在金融数学和统计学及其交叉领域取得一系列创新性研究成果。发展“有效维数”的概念，并率先给出高维金融问题有效维数的分析与计算方法，对深化高维金融计算复杂性的认识具有明确的指示意义；提出新的降维策略及函数光滑化方法，发展高效、实时的资产定价和金融风险定量分析算法，有效克服高维计算中“维数的灾难”和函数间断性困难，显著提高计算效率和准确性，拓展方法的适用性；首次用构造性方法证明高维积分的“强可计算性”及最优收敛阶，解决复杂性领域重要的公开问题；本质拓展“加权函数空间”理论，提出“有限阶权重”的概念，并提出构造高维空间中高质量“低偏差点列”的新方法，具有重要的金融应用。
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.
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.
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.
Xiaoqun Wang. Handling discontinuities in financial engineering: A good path simulation approach. Operations Research, Vol. 64, No. 2, 297-314, 2016.
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.
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.
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.
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.
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.
Xiaoqun Wang. Dimension reduction techniques in quasi-Monte Carlo methods for option pricing. INFORMS Journal on Computing, Vol. 21, No.3, 488-504, 2009.
Xiaoqun Wang. Constructing robust lattice rules for computational finance. SIAM Journal on Scientific Computing, Vol. 29, No. 2, 598 - 621, 2007.
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.
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.
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.
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.
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.
Xiaoqun Wang. Strong tractability of multivariate integration using quasi-Monte Carlo algorithms. Mathematics of Computation, 2003, Vol.72, No. 242, 823-838, 2003.
Xiaoqun Wang and Kai-Tai Fang. The effective dimensions and quasi-Monte Carlo integration. Journal of Complexity, Vol. 19, No. 2, 101-124, 2003.
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.
