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Yang, Yaxing

Associate Professor

Hong Kong University of Science and Technology

Phone：

Email：yyangaj@connect.ust.hk

Office：

Office Hours:

Research Fields:

Homepage:



Professor Associate Professor Phone
Email yyangaj@connect.ust.hk Office
Office Hours Research Fields
Homepage Job Hong Kong University of Science and Technology

个人简介 研究成果 研究项目

 

 

Research interests:

Financial Econometrics,
Nonlinear time series analysis.
 
Education:
Ph.D. in Statistics, Hong Kong University of Science and Technology, 2016.
M.Phil. in Probability and Mathematical Statistics, Hainan Normal University, China, 2012.
B.S. in Mathematics, Hainan Normal University, China, 2009.
Li D., Tao Y.,  Yang Y. and  Zhang R. (2023). Maximum likelihood estimation for alpha-stable double autoregressive  models.   Journal of Econometrics, Accepted.
 
Yang Y., Ling S. and  Wang Q. (2022). Consistency of global LSE for MA(1) models. Statistics & Probability Letters.182, 1-8.
 
Ling S.,  Tsay R. and   Yang Y. (2021). Testing serial correlation and ARCH effect of high-dimensional time series data.  Journal of Business & Economic Statistics. 39,136-147.
 
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.
 
Yang Y. and Ling S. (2018). A note on the LSE of three regime TAR model with an infinite variance. Annals of Financial Economics. 13(02), 1-13.
 
Yang Y. and Ling S. (2017). Inference for heavy-tailed and multiple-threshold double autoregressive models.  Journal of Business & Economic Statistics. 35, 318-333. 
 
Yang Y. and Ling S. (2017). Self-weighted LAD-based inference for heavy-tailed threshold autoregressive models.  Journal of Econometrics. 197(2),368-381.
 
Tai M., Yang Y. and Ling S. (2016). Diagnostic checking of partially nonstationary multivariate AR and ARMA models.  Advances in Time Series Methods and Application （Part of the Fields Institute Communications book series,78,115-130.

 

国家自然科学基金青年科学基金项目：连续型门限模型的统计推断及应用, 2019-2021。

福建省自然科学基金面上项目：一类门限波动率模型的统计推断研究，2019-2021。