search query: @author Tan, K. / total: 4
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| Author: | Joy, C. Tan, K. Boyle, P. |
| Title: | Quasi-Monte Carlo methods in numerical finance |
| Journal: | Management Science
1996 : JUN, VOL. 42:6, p. 926-938 |
| Index terms: | MANAGEMENT SCIENCE FINANCE SIMULATION |
| Language: | eng |
| Abstract: | This paper introduces and illustrates a new version of the Monte Carlo method that has attractive properties for the numerical valuation of derivatives. The traditional Monte Carlo method has proven to be a powerful and flexible tool for many types of derivatives calculations. Under the conventional approach pseudo-random numbers are used to evaluate the expression of interest. Unfortunately, the use of pseudo-random numbers yields an error bound that is probabilistic which can be a disadvantage. Another drawback of the standard approach is that many simulations may be required to obtain a high level of accuracy. |
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