Ruodu Wang

Associate Professor; University Research Chair

Ruodu WangContact Information:
Office: M3 3122
Phone: 519-888-4567, ext. 31569
Email: wang@uwaterloo.ca

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 model uncertainty
  • systemic risk
  • risk sharing and market equilibria
  • decision theory
  • risk measures
  • risk aggregation
  • dependence modeling and copulas
  • probabilistic combinatorics
  • robust statistics

Education/biography

  • 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

  • Embrechts, P., Liu, H., Mao, T. and Wang, R. (2018). Quantile-based risk sharing with heterogeneous beliefs. Mathematical Programming, forthcoming.
  • 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 Research41(3), 808-826.
  • Embrecths, P., Hofert, M. and Wang, R. (2016). Bernoulli and tail-dependence compatibility. Annals of Applied Probability26(3), 1636–1658.
  • Puccetti, G. and Wang, R. (2015). Extremal dependence concepts. Statistical Science30(4), 485–517.
  • Embrechts, P., Wang, B. and Wang, R. (2015). Aggregation-robustness and model uncertainty of regulatory risk measures. Finance and Stochastics19(4), 763–790.
  • Wang, R., Bignozzi, V. and Tsanakas, A. (2015). How superadditive can a risk measure be? SIAM Journal on Financial Mathematics6(1), 776–803.
  • Bernard, C., Jiang, X. and Wang, R. (2014). Risk aggregation with dependence uncertainty. Insurance: Mathematics and Economics54, 93–108.
  • Zhang, R., Peng, L. and Wang, R. (2013). Tests for covariance matrix with fixed or divergent dimension. Annals of Statistics41(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 Stochastics17(2), 395–417.
  • Wang, B. and Wang, R. (2011). The complete mixability and convex minimization problems for monotone marginal distributions. Journal of Multivariate Analysis102(10), 1344–1360.
Affiliation: 
University of Waterloo
Contact information: