Deterministic simulation for risk management: Quasi-Monte Carlo beats Monte Carlo for value at risk

Journal of Portfolio Management

Volumn 25, Issue SUPPL., 1999, Pages 122-127

  Papageorgiou, Anargyros ^a   Paskov, Spassimir ^b  

^a Columbia University ^*  (United States)

^b Federal Service for Surveillance on Consumer Rights Protection and Human Well Being   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 20144385376     PISSN: 00954918     EISSN: None     Source Type: Journal    
DOI: 10.3905/jpm.1999.319698     Document Type: Article

References (9)

1. Jorion, P. Value at Risk. New York: McGraw-Hill, 1997.
2. Niederreiter, H. "Random Number Generation and Quasi-Monte Carlo Methods." SIAM, CBMS-NSF, 1992.
3. Ninomiya, S., and S. Tezuka. "Toward Real-Time Pricing of Complex Financial Derivatives." Appl. Math. Finance, 3, 1996, pp. 1-20.
4. Papageorgiou, A., and J.F. Traub. "Beating Monte Carlo." Risk, 9:6 (1996), pp. 63-65.
5. Paskov, S. "New Methodologies for Valuing Derivatives." In M. Dempster and S. Pliska eds., Mathematics of Derivative Securities. Cambridge: Cambridge University Press, 1997, pp. 545-582.
6. Paskov, S., and J.F. Traub. "Faster Valuation of Financial Derivatives. "Journal of Portfolio Management, Fall 1995, pp. 113-120.
7. Sloan, I., and H. Wozniakowski. "When Are Quasi-Monte Carlo Algorithms Efficient for High Dimensional Integrals?" J. Complexity, 4 (1998), pp. 1-33.
8. Stuart, A., and J.K. Ord. Kendall's Advanced Theory of Statistics. Volume 1, Distribution Theory. New York: Halsted Press, 1994.
9. Tezuka, S. Uniform Random Numbers: Theory and Practice. Boston: Kluwer Academic Publishers, 1995.