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A regression-based numerical scheme for backward stochastic differential equations
Deng DING; Yiqi Liu
2017-12
Source PublicationCOMPUTATIONAL STATISTICS
ABS Journal Level2
ISSN0943-4062
Volume32Issue:4Pages:1357-1373
Abstract

Based on Fourier cosine expansion, two approximations of conditional expectations are studied, and the local errors for these approximations are analyzed. Using these approximations and the theta-time discretization, a new and efficient numerical scheme, which is based on least-squares regression, for forward-backward stochastic differential equations is proposed. Numerical experiments are done to test the availability and stability of this new scheme for Black-Scholes call and calls combination under an empirical expression about volatility. Some conclusions are given.

KeywordCharacteristic Functions Least-squares Regressions Monte Carlo Methods European Options
DOIhttp://doi.org/10.1007/s00180-017-0763-x
Indexed BySCI
Language英语
WOS Research AreaMathematics
WOS SubjectStatistics & Probability
WOS IDWOS:000413025300007
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Cited Times [WOS]:2   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionFaculty of Science and Technology
DEPARTMENT OF MATHEMATICS
Corresponding AuthorDeng DING
AffiliationDepartment of Mathematics Faculty of Science and Technology University of Macau, Macao, China
First Author AffilicationFaculty of Science and Technology
Corresponding Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Deng DING,Yiqi Liu. A regression-based numerical scheme for backward stochastic differential equations[J]. COMPUTATIONAL STATISTICS,2017,32(4):1357-1373.
APA Deng DING,&Yiqi Liu.(2017).A regression-based numerical scheme for backward stochastic differential equations.COMPUTATIONAL STATISTICS,32(4),1357-1373.
MLA Deng DING,et al."A regression-based numerical scheme for backward stochastic differential equations".COMPUTATIONAL STATISTICS 32.4(2017):1357-1373.
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