孔新兵
孔新兵
发布时间:2017-03-11 浏览次数:

 

               

姓名 孔新兵

职称教授                                   

研究领域经济统计、数理统计、网络数据统计

教育背景香港科技大学、博士、2007-2011

          兰州大学、硕士及本科、2000-2007

工作经历南京审计大学、理学院/统计与大数据研究院、教授、20173-至今;

苏州大学、数学学院/高等统计与计量经济研究中心、教授、20148-20172月; 

复旦大学、管理学院、副教授及助理教授、20117-20147月。

课题主持自然科学基金面上、青年项目各1项;教育部人文社科项目1项。

论文

(1)工作论文

1. Kong Xin-Bing, Liu Cheng (2017). Testing against constancy of the factor loadings using large panel high-frequency data. Under Revision.

2. Kong Xin-Bing (2017). Testing for infinite variation jumps using high-frequency data. Under Revision.

3. Kong Xin-Bing, Liu Zhi, Zhou Wang (2017). A central limit theorem on the number of factors with high-frequency data. Under Revision.

4. Kim, Donggyu, Kong Xin-Bing, Li, Cuixia, Wang Yazhen (2017). Adaptive thresholding estimator of the large dimensional integrated volatility matrix. Under Revision.

5. Kong Xin-Bing (2017). On the integrated idiosyncratic and systematic volatility with the large panel high-frequency data. Under Revision.

(2) 发表论文

1. Kong Xin-Bing (2017). How many common driving processes underlying large panel high-frequency data. Biometrika. To appear

2. Cai Zong-Wu, Kong Xin-Bing, Jing Bing-Yi, Liu Zhi (2017). Nonparametric regression with nearly integrated regressor under long run dependence. Econometrics Journal. To appear

3. Kong Xin-Bing, Liu Zhi, Zhou Wang (2017). Sure screening via ranking canonical correlations. TEST. To appear

4. Jing Bing-Yi, Liu Zhi, Kong Xin-Bing (2017). Estimating volatility functional with multiple transactions. Econometric Theory. To appear

5. Kong Xin-Bing, Xu Qin-Feng (2015). On false discovery and non-discovery proportions of the dynamic adaptive procedure under dependence. Scandinavian Journal of Statistics Vol. 42, 530-544.

6. Kong Xin-Bing, Liu Zhi, Jing Bing-Yi (2015). A new test for pure-jump processes underlying high frequency data. Annals of Statistics Vol. 43, 847-877.

7. Jing Bing-Yi, Kong Xin-Bing, Zhou Wang (2014). FDR control under nonnormality. (2014). Statistica Sinica. Vol. 24, 1879-1899.

8. Jing Bing-Yi, Liu Zhi, Kong Xin-Bing (2014). Estimating volatility functional with infinitely active jumps. Journal of Business and Economic Statistics. Vol. 32, 457-467.

9. Kong Xin-Bing (2013). A direct estimation approach to risk approximation for vast portfolios under gross-exposure constraint. TEST 22, 647-669.

10. Jing Bing-Yi, Kong Xin-Bing, Liu Zhi (2012). Modeling high frequency data by pure jump processes? Annals of Statistics, 40, 759-784.

11. Jing Bing-Yi, Kong Xin-Bing, Liu Zhi, Per Mykland (2012).On the jump activity index for semimartingales. Journal of Econometrics 166, 213-223.

12. Jing Bing-Yi, Kong Xin-Bing, Liu Zhi (2011). Estimating the jump activity index under noisy observations using high frequency data. Journal of the American Statistical Association 106, 558-568.

所授课程《多元分析》、《时间序列》、《金融工程导论》、《概率论于数理统计》、《高等数理统计III》。

荣誉国际统计协会(ISI)当选会员;江苏省“双创博士”;香港数学会“最佳博士论文奖”;复旦大学管理学院年度“青年新星奖”。

学术兼职现场统计研究会高维统计分会理事。