Papers and Manuscripts (*: Graduate students)
  1. *Xu, Z. and Zhao, Z. (2021) Efficient estimation for models with nonlinear heteroscedasticity.
    Journal of Business and Economic Statistics , To appear.

  2. *Xu, Z., *Kim, S. and Zhao, Z. (2020) Locally stationary quantile regression for inflation and interest rates.
    Journal of Business and Economic Statistics , To appear.

  3. *Ou, L. and Zhao, Z. (2020) Value-at-Risk forecasting via dynamic asymmetric exponential power distributions.
    Journal of Forecasting 40, 291-300.

  4. *Li, X. and Zhao, Z. (2019) A Time-varying Approach to the Stock Return-Inflation Puzzle.
    Journal of the Royal Statistical Society: Series C 68, 1509-1528.

  5. *Kim, S., Zhao, Z. and Xiao, Z. (2018) Efficient estimation for time-varying coefficient longitudinal models.
    Journal of Nonparametric Statistics 30, 680-702.

  6. *Wang, C. and Zhao, Z. (2016) Conditional Value-at-Risk: Semiparametric estimation and inference.
    Journal of Econometrics 195, 86-103. Longer version of the JoE paper. R code for SP500 index.

  7. *Kim, S, Zhao, Z. and Shao, X. (2015) Nonparametric functional central limit theorem for time series with application to self-normalized confidence interval.
    Journal of Multivariate Analysis 133, 277-290.

  8. Zhao, Z. (2015) Inference for local autocorrelation process in locally stationary models.
    Journal of Business and Economic Statistics 33, 296-306.

  9. Zhao, Z. and Xiao, Z. (2014) Efficient regressions via optimally combining quantile information.
    Econometric Theory 30, 1272-1314.

  10. *Kim, S. and Zhao, Z. (2014) Specification test for Markov models with measurement errors.
    Journal of Multivariate Analysis 130, 118-133.

  11. Zhao, Z., Zhang, Y. and Li, R. (2014) Nonparametric estimation under strong dependence.
    Journal of Time Series Analysis 35, 4-15.

  12. Zhao, Z., Wei, Y. and Lin, D. (2014) Asymptotics of nonparametric L-1 regression models with dependent data.
    Bernoulli 20, 1532-1559.

  13. Yao, W. and Zhao, Z. (2013) Kernel density based linear regression estimates.
    Communications in Statistics: Theory and Methods 42, 4499-4512.

  14. *Li, X. and Zhao, Z. (2013) Testing for changes in autocovariances of nonparametric time series models.
    Journal of Statistical Planning and Inference 143, 237-250.

  15. Zhao, Z. and *Li, X. (2013) Inference for modulated stationary processes.
    Bernoulli 19, 205-227.

  16. *Kim, S. and Zhao, Z. (2013) Unified inference for sparse and dense longitudinal models.
    Biometrika 100, 203-212.

  17. Zhao, Z. and Yao, W. (2012) Sequential design for nonparametric inference.
    Canadian Journal of Statistics 40, 362-377.

  18. Wei, Y., Zhao, Z. and Lin, D. (2012) Profile control charts based on nonparametric L-1 regression methods.
    Annals of Applied Statistics 6, 409-427.

  19. Zhao, Z. (2011) A self-normalized confidence interval for the mean of a class of non-stationary processes.
    Biometrika 98, 81-90. Supplementary materials.

  20. Zhao, Z. (2011) Nonparametric model validations for hidden Markov models with applications in financial econometrics.
    Journal of Econometrics 162, 225-239.

  21. Zhao, Z. (2010) Density estimation for nonlinear parametric models with conditional heteroscedasticity.
    Journal of Econometrics 155, 71-82.

  22. Zhao, Z. and Wu, W.B. (2009) Nonparametric inference of discretely sampled stable Levy processes.
    Journal of Econometrics 153, 83-92.

  23. Zhao, Z. (2008) Parametric and nonparametric models and methods in financial econometrics.
    Statistics Surveys 2, 1-42.

  24. Zhao, Z. and Wu, W.B. (2008) Confidence bands in nonparametric time series regression.
    Annals of Statistics 36, 1854-1878.

  25. Wu, W.B. and Zhao, Z. (2008) Moderate deviations for stationary processes.
    Statistica Sinica 18, 769-782.

  26. Wu, W.B. and Zhao, Z. (2007) Inference of trends in time series.
    Journal of the Royal Statistical Society: Series B 69, 391-410.

  27. Zhao, Z. and Wu, W.B. (2007) Asymptotic theory for curve-crossing analysis.
    Stochastic Processes and their Applications 117, 862-877.

PhD Thesis
Zhao, Z. (2007) Nonparametric inference for stochastic diffusion models.
University of Chicago.