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Lina von Sydow
Lina von Sydow
Professor of Scientific Computing, Department of Information Technology, Uppsala University
Verifierad e-postadress på it.uu.se - Startsida
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Space–time adaptive finite difference method for European multi-asset options
P Lötstedt, J Persson, L von Sydow, J Tysk
Computers & Mathematics with Applications 53 (8), 1159-1180, 2007
902007
BENCHOP–The BENCHmarking project in option pricing
L von Sydow, L Josef Höök, E Larsson, E Lindström, S Milovanović, ...
International Journal of Computer Mathematics 92 (12), 2361-2379, 2015
842015
Pricing European multi-asset options using a space-time adaptive FD-method
J Persson, L von Sydow
in Computing and Visualization in Science, Dept. of Information Technology …, 2007
842007
An IMEX-scheme for pricing options under stochastic volatility models with jumps
S Salmi, J Toivanen, L von Sydow
SIAM Journal on Scientific Computing 36 (5), B817-B834, 2014
722014
Preconditioning for radial basis function partition of unity methods
A Heryudono, E Larsson, A Ramage, L von Sydow
Journal of Scientific Computing 67, 1089-1109, 2016
542016
Implicit solution of hyperbolic equations with space-time adaptivity
P Lötstedt, S Söderberg, A Ramage, L Hemmingsson-Frändén
BIT Numerical Mathematics 42 (1), 134-158, 2002
462002
Radial basis function generated finite differences for option pricing problems
S Milovanović, L von Sydow
Computers & Mathematics with Applications 75 (4), 1462-1481, 2018
422018
Pricing American options using a space-time adaptive finite difference method
J Persson, L von Sydow
Mathematics and Computers in Simulation 80 (9), 1922-1935, 2010
362010
A highly accurate adaptive finite difference solver for the Black–Scholes equation
G Linde, J Persson, L Von Sydow
International Journal of Computer Mathematics 86 (12), 2104-2121, 2009
34*2009
Iterative methods for pricing American options under the Bates model
S Salmi, J Toivanen, L von Sydow
Procedia Computer Science 18, 1136-1144, 2013
332013
Forward deterministic pricing of options using Gaussian radial basis functions
J Amani Rad, J Höök, E Larsson, L von Sydow
Journal of computational science 24, 209-217, 2018
292018
Shallow ice approximation, second order shallow ice approximation, and full Stokes models: A discussion of their roles in palaeo-ice sheet modelling and development
N Kirchner, J Ahlkrona, EJ Gowan, P Lötstedt, JM Lea, R Noormets, ...
Quaternary Science Reviews 147, 136-147, 2016
272016
A semi-circulant preconditioner for the convection-diffusion equation
L Hemmingsson
Numerische Mathematik 81 (2), 211-248, 1998
271998
Adaptive finite differences and IMEX time-stepping to price options under Bates model
L von Sydow, J Toivanen, C Zhang
International Journal of Computer Mathematics 92 (12), 2515-2529, 2015
252015
Toeplitz Preconditioners with Block Structure for First‐order PDEs
L Hemmingsson
Numerical linear algebra with applications 3 (1), 21-44, 1998
241998
A high order method for pricing of financial derivatives using radial basis function generated finite differences
S Milovanović, L von Sydow
Mathematics and Computers in Simulation 174, 205-217, 2020
222020
Analysis of semi-Toeplitz preconditioners for first-order PDEs
L Hemmingsson, K Otto
SIAM Journal on Scientific Computing 17 (1), 47-64, 1996
211996
A fast modified sine transform for solving block-tridiagonal systems with Toeplitz blocks
L Hemmingsson
Numerical Algorithms 7 (2), 375-389, 1994
211994
A fast domain decomposition high order Poisson solver
B Gustafsson, L Hemmingsson-Frändén
Journal of scientific computing 14 (3), 223-243, 1999
171999
Numerical option pricing in the presence of bubbles
E Ekström, P Lötstedt, LV Sydow, J Tysk
Quantitative Finance 11 (8), 1125-1128, 2011
162011
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Artiklar 1–20