Random sampling from low-discrepancy sequences: Applications to option pricing

Mathematical and Computer Modelling

Volumn 35, Issue 11-12, 2002, Pages 1221-1234

  Okten G ^a  

^a BALL STATE UNIVERSITY   (United States)

Author keywords

Low discrepancy sequences; Monte Carlo methods; Option pricing

Indexed keywords

ECONOMIC ASPECT; MATHEMATICAL ANALYSIS; MONTE CARLO METHOD; OPTION PRICING; PROSPECTIVE PRICING;

EID: 0037118234     PISSN: 08957177     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0895-7177(02)00081-X     Document Type: Article

References (23)

1. Latin supercube sampling for very high dimensional simulations
2. A probabilistic result on the discrepancy of a hybrid-Monte Carlo sequence and applications
3. Applications of a hybrid-Monte Carlo sequence to option pricing
4. High dimensional simulation
5. Randomly permuted (t,m,s)-nets and (t,s)-sequences, Monte Carlo and quasi-Monte Carlo in scientific computing
6. Randomization of number theoretic methods for multiple integration
7. On the use of low discrepancy sequences in Monte Carlo methods
8. Error estimation for quasi-Monte Carlo methods, Monte Carlo and quasi-Monte Carlo methods, 1996
9. Randomized Halton sequences
10. Twisted GFSR generators II
11. Implementation and tests of low-discrepancy sequences
12. Good permutations for extreme discrepancy
13. Methods for estimating discrepancy
14. Sequences with low discrepancy and pseudo-random numbers: Theoretical remarks and numerical tests
15. Quasi-Monte Carlo methods in numerical finance