Dong Li-永利赌场-永利在线赌场网址

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Dong Li Associate Professor

Research Areas:financial econometrics, nonlinear time series analysis, network and big data

Office: Room 203-B, Weiqing Building

Phone: +86-10-62780177

Email: [email protected]

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 42, 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
全国工业永利赌场教学研究会常务理事【12-2022.12】
中国青年永利赌场家协会常务理事【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.

职称	Associate Professor	地址	Room 203-B, Weiqing Building
电话	+86-10-62780177	邮箱	[email protected]
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