Efficient Importance Sampling in Quasi-Monte Carlo Methods for Computational Finance

2021 ◽  
Vol 43 (1) ◽  
pp. B1-B29
Author(s):  
Chaojun Zhang ◽  
Xiaoqun Wang ◽  
Zhijian He
Keyword(s):  
Monte Carlo ◽  
Importance Sampling ◽  
Monte Carlo Methods ◽  
Computational Finance ◽  
Quasi Monte Carlo

QUASI-MONTE CARLO METHODS IN COMPUTATIONAL FINANCE

COSMOS ◽  
2005 ◽  
Vol 01 (01) ◽  
pp. 113-125
Author(s):  
HARALD NIEDERREITER
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Monte Carlo Methods ◽  
Scientific Computing ◽  
Computational Finance ◽  
Quasi Monte Carlo ◽  
Random Samples ◽  
Mortgage Backed Securities

Quasi-Monte Carlo methods are deterministic versions of Monte Carlo methods, in the sense that the random samples used in the implementation of a Monte Carlo method are replaced by judiciously chosen deterministic points with good distribution properties. They outperform classical Monte Carlo methods in many problems of scientific computing. This paper discusses applications of quasi-Monte Carlo methods to computational finance, with a special emphasis on the problems of pricing mortgage-backed securities and options. The necessary background on Monte Carlo and quasi-Monte Carlo methods is also provided.

scholarly journals Multilevel Quasi-Monte Carlo methods for lognormal diffusion problems

2017 ◽  
Vol 86 (308) ◽  
pp. 2827-2860 ◽  
Author(s):  
Frances Y. Kuo ◽  
Robert Scheichl ◽  
Christoph Schwab ◽  
Ian H. Sloan ◽  
Elisabeth Ullmann
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Methods ◽  
Quasi Monte Carlo ◽  
Diffusion Problems
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