Associate Professor Yanrong Yang

Yanrong Yan


Research School of Finance, Actuarial Studies & Statistics

Associate Professor
Phone number
+61 2 612 58975
Room 3.39, CBE Bld (26C)
Research areas

High Dimensional Statistics; Large Panel Data Analysis; Large Dimensional Random Matrix Theory; Functional Data Analysis.


Yanrong Yang is an Associate Professor of Statistics. Yanrong’s research interests include high dimensional statistical inference and large dimensional random matrix theory. She has established new asymptotic theory for high dimensional statistics and applied her theory to forecasting high dimensional time series and large panel data. Yanrong has published in leading journals in statistics and actuarial science including Annals of Statistics, Journal of the Royal Statistical Society: Series BJournal of the American Statistical Association, Journal of Econometrics, Econometric Theory, Annals of Applied Statistics, Statistica Sinica, Electronic Journal of Probability, Journal of Multivariate Analysis, Insurance: Mathematics and Economics, Economics Letters, Australian and New Zealand Journal of Statistics, and Journal of Computational Finance.    

Google Scholar

Research publications

Journal Articles

[15] Bin Peng, Liangjun Su, Joakim Westerlund, Yanrong Yang. (2023). Interactive effects panel data models with general factors and regressors. Econometric Theory. To appear.

[14] Lingyu He, Yanrong Yang, Bo Zhang (2022). Robust PCA for high-dimensional data based on characteristic function. Under Review. Australian and New Zealand Journal of Statistics. Accepted.  

[13] Qingliang Fan, Ruike Wu, Yanrong Yang, Wei Zhong. (2022). Time-varying minimum variance portfolio. Journal of Econometrics. To appear.

[12] Yuan Gao, Han Lin Shang, Yanrong Yang (2022). Factor-augmented smoothing model for functional data. Statistica Sinica. To appear.

[11] Chen Tang, Han Lin Shang, Yanrong Yang (2022). Clustering and forecasting multiple functional time series. Annals of Applied Statistics. 16(4), 2523 - 2553.  

[10] Yang Yang, Yanrong Yang, Han Lin Shang (2021). Feature extraction for functional time series: theory and application to NIR spectroscopy data. Journal of Multivariate Analysis. 189, 104863.

[9] Xiaoyi Han, Bin Peng, Yanrong Yang, Huanjun Zhu (2021). Shrinkage estimation of the varying-coefficient model with continuous and categorical covariates. Economics Letters. 202, 109819. 

[8] Jianjie Shi, Lingyu He, Fei Huang, Yanrong Yang (2021). Mortality forecasting: time-varying or constant factor loadings? Insurance: Mathematics and Economics. 98, 14-34. 

[7] Bin Jiang, Yanrong Yang, Jiti Gao, Cheng Hsiao (2021). Recursive estimation in large panel data models: theory and practice. Journal of Econometrics. 224(2) 439-465.

[6] Yuan Gao, Hanlin Shang, Yanrong Yang (2019). High dimensional functional time series analysis: an application to age-specific mortality rates. Journal of Multivariate Analysis. 170, 232-243.

[5] Jiti Gao, Xiao Han, Guangming Pan, Yanrong Yang (2017). High dimensional correlation matrices: CLT and its applications. Journal of the Royal Statistical Society: Series B. 79(3) 677-693.

[4] Yanrong Yang, Guangming Pan (2015). Independence test for high dimensional data based on regularized canonical correlation coefficients. Annals of Statistics. 43(2) 467-500.

[3] Guangming Pan, Jiti Gao, Yanrong Yang (2014). Test independence among a large number of high dimensional random vectors. Journal of the American Statistical Association. 109(506) 600-612.

[2] Yanrong Yang, Guangming Pan (2012). The convergence of the empirical distribution of canonical correlation coefficients. Electronic Journal of Probability. 17(64) 1-13.

[1] Haifeng Fu, Xin Jin, Guangming Pan, Yanrong Yang (2012). Estimating multiple option greeks simultaneously using random parameter regression. Journal of Computational Finance. 16(2), 85-118.

Book Chapters

[2] Gao, Yuan, Shang, Han Lin, Yang, Yanrong (2020). ‘Modelling functional data with high-dimensional error structure’, Functional and High-Dimensional Statistics and Related Fields, Springer, pp. 99-106

[1] Gao, Yuan, Shang, Han Lin, Yang, Yanrong (2017). ‘High-dimensional functional time series forecasting’, Functional Statistics and Related Fields, Springer, pp. 131-136


Under Review

[7] Daning Bi, Le Chang, Yanrong Yang (2022). Homogeneity and sub-homogeneity pursuit: iterative complement clustering PCA. . 

[6] Daning Bi, Xiao Han, Adam Nie, Yanrong Yang (2022). Spiked eigenvalues of high-dimensional sample auto-covariance matrices: CLT and its applications. , Under Review.  

[5] Daning Bi, Han Lin Shang, Yanrong Yang, Huanjun Zhu. (2021). AR-sieve bootstrap for high-dimensional time series. Under Review. 

[4] Chen Tang, Han Lin Shang, Yanrong Yang. (2021). Multi-population mortality forecasting using high-dimensional functional factor models. Under Review.

[3] Lingyu He, Fei Huang, Yanrong Yang. (2020). A forecast-driven hierarchical factor model with application to mortality data. Under Revision. 

[2] Bo Zhang, Jiti Gao, Guangming Pan, Yanrong Yang. (2020). Spiked eigenvalues of high-dimensional separable sample covariance matrices. Under Revision.

[1] Jiti Gao, Guangming Pan, Yanrong Yang, Bo Zhang. (2019). Estimation of cross-sectional dependence in large panels. Under Revision. 

Working Papers:

[3] Qingliang Fan, Ruike Wu, Yanrong Yang (2022). Robust minimum variance portfolio for a large universe of assets.  

[2] Yonghe Lu, Haijun Gong, Yanrong Yang, Bo Zhang. (2022). Change-point analysis for graphical modelling on ultra high-dimensional nonstationary time series. 

[1] Yuan Gao, Han Lin Shang, Yang Yang, Yanrong Yang. (2022). Factor analysis for functional time series: cross-sectional dependence or temporal dependence?



Research grants and awards

ARC DP230102250 (with Hanlin Shang, Degui Li, Xinghao Qiao and Qingliang Fan): 2023 - 2025

Title: Feature learning for high-dimensional functional time series



Research engagement and outreach

PhD Supervision (completion, as primary supervisor)

Yang Yang (2016 - 2020): Modelling and Forecasting for Functional Time Series 

Lingyu He (2016 - 2020): Data-adaptive Principal Component Analysis for High Dimensional Data

Yuan Gao (2015 - 2020): Modelling and Forecasting for High-dimensional Functional Data

Daning Bi (2016 - 2021): Various Statistical Inferences for High-dimensional time series: Bootstrap, Homogeneity Pursuit and  

                                        Auto-covariance Test

Chen Tang (2016 - 2021): Modelling and Forecasting High-dimensional Functional Time Series

PhD Supervision (Current, as primary supervisor)

Yonghe Lu (2021 - ): Precision Matrix Estimation for High-dimensional Complicated Data  


Current Teaching:

STAT3050/4050/7050 Advanced Statistical Learning

Previous Teaching:

STAT3013/4027/8027 Statistical Inference

STAT3040/4040/7040 Statistical Learning