Research

Publications in refereed journals:

1.  Chen, L., Li, D. and Zhang, Z. (2026+). Systemic and systematic risks driven marginal expected shortfall. JASA, in press.

2.  Zhong, Q., Ji, J., Chen, L., Hou, Y. and Li, D. (2028). Inference for a two-step joint model of extreme quantile and expected shortfall regression. Statistica Sinica, in press.

3.   Chen, L., Li, D. and Zhou, C. (2027). Distributed inference for tail risks. Statistica Sinica, in press.

4.   Chen, L. and Zeng, J. (2027). Dimension reduction for extreme tail regression via contour projection. Statistica Sinica, in press.

5.  Wang, Z., Chen, L. and Li, D. (2027). Estimation of tail gini functional under asymptotic independence. Statistica Sinica, in press.

6.   Zhang T., Chen, L. and Ji, J. (2024). Estimation of expectile based marginal expected shortfall under asymptotic independence. Stat, 13(4), 1-11. 

7. Li, Y., Chen, L., Li, D. and Wang, H. (2024). Estimating extreme value index by subsampling for massive datasets with heavy-tailed distributions. Statistics and Its Interface, 17(4):605-622.

8. Chen, L., Li, D. and Zhou, C. (2022). Distributed inference for extreme value index. Biometrika, 109(1), 257-264. 

9.  Chen, L., Li, D. and Zhou, C. (2022). Adapting the Hill estimator to distributed inference: dealing with the bias.  Extremes,  25:389-416.

Working Papers:

1.  Chen, L. and Zhou, C. (2026+). High dimensional inference for extreme value indices. 

2. Chen, L., Oesting, M. and Zhou, C. (2026+). Tail Clustering in high dimensions. 

3. Chen, L. and Zhou, C. (2026+). High-dimensional inference for shrinkage variables with applications to value-at-risk backtest. 

4. Chen, L., Li, D. and Zhou, C. (2026+). Distributed inference for multivariate extremes. 

5. Chen, L., Li, D. and Zhang Z. (2026+). Tail max-linear regression. 

6. Miao, Z., Chen, L. and Li, D. (2026+). CTE2: Conditional tail expectation treatment effect. 

7. Miao, Z., Chen, L. and Li, D. (2026+). A unified framework for extremal quantile treatment effects.