue. ,
p.
1.
KIM, JUNSEOK
YOO, MINHYUN
SON, HYEJU
LEE, SEUNGGYU
KIM, MYEONG-HYEON
CHOI, YONGHO
JEONG, DARAE
and
KIM, YOUNG ROCK
2016.
PATH AVERAGED OPTION VALUE CRITERIA FOR SELECTING BETTER OPTIONS.
Journal of the Korea Society for Industrial and Applied Mathematics,
Vol. 20,
Issue. 2,
p.
163.
Canale, Anna
Mininni, Rosa Maria
and
Rhandi, Abdelaziz
2017.
Analytic approach to solve a degenerate parabolic PDE for the Heston model.
Mathematical Methods in the Applied Sciences,
Zhang, Rui Yan
Xu, Fang Fang
and
Huang, Jian Chao
2017.
Reconstructing local volatility using total variation.
Acta Mathematica Sinica, English Series,
Vol. 33,
Issue. 2,
p.
263.
Hozman, J.
and
Tichý, T.
2017.
A DG approach to the numerical solution of the Stein-Stein stochastic volatility option pricing model.
Vol. 1910,
Issue. ,
p.
030006.
Bonnans, J. Frédéric
and
Kröner, Axel
2018.
Variational Analysis for Options with Stochastic Volatility and Multiple Factors.
SIAM Journal on Financial Mathematics,
Vol. 9,
Issue. 2,
p.
465.
Hozman, Jiří
and
Tichý, Tomáš
2018.
DG framework for pricing European options under one-factor stochastic volatility models.
Journal of Computational and Applied Mathematics,
Vol. 344,
Issue. ,
p.
585.
Prohl, Silke
2019.
Finite Element Methods for Partial Differential Equations for Option Pricing.
SSRN Electronic Journal ,
Al–Zhour, Zeyad
Barfeie, Mahdiar
Soleymani, Fazlollah
and
Tohidi, Emran
2019.
A computational method to price with transaction costs under the nonlinear Black–Scholes model.
Chaos, Solitons & Fractals,
Vol. 127,
Issue. ,
p.
291.
Deswal, Komal
and
Kumar, Devendra
2022.
A wavelet‐based novel approximation to investigate the sensitivities of various path‐independent binary options.
Mathematical Methods in the Applied Sciences,
Vol. 45,
Issue. 16,
p.
9456.