中文 Tsinghua University Access to the old version Talent Recruitment
中文 Tsinghua University Access to the old version Talent Recruitment

Wang Xiaoqun

  • Professor
  • Tel:
  • Email: wangxiaoqun@mail.tsinghua.edu.cn
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Education

Ph.D.,St Petersburg State University，1995

Work Experience

Professor, Tsinghua University, date


Research Interests

XXX


Teaching

XXX


Selected Publications

  1. Zhijian He and Xiaoqun Wang. Convergence analysis of quasi-Monte Carlo sampling for quantile and expected shortfall. Mathematics of Computation, Vol. 90, No. 327, 303-319, 2021.

  2. Chaojun Zhang, Xiaoqun Wang, Zhijian He. Efficient importance sampling in quasi-Monte Carlo methods for computational finance. SIAM Journal on Scientific Computing,Vol. 43, No.1, B1-B29, 2021.

  3. Chengfeng Weng, Xiaoqun Wang and Zhijian He. Efficient computation of option prices and Greeks by quasi-Monte Carlo method with smoothing and dimension reduction. SIAM Journal on Scientific Computing, Vol. 39, No. 2, B298-B322, 2017.

  4. Xiaoqun Wang. Handling discontinuities in financial engineering: A good path simulation approach. Operations Research, Vol. 64, No. 2, 297-314, 2016.

  5. Zhijian He and Xiaoqun Wang. On the convergence rate of randomized quasi-Monte Carlo f for discontinuous functions, SIAM Journal on Numerical Analysis, Vol. 53, No. 5, 2488-2503, 2015.

  6. Zhijian He, Xiaoqun Wang, Good path generation methods in quasi-Monte Carlo for pricing financial derivatives, SIAM Journal on Scientific Computing, 2014，Vol. 36, No. 2, pp. B171-B197, 2014.

  7. Xiaoqun Wang and K. S. Tan. Pricing and hedging with discontinuous functions: quasi-Monte Carlo Methods and dimension reduction. Management Science, Vol. 59, No. 2, 376-389, 2013.

  8. Xiaoqun Wang. Enhancing quasi-Monte Carlo by exploiting additive approximation for problems in finance. SIAM Journal on Scientific Computing, Vol.34, No.1, A283-A308, 2012.

  9. Xiaoqun Wang and I. H. Sloan. Quasi-Monte Carlo methods in financial engineering: an equivalent principle and dimension reduction. Operations Research, Vol. 59, No. 1, 80-95, 2011.

  10. Xiaoqun Wang. Dimension reduction techniques in quasi-Monte Carlo methods for option pricing. INFORMS Journal on Computing, Vol. 21, No.3, 488-504, 2009.

  11. Xiaoqun Wang. Constructing robust lattice rules for computational finance. SIAM Journal on Scientific Computing, Vol. 29, No. 2, 598 - 621, 2007.

  12. Xiaoqun Wang. On the effects of dimension reduction techniques on some high-dimensional problems in finance. Operations Research, Vol.54, No.6, 1063-1078, 2006.

  13. Xiaoqun Wang and I. H. Sloan. Efficient weighted lattice rules with applications to finance. SIAM Journal on Scientific Computing, Vol. 28, No.2, 728-750, 2006.

  14. Dick, J., I. H. Sloan, Xiaoqun Wang and H. Wozniakowski. Good lattice rules in weighted spaces with general weights. Numerische Mathematik, Vol. 103, No. 1, 63-97, 2006.

  15. Xiaoqun Wang and I. H. Sloan. Why are high-dimensional finance problems often of low effective dimension. SIAM Journal on Scientific Computing, Vol. 27, No.1, 159-183, 2005.

  16. Xiaoqun Wang, I. H. Sloan and J. Dick. On Korobov lattice rules in weighted spaces. SIAM Journal on Numerical Analysis, Vol. 42, No. 4, 1760-1779, 2004.

  17. Xiaoqun Wang. Strong tractability of multivariate integration using quasi-Monte Carlo algorithms. Mathematics of Computation, 2003, Vol.72, No. 242, 823-838, 2003.

  18. Xiaoqun Wang and Kai-Tai Fang. The effective dimensions and quasi-Monte Carlo integration. Journal of Complexity, Vol. 19, No. 2, 101-124, 2003.

  19. Hickernell, F. J. and Xiaoqun Wang. The error bounds and tractability of quasi-Monte Carlo algorithms in infinite dimension. Mathematics of Computation, Vol. 71, No. 240, 1641-1661, 2002.