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Liang Peng

Professor    
Education
  • Ph.D. in probability and mathematical statistics, Erasmus University Rotterdam
  • M.S. in probability, Peking University
  • B.S. in mathematics, Zhejiang University
Specializations
  • Extreme value theory in finance and environmental sciences
  • Nonparametric statistics
  • Heavy tailed, long-range dependent and nonlinear time series
  • Empirical likelihood methods
  • Copula and tail copula in risk management
  • Continuous-time stochastic processes in finance
Biography

Liang Peng is a professor of risk management and insurance in the Robinson College of Business at Georgia State University. He received his Ph.D. in statistics at Erasmus University Rotterdam, the Netherlands in 1998. He is a fellow of both Institute of Mathematical Statistics and American Statistical Association. His research interests include extreme value theory, nonparametric statistics and time series analysis with particular applications in finance, insurance and risk management.

Publications
  • Deyuan Li, Ngaihang Chan and Liang Peng (2014). Empirical likelihood test for causality for bivariate AR(1) processes. Econometric Theory 30, 357–371.
  • Liang Peng, Yongcheng Qi and Fan Wang (2014). Empirical likelihood method for high dimensional means. Statistical Science 29, 113–127.
  • Fukang Zhu, Zongwu Cai and Liang Peng (2014). Predictive regressions for macroeconomic data. Annals of Applied Statistics 8, 577–594.
  • Rongmao Zhang, Liang Peng and Ruodu Wang (2013). Tests for covariance matrix with fixed or divergent dimension. Ann. Statist. 41, 2075–2096.
  • Ngaihang Chan, Deyuan Li, Liang Peng and Rongmao Zhang (2013). Tail index of an AR(1) model with ARCH(1) errors. Econometric Theory 29, 920–940.
  • Ruodu Wang, Liang Peng and Jingping Yang (2013). Jackknife empirical likelihood for parametric copulas. Scandinavian Actuarial Journal 5, 325–339.
  • Ruodu Wang, Liang Peng and Jingping Yang (2013). Bounds for the sum of dependent risks and worst Value-at-Risk with monotone marginal densities. Finance and Stochastics 17, 395–417.
  • Ngaihang Chan, Deyuan Li, Liang Peng and Rongmao Zhang (2013). Tail index of an AR(1) model with ARCH(1) errors. Econometric Theory 29, 920–940.
  • Liang Peng, Yongcheng Qi, Ruodu Wang and Jingping Yang (2012). Jackknife empirical likelihood methods for risk measures and related quantities. Insurance: Mathematics and Economics 51, 142–150.
  • Ruodu Wang and Liang Peng (2011). Jackknife empirical likelihood intervals for Spearman’s rho. North American Actuarial Journal 15, 475–486.
  • Liang Peng (2010). A practical way for estimating tail dependence functions. Statistica Sinica 20, 365–378.
  • Ngaihang Chan, Songxi Chen, Liang Peng and Cindy Yu (2009). Empirical likelihood methods based on characteristic functions with applications to L’evy processes. Journal of the American Statistical Association 104, 1621–1630.
  • Liang Peng (2008). Estimating the probability of a rare event via elliptical copulas. Northern American Actuarial Journal 12(2), 116–128.
  • Mingyen Cheng and Liang Peng (2007). Variance reduction in multivariate likelihood models. Journal of The American Statistical Association 102(477), 293 – 304.