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Ruodu Wang

Associate Professor; University Research Chair

Ruodu WangContact Information:
Office: M3 3122
Phone: 519-888-4567, ext. 31569

Ruodu Wang's personal website

Research interests

Professor Wang's research interests mainly lie in quantitative risk management, which includes various topics in actuarial science, financial engineering, operations research, probability theory, and statistics.

His current specific research topics include:

  • Risk, ambiguity and uncertainty
  • Dependence modeling and copulas
  • Risk measures
  • Decision theory
  • Mass transportation
  • General equilibria
  • FinTech/InsurTech
  • Systemic risk
  • Risk aggregation
  • Probabilistic combinatorics
  • Non-convex optimization
  • Robust methods for finance
  • Hypothesis testing
  • High-dimensional data analysis


  • 2012 PhD (Mathematics) Georgia Institute of Technology, U.S.A. Advisor: Liang Peng.
  • 2009 MS (Financial Mathematics) Peking University, China.
  • 2006 BS (Mathematics) Peking University, China.

Professor Wang works in the Department of Statistics and Actuarial Science at the University of Waterloo as Assistant Professor (2012 - 2017), Associate Professor (2017 - present) and University Research Chair (2018 - present).  He serves as a Co-Editor of the European Actuarial Journal (2016 - present) and a Co-Editor of ASTIN Bulletin - The Journal of the International Actuarial Association (2018 - present), and is an affiliated member of RiskLab at ETH Zurich, Switzerland (2015 - present). He received the inaugural Golden Jubilee Research Excellence Award from the Faculty of Mathematics at Waterloo (2017) and the Discovery Accelerator Award from the Natural Sciences and Engineering Research Council of Canada (2018).

Selected publications

  • Wang, R. and Zitikis, R. (2020). An axiomatic foundation for the Expected Shortfall. Management Science, forthcoming.
  • Liu, F. and Wang, R. (2020). A theory for measures of tail risk. Mathematics of Operations Research, forthcoming.
  • Mao, T. and Wang, R. (2020). Risk aversion in regulatory capital principles. SIAM Journal on Financial Mathematics, forthcoming.
  • Vovk, V. and Wang, R. (2020). Combining p-values via averaging. Biometrika, forthcoming.
  • Wang, R., Wei, Y. and Willmot, G. (2020). Characterization, robustness and aggregation of signed Choquet integrals. Mathematics of Operations Research, forthcoming.
  • Wang, R., Xu, Z. Q. and Zhou, X. Y. (2019). Dual utilities under dependence uncertainty. Finance and Stochastics, 23(4), 1025-1048.
  • Asimit, V., Peng, L., Wang, R. and Yu, A. (2019). An efficient approach to quantile capital allocation and sensitivity analysis. Mathematical Finance, 29(4), 1131-1156.
  • Shen, J., Shen, Y., Wang, B. and Wang, R. (2019). Distributional compatibility for change of measures. Finance and Stochastics, 23(3), 761-794.
  • Embrechts, P., Liu, H., Mao, T. and Wang, R. (2018). Quantile-based risk sharing with heterogeneous beliefs. Mathematical Programming, published online.
  • Embrechts, P., Liu, H. and Wang, R. (2018). Quantile-based risk sharing. Operations Research, 66(4), 936-949.
  • Li. L., Shao, H., Wang, R. and Yang, J. (2018). Worst-case Range Value-at-Risk with partial information. SIAM Journal on Financial Mathematics, 9(1), 190-218.
  • Cai, J., Liu, H. and Wang, R. (2018). Asymptotic equivalence of risk measures under dependence uncertainty. Mathematical Finance, 28(1), 29-49.
  • Furman, E., Wang, R. and Zitikis, R. (2017). Gini-type measures of risk and variability: Gini shortfall, capital allocations, and heavy-tailed risks. Journal of Banking and Finance, 83, 70-84.
  • Bernard, C., Rüschendorf, L., Vanduffel, S. and Wang, R. (2017). Risk bounds for factor models. Finance and Stochastics, 21(3), 631-659.
  • Wang, B. and Wang, R. (2016). Joint mixability. Mathematics of Operations Research, 41(3), 808-826.
  • Embrecths, P., Hofert, M. and Wang, R. (2016). Bernoulli and tail-dependence compatibility. Annals of Applied Probability, 26(3), 1636-1658.
  • Puccetti, G. and Wang, R. (2015). Extremal dependence concepts. Statistical Science, 30(4), 485-517.
  • Embrechts, P., Wang, B. and Wang, R. (2015). Aggregation-robustness and model uncertainty of regulatory risk measures. Finance and Stochastics, 19(4), 763-790.
  • Wang, R., Bignozzi, V. and Tsanakas, A. (2015). How superadditive can a risk measure be? SIAM Journal on Financial Mathematics, 6(1), 776-803.
  • Bernard, C., Jiang, X. and Wang, R. (2014). Risk aggregation with dependence uncertainty. Insurance: Mathematics and Economics, 54, 93-108.
  • Zhang, R., Peng, L. and Wang, R. (2013). Tests for covariance matrix with fixed or divergent dimension. Annals of Statistics, 41(4), 2075-2096.
  • Wang, R., Peng, L. and Yang, J. (2013). Bounds for the sum of dependent risks and worst Value-at-Risk with monotone marginal densities. Finance and Stochastics, 17(2), 395-417.
  • Wang, B. and Wang, R. (2011). The complete mixability and convex minimization problems for monotone marginal distributions. Journal of Multivariate Analysis, 102(10), 1344-1360.
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