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Adaptive finite differences and IMEX time-stepping to price options under Bates model.

, , and . Int. J. Comput. Math., 92 (12): 2515-2529 (2015)

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Special issue - Computational and algorithmic finance., , , and . J. Comput. Sci., (2018)A High Order Method for Pricing of Financial Derivatives using Radial Basis Function generated Finite Differences., and . CoRR, (2018)BENCHOP - SLV: the BENCHmarking project in Option Pricing - Stochastic and Local Volatility problems., , , , , , , , , and 2 other author(s). Int. J. Comput. Math., 96 (10): 1910-1923 (2019)A high order method for pricing of financial derivatives using Radial Basis Function generated Finite Differences., and . Math. Comput. Simul., (2020)Numerical option pricing without oscillations using flux limiters., and . Comput. Math. Appl., 70 (1): 1-10 (2015)Iterative Methods for Pricing American Options under the Bates Model., , and . ICCS, volume 18 of Procedia Computer Science, page 1136-1144. Elsevier, (2013)Preconditioning for Radial Basis Function Partition of Unity Methods., , , and . J. Sci. Comput., 67 (3): 1089-1109 (2016)Accurate and stable time stepping in ice sheet modeling., , and . J. Comput. Phys., (2017)Radial Basis Function generated Finite Differences for option pricing problems., and . Comput. Math. Appl., 75 (4): 1462-1481 (2018)The Kolmogorov forward fractional partial differential equation for the CGMY-process with applications in option pricing., , and . Comput. Math. Appl., 76 (10): 2330-2344 (2018)