Academic Position

• Associate Professor, Center for Statistical Science, Tsinghua University, 12/2016 - present.

• Assistant Professor, Center for Statistical Science, Tsinghua University, 11/2015 – 12/2016.

• Assistant Professor, Yau Mathematical Sciences Center, Tsinghua University, 09/2013 – 10/2015.

Education

• Hong Kong University of Science and Technology, Hong Kong (2010)

• Academy of Mathematics and Systems Science, Chinese Academy of Sciences (2005)

• Qufu Normal University (2002)

Research and Visiting Experience

• 2019/07-2019/08 University of Hong Kong, Research Associate

• 2018/08-2018/08 University of Hong Kong, Research Associate

• 2017/08-2017/09, University of Hong Kong, Research Associate

• 2015/10-2015/10, Hong Kong University of Science and Technology, Visiting Scholar.

• 2013/02-2013/08, Hong Kong University of Science and Technology, Visiting Scholar.

• 2012/05-2012/05, London School of Economics & Political Science, Visiting Scholar.

• 2011/08-2013/02, University of Iowa, Post-doc Fellow.

• 2011/02-2011/07, Hong Kong University of Science and Technology, Post-doc Fellow.

• 2005/09-2006/05, Hong Kong University of Science and Technology, Research Assistant.

Research Interests

• Financial Econometrics

• Nonlinear Time Series Analysis

• Network and Big Data

Publications

• Luo, D., Zhu, K., Gong, H. and Li, D.^* (2021+). Testing error distribution by kernelized Stein discrepancy in multivariate time series models. Journal of Business & Economic Statistics.

• Jiang, F.Y., Li, D., Li, W.K. and Zhu, K. (2021+). Testing and modelling for the structural change in covariance matrix time series with multiplicative form. Statistica Sinica.

• Li, D., Li, M. and Zeng, L. (2021+). Simulation and application of subsampling for threshold autoregressive moving-average models, Communications in Statistics: Simulation and Computation.

• Sun, L.Y. and Li, D.^* (2021). Change-point detection for expected shortfall in time series. Journal of Management Science and Engineering 6, 324-335.

• Jiang, F.Y., Li, D. and Zhu, K. (2021). Adaptive inference for a semiparametric GARCH model. Journal of Econometrics 224, 306-329.

• Jiang, F.Y., Li, D. and Zhu, K. (2020). Non-standard inference for augmented double autoregressive models with null volatility coefficients. Journal of Econometrics 215, 165-183.

• Li, D. and Tong, H. (2020). On an absolute autoregressive model and skew symmetric distributions. Statistica 80, 177-198.

• Zhou, J., Li, D., Pan, R. and Wang, H. S. (2020). Network GARCH model. Statistica Sinica 30, 1723-1740.

• Gong, H. and Li, D.^* (2020). On the three-step non-Gaussian quasi-maximum likelihood estimation of heavy-tailed double AR models. Journal of Time Series Analysis 41, 883-891.

• Li, D.^* and Qiu, J.M. (2020). The marginal density of a TMA (1) process. Journal of Time Series Analysis 41, 476-484.

• Yang, Y. and Li, D.^* (2020). Self-weighted LAD-based inference for heavy-tailed continuous threshold autoregressive models. Journal of Time Series Analysis 41,163-172.

• Li, D. and Zhu, K. (2020). Inference for asymmetric exponentially weighted moving average models. Journal of Time Series Analysis 41,154-162.

• Guo, S., Li, D. and Li, M.Y. (2019). Strict stationarity testing and GLAD estimation of double autoregressive models. Journal of Econometrics 211, 319-337.

• Li, D., Guo, S. and Zhu, K. (2019). Double AR model without intercept: An alternative to modeling nonstationarity and heteroscedasticity. Econometric Reviews 38, 319-331.

• Li, D., Ling, S., Tong, H. and Yang, G.R. (2019). On Brownian motion approximation of compound Poisson processes with applications to threshold models. Advances in Decision Sciences 23. Bridging.pdf

• Li, D. and Wu, W. (2018). Renorming volatilities in a family of GARCH models. Econometric Theory 34, 1370-1382.

• Liu, F., Li, D.* and Kang, X.M. (2018). Sample path properties of an explosive double AR model. Econometric Reviews 37, 484-490.

• Li, D., Zhang, X., Zhu, K. and Ling, S. (2018). The ZD-GARCH model: A new way to study heteroscedasticity. Journal of Econometrics 202, 1-17.

• Li, D. and Tong, H. (2016). Nested sub-sample search algorithm for estimation of threshold models. Statistica Sinica 26, 1543-1554.

• Li, D., Ling, S. and Zhang, R.M. (2016). On a threshold double autoregressive model. Journal of Business & Economic Statistics 34, 68-80.

• Li, D., Ling, S. and Zakoïan, J.-M. (2015). Asymptotic inference in multiple-threshold double autoregressive models. Journal of Econometrics 189, 415-427.

• Li, D., Li, M. and Wu, W. (2014). On dynamics of volatilities in nonstationary GARCH models. Statistics and Probability Letter 94, 86-90.

• Chen, M., Li, D.^* and Ling, S. (2014). Non-stationarity and quasi-maximum likelihood estimation on a double autoregressive model. Journal of Time Series Analysis 35, 189-202.

• Chan, K.S., Li, D., Ling, S. and Tong, H. (2014). On conditionally heteroscedastic AR models with thresholds. Statistica Sinica 24, 625-652.

• Li, D. (2014). Weak convergence of the sequential empirical processes of residuals in TAR models. Science China: Mathematics 57, 173-180.

• Li, D., Chan, K.S. and Schilling, K.E. (2013). Nitrate concentration trends in Iowa’s rivers, 1998 to 2012: What challenges await nutrient reduction initiatives? Journal of Environmental Quality 4, 1822-1828.

• Li, D., Ling, S. and Li, W. K. (2013). Asymptotic theory on the least squares estimation of threshold moving-average models. Econometric Theory 29, 482-516.

• Wu, W., Li, D., Pan, S. and Chen, M. (2013) Three-regime mean reversion, TAR and its applications. Systems Engineering - Theory & Practice 33, 901-909.

• Li, D. (2012). A note on moving-average models with feedback. Journal of Time Series Analysis 33, 873-879.

• Li, D., Ling, S. and Tong, H. (2012). On moving-average models with feedback. Bernoulli 18, 735-745.

• Li, D. and Ling, S. (2012). On the least squares estimation of multiple-regime threshold autoregressive models.  Journal of Econometrics 167, 240-253

• Li, D., Li, W. K. and Ling, S. (2011). On the least squares estimation of threshold autoregressive and moving-average models. Statistics and Its Interface 4, 183-196.

• Ling, S. and Li, D. (2008). Asymptotic inference for a non-stationary double AR(1) model. Biometrika 95, 257-263.

• Ling, S., Tong, H. and Li, D. (2007). Ergodicity and invertibility of threshold moving-average models. Bernoulli 13, 161-168.

Submitted Paper

• Li, D. (2021). Quasi-maximum likelihood estimation in a simple random-coefficient nonlinear AR model.

• Jiang, F.Y., Li, D., Li, W.K. and Zhu, K. (2021). Testing and modelling for the structural change in covariance matrix time series with multiplicative form.

• Zhang, X., Li, D.* and Tong, H. (2021). On the LSE of k-threshold-variable AR models.

• Zhang, X. and Li, D.* (2021). Smooth transition MA model: Estimation and testing.

• Yang, X. and Li, D.* (2021). DAAR model: An alternative to GARCH-in-mean model.

• Tao, Y. and Li, D.*(2021). The dynamic duality between normal and skew-normal distributions.

Teaching

• Graduate courses

• Time Series Analysis. (2017/Spring)

• Advanced Probability Theory I. (2016-21/Fall)

• Multivariate Statistical Analysis. (2014, 2015/Spring)

• Advanced Mathematical Statistics. (2014/Fall)

• Undergraduate courses

• Applied Time Series Analysis. (2017, 2018，2020/Spring)

• Elementary Probability Theory. (2016/Fall)

• Introduction to Statistics. (2018/Fall, 2020-21/Spring with Dr. K. Deng)

• Financial Statistics. (2017, 2019/Spring)

• Multivariate Statistical Analysis.（2021/Spring）

Service

• Council member of Beijing Applied Statistic Association

• 中国现场统计研究会计算统计分会理事

• 全国工业统计学教学研究会常务理事【12-2022.12】

• 中国青年统计学家协会常务理事【4-2023.4】

Organizing Conference

• Co-organizer, the international conference on Complex Time Series Modelling and Forecasting: Dynamic Network, Spatio-temporal Data, and Functional Processes, Tsinghua-Sanya International Mathematics Forum, Jan. 8-12, 2018. (with Professor Marc Genton at KAUST, Professor Eric D. Kolaczyk at Boston University, and Professor Qiwei Yao at the LSE)

• Organizer, Mini workshop on Big Data and Internet Finance, Tsinghua University, Dec. 18, 2016.

• Co-organizer, 2016 Tsinghua Symposium on Statistics and Data Science for Young Scholars, Tsinghua University, Dec. 9-11, 2016. (with Ke Deng and Lin Hou)

• Co-organizer, the international conference on Time Series Econometrics, Tsinghua-Sanya International Mathematics Forum, Dec. 18-20, 2015. (with Professor Shiqing Ling at HKUST and Professor Chuanzhong Chen at Hainan Normal University)

Journal Reviewing

• Applied Stochastic Models in Business and Industry，Annals of Statistics，Biometrika，Colombian Journal of Statistics，Communications in Statistics - Simulation and Computation，Computational Statistics & Data Analysis，European Journal of Industrial Engineering，Econometric Theory，Journal of Business & Economic Statistics, Journal of Econometrics，Journal of the Korean Statistical Society， Journal of Risk and Financial Management，Metrika，Statistica Sinica，Stochastic Environmental Research and Risk Assessment，Statistics & Probability Letters，Test.

Funding

• Network-based analysis of high-dimensional time series. NSFC, 2018/01-2021/12, PI.

• A study on some hypothesis testing problems in time series analysis. NSFC, 2016/01-2019/12, Co-PI.

• Conditional heteroscedastic models with stable innovations: statistical inference and their applications. NSFC, 2015/01-2018/12. PI.

• Curriculum Vitae：CV.pdf

• Essentially, all models are wrong, but some are useful. —— Box, G. P.

• When solving a given problem, try to avoid solving a more general problem as an intermediate step. —— Vapnik, V.