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Ke Zhu

Personal Details

First Name:Ke
Middle Name:
Last Name:Zhu
Suffix:
RePEc Short-ID:pzh444
https://sites.google.com/site/nelsonkezhu/

Affiliation

中国科学院,数学与系统科学研究院 (Academy of Mathematics and Systems Science, Chinese Academy of Sciences)

http://www.amss.ac.cn/
Beijing, China

Research output

as
Jump to: Working papers Articles

Working papers

  1. Ke Zhu, 2018. "Statistical inference for autoregressive models under heteroscedasticity of unknown form," Papers 1804.02348, arXiv.org, revised Aug 2018.
  2. Guochang Wang & Wai Keung Li & Ke Zhu, 2018. "New HSIC-based tests for independence between two stationary multivariate time series," Papers 1804.09866, arXiv.org.
  3. Li, Dong & Ling, Shiqing & Zhu, Ke, 2016. "ZD-GARCH model: a new way to study heteroscedasticity," MPRA Paper 68621, University Library of Munich, Germany.
  4. Zhu, Ke, 2015. "Bootstrapping the portmanteau tests in weak auto-regressive moving average models," MPRA Paper 61930, University Library of Munich, Germany.
  5. Zhu, Ke, 2015. "Hausman tests for the error distribution in conditionally heteroskedastic models," MPRA Paper 66991, University Library of Munich, Germany.
  6. Zhu, Ke & Li, Wai Keung & Yu, Philip L.H., 2014. "Buffered autoregressive models with conditional heteroscedasticity: An application to exchange rates," MPRA Paper 53874, University Library of Munich, Germany.
  7. Chen, Min & Zhu, Ke, 2014. "Sign-based specification tests for martingale difference with conditional heteroscedasity," MPRA Paper 56347, University Library of Munich, Germany.
  8. Zhu, Ke & Ling, Shiqing, 2014. "Model-based pricing for financial derivatives," MPRA Paper 56623, University Library of Munich, Germany.
  9. Zhu, Ke & Ling, Shiqing, 2014. "LADE-based inference for ARMA models with unspecified and heavy-tailed heteroscedastic noises," MPRA Paper 59099, University Library of Munich, Germany.
  10. Chen, Min & Zhu, Ke, 2013. "Sign-based portmanteau test for ARCH-type models with heavy-tailed innovations," MPRA Paper 50487, University Library of Munich, Germany.
  11. Zhu, Ke & Li, Wai Keung, 2013. "A new Pearson-type QMLE for conditionally heteroskedastic models," MPRA Paper 52344, University Library of Munich, Germany.
  12. Guo, Shaojun & Ling, Shiqing & Zhu, Ke, 2013. "Factor double autoregressive models with application to simultaneous causality testing," MPRA Paper 51570, University Library of Munich, Germany.
  13. Zhu, Ke & Ling, Shiqing, 2013. "Global self-weighted and local quasi-maximum exponential likelihood estimators for ARMA-GARCH/IGARCH models," MPRA Paper 51509, University Library of Munich, Germany.
  14. Zhu, Ke & Yu, Philip L.H. & Li, Wai Keung, 2013. "Testing for the buffered autoregressive processes," MPRA Paper 51706, University Library of Munich, Germany.
  15. Zhu, Ke & Li, Wai-Keung, 2013. "A bootstrapped spectral test for adequacy in weak ARMA models," MPRA Paper 51224, University Library of Munich, Germany.
  16. Zhu, Ke, 2012. "A mixed portmanteau test for ARMA-GARCH model by the quasi-maximum exponential likelihood estimation approach," MPRA Paper 40382, University Library of Munich, Germany.

Articles

  1. Li, Dong & Zhang, Xingfa & Zhu, Ke & Ling, Shiqing, 2018. "The ZD-GARCH model: A new way to study heteroscedasticity," Journal of Econometrics, Elsevier, vol. 202(1), pages 1-17.
  2. Ke Zhu & Wai Keung Li & Philip L. H. Yu, 2017. "Buffered Autoregressive Models With Conditional Heteroscedasticity: An Application to Exchange Rates," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 528-542, October.
  3. Ke Zhu, 2016. "Bootstrapping the portmanteau tests in weak auto-regressive moving average models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(2), pages 463-485, March.
  4. Ke Zhu & Shiqing Ling, 2015. "LADE-Based Inference for ARMA Models With Unspecified and Heavy-Tailed Heteroscedastic Noises," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(510), pages 784-794, June.
  5. Chen, Min & Zhu, Ke, 2015. "Sign-based portmanteau test for ARCH-type models with heavy-tailed innovations," Journal of Econometrics, Elsevier, vol. 189(2), pages 313-320.
  6. Zhu, Ke & Li, Wai Keung, 2015. "A bootstrapped spectral test for adequacy in weak ARMA models," Journal of Econometrics, Elsevier, vol. 187(1), pages 113-130.
  7. Zhu, Ke & Ling, Shiqing, 2015. "Model-based pricing for financial derivatives," Journal of Econometrics, Elsevier, vol. 187(2), pages 447-457.
  8. Ke Zhu & Wai Keung Li, 2015. "A New Pearson-Type QMLE for Conditionally Heteroscedastic Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 552-565, October.
  9. Shiqing Ling & Ke Zhu, 2014. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(2), pages 202-203, April.
  10. Ke. Zhu, 2013. "A mixed portmanteau test for ARMA-GARCH models by the quasi-maximum exponential likelihood estimation approach," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(2), pages 230-237, March.
  11. Ling, Shiqing & Zhu, Ke & Yee, Chong Ching, 2013. "Diagnostic checking for non-stationary ARMA models with an application to financial data," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 624-639.
  12. Zhu, Ke & Ling, Shiqing, 2012. "THE GLOBAL WEIGHTED LAD ESTIMATORS FOR FINITE/INFINITE VARIANCE ARMA(p,q) MODELS," Econometric Theory, Cambridge University Press, vol. 28(05), pages 1065-1086, October.
  13. Ke Zhu & Shiqing Ling, 2012. "Likelihood ratio tests for the structural change of an AR(p) model to a Threshold AR(p) model," Journal of Time Series Analysis, Wiley Blackwell, vol. 33(2), pages 223-232, March.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Zhu, Ke, 2015. "Bootstrapping the portmanteau tests in weak auto-regressive moving average models," MPRA Paper 61930, University Library of Munich, Germany.

    Cited by:

    1. Ke Zhu, 2018. "Statistical inference for autoregressive models under heteroscedasticity of unknown form," Papers 1804.02348, arXiv.org, revised Aug 2018.
    2. Li, Dong & Zhang, Xingfa & Zhu, Ke & Ling, Shiqing, 2018. "The ZD-GARCH model: A new way to study heteroscedasticity," Journal of Econometrics, Elsevier, vol. 202(1), pages 1-17.

  2. Zhu, Ke & Li, Wai Keung & Yu, Philip L.H., 2014. "Buffered autoregressive models with conditional heteroscedasticity: An application to exchange rates," MPRA Paper 53874, University Library of Munich, Germany.

    Cited by:

    1. Tong, Howell, 2015. "Threshold models in time series analysis—Some reflections," Journal of Econometrics, Elsevier, vol. 189(2), pages 485-491.

  3. Zhu, Ke & Ling, Shiqing, 2014. "Model-based pricing for financial derivatives," MPRA Paper 56623, University Library of Munich, Germany.

    Cited by:

    1. Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Working Papers in Economics 14/29, University of Canterbury, Department of Economics and Finance.
    2. Badescu, Alexandru & Cui, Zhenyu & Ortega, Juan-Pablo, 2016. "A note on the Wang transform for stochastic volatility pricing models," Finance Research Letters, Elsevier, vol. 19(C), pages 189-196.
    3. Chang, C-L. & McAleer, M.J., 2014. "Econometric Analysis of Financial Derivatives," Econometric Institute Research Papers EI 2015-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Zhu, Ke, 2015. "Hausman tests for the error distribution in conditionally heteroskedastic models," MPRA Paper 66991, University Library of Munich, Germany.

  4. Zhu, Ke & Ling, Shiqing, 2014. "LADE-based inference for ARMA models with unspecified and heavy-tailed heteroscedastic noises," MPRA Paper 59099, University Library of Munich, Germany.

    Cited by:

    1. Ke Zhu, 2016. "Bootstrapping the portmanteau tests in weak auto-regressive moving average models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(2), pages 463-485, March.
    2. Ke Zhu, 2018. "Statistical inference for autoregressive models under heteroscedasticity of unknown form," Papers 1804.02348, arXiv.org, revised Aug 2018.

  5. Chen, Min & Zhu, Ke, 2013. "Sign-based portmanteau test for ARCH-type models with heavy-tailed innovations," MPRA Paper 50487, University Library of Munich, Germany.

    Cited by:

    1. Shiqing Ling & Michael McAleer & Howell Tong, 2015. "Frontiers in Time Series and Financial Econometrics: An Overview," Tinbergen Institute Discussion Papers 15-026/III, Tinbergen Institute.
    2. Li, Dong & Ling, Shiqing & Zhu, Ke, 2016. "ZD-GARCH model: a new way to study heteroscedasticity," MPRA Paper 68621, University Library of Munich, Germany.
    3. Ke Zhu, 2016. "Bootstrapping the portmanteau tests in weak auto-regressive moving average models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(2), pages 463-485, March.
    4. Zhu, Ke, 2015. "Hausman tests for the error distribution in conditionally heteroskedastic models," MPRA Paper 66991, University Library of Munich, Germany.
    5. Ling, S. & McAleer, M.J. & Tong, H., 2015. "Frontiers in Time Series and Financial Econometrics," Econometric Institute Research Papers EI 2015-07, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Li, Dong & Zhang, Xingfa & Zhu, Ke & Ling, Shiqing, 2018. "The ZD-GARCH model: A new way to study heteroscedasticity," Journal of Econometrics, Elsevier, vol. 202(1), pages 1-17.

  6. Zhu, Ke & Li, Wai Keung, 2013. "A new Pearson-type QMLE for conditionally heteroskedastic models," MPRA Paper 52344, University Library of Munich, Germany.

    Cited by:

    1. Vijverberg, Chu-Ping C. & Vijverberg, Wim P.M. & Taşpınar, Süleyman, 2016. "Linking Tukey’s legacy to financial risk measurement," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 595-615.
    2. Li, Dong & Zhang, Xingfa & Zhu, Ke & Ling, Shiqing, 2018. "The ZD-GARCH model: A new way to study heteroscedasticity," Journal of Econometrics, Elsevier, vol. 202(1), pages 1-17.
    3. Aknouche, Abdelhakim & Al-Eid, Eid & Demouche, Nacer, 2016. "Generalized quasi-maximum likelihood inference for periodic conditionally heteroskedastic models," MPRA Paper 75770, University Library of Munich, Germany, revised 19 Dec 2016.

  7. Zhu, Ke & Yu, Philip L.H. & Li, Wai Keung, 2013. "Testing for the buffered autoregressive processes," MPRA Paper 51706, University Library of Munich, Germany.

    Cited by:

    1. Andrabi,Tahir & Das,Jishnu & Khwaja,Asim Ijaz, 2015. "Delivering education : a pragmatic framework for improving education in low-income countries," Policy Research Working Paper Series 7277, The World Bank.

  8. Zhu, Ke & Li, Wai-Keung, 2013. "A bootstrapped spectral test for adequacy in weak ARMA models," MPRA Paper 51224, University Library of Munich, Germany.

    Cited by:

    1. Zhu, Ke & Ling, Shiqing, 2014. "LADE-based inference for ARMA models with unspecified and heavy-tailed heteroscedastic noises," MPRA Paper 59099, University Library of Munich, Germany.
    2. Zhang, Xianyang, 2016. "White noise testing and model diagnostic checking for functional time series," Journal of Econometrics, Elsevier, vol. 194(1), pages 76-95.
    3. Ke Zhu, 2018. "Statistical inference for autoregressive models under heteroscedasticity of unknown form," Papers 1804.02348, arXiv.org, revised Aug 2018.
    4. Li, Dong & Zhang, Xingfa & Zhu, Ke & Ling, Shiqing, 2018. "The ZD-GARCH model: A new way to study heteroscedasticity," Journal of Econometrics, Elsevier, vol. 202(1), pages 1-17.

  9. Zhu, Ke, 2012. "A mixed portmanteau test for ARMA-GARCH model by the quasi-maximum exponential likelihood estimation approach," MPRA Paper 40382, University Library of Munich, Germany.

    Cited by:

    1. Kilani Ghoudi & Bruno Rémillard, 2018. "Serial independence tests for innovations of conditional mean and variance models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(1), pages 3-26, March.

Articles

  1. Li, Dong & Zhang, Xingfa & Zhu, Ke & Ling, Shiqing, 2018. "The ZD-GARCH model: A new way to study heteroscedasticity," Journal of Econometrics, Elsevier, vol. 202(1), pages 1-17.

    Cited by:

    1. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2504. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," CREATES Research Papers 2018-14, Department of Economics and Business Economics, Aarhus University.

  2. Ke Zhu & Wai Keung Li & Philip L. H. Yu, 2017. "Buffered Autoregressive Models With Conditional Heteroscedasticity: An Application to Exchange Rates," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 528-542, October.
    See citations under working paper version above.
  3. Ke Zhu, 2016. "Bootstrapping the portmanteau tests in weak auto-regressive moving average models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(2), pages 463-485, March.
    See citations under working paper version above.
  4. Ke Zhu & Shiqing Ling, 2015. "LADE-Based Inference for ARMA Models With Unspecified and Heavy-Tailed Heteroscedastic Noises," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(510), pages 784-794, June.
    See citations under working paper version above.
  5. Chen, Min & Zhu, Ke, 2015. "Sign-based portmanteau test for ARCH-type models with heavy-tailed innovations," Journal of Econometrics, Elsevier, vol. 189(2), pages 313-320.
    See citations under working paper version above.
  6. Zhu, Ke & Li, Wai Keung, 2015. "A bootstrapped spectral test for adequacy in weak ARMA models," Journal of Econometrics, Elsevier, vol. 187(1), pages 113-130.
    See citations under working paper version above.
  7. Zhu, Ke & Ling, Shiqing, 2015. "Model-based pricing for financial derivatives," Journal of Econometrics, Elsevier, vol. 187(2), pages 447-457.
    See citations under working paper version above.
  8. Ke Zhu & Wai Keung Li, 2015. "A New Pearson-Type QMLE for Conditionally Heteroscedastic Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 552-565, October.
    See citations under working paper version above.
  9. Ke. Zhu, 2013. "A mixed portmanteau test for ARMA-GARCH models by the quasi-maximum exponential likelihood estimation approach," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(2), pages 230-237, March. See citations under working paper version above.
  10. Ling, Shiqing & Zhu, Ke & Yee, Chong Ching, 2013. "Diagnostic checking for non-stationary ARMA models with an application to financial data," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 624-639.

    Cited by:

    1. Chang, C-L. & Allen, D.E. & McAleer, M.J., 2013. "Recent Developments in Financial Economics and Econometrics: An Overview," Econometric Institute Research Papers EI 2013-03, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  11. Zhu, Ke & Ling, Shiqing, 2012. "THE GLOBAL WEIGHTED LAD ESTIMATORS FOR FINITE/INFINITE VARIANCE ARMA(p,q) MODELS," Econometric Theory, Cambridge University Press, vol. 28(05), pages 1065-1086, October.

    Cited by:

    1. Zhu, Ke & Ling, Shiqing, 2014. "LADE-based inference for ARMA models with unspecified and heavy-tailed heteroscedastic noises," MPRA Paper 59099, University Library of Munich, Germany.
    2. Ke Zhu, 2018. "Statistical inference for autoregressive models under heteroscedasticity of unknown form," Papers 1804.02348, arXiv.org, revised Aug 2018.
    3. Zhu, Ke & Ling, Shiqing, 2013. "Global self-weighted and local quasi-maximum exponential likelihood estimators for ARMA-GARCH/IGARCH models," MPRA Paper 51509, University Library of Munich, Germany.
    4. Zhu, Ke & Li, Wai Keung, 2015. "A bootstrapped spectral test for adequacy in weak ARMA models," Journal of Econometrics, Elsevier, vol. 187(1), pages 113-130.
    5. Yang, Yaxing & Ling, Shiqing, 2017. "Self-weighted LAD-based inference for heavy-tailed threshold autoregressive models," Journal of Econometrics, Elsevier, vol. 197(2), pages 368-381.

  12. Ke Zhu & Shiqing Ling, 2012. "Likelihood ratio tests for the structural change of an AR(p) model to a Threshold AR(p) model," Journal of Time Series Analysis, Wiley Blackwell, vol. 33(2), pages 223-232, March.

    Cited by:

    1. Zhu, Ke & Li, Wai Keung & Yu, Philip L.H., 2014. "Buffered autoregressive models with conditional heteroscedasticity: An application to exchange rates," MPRA Paper 53874, University Library of Munich, Germany.
    2. Zhu, Ke & Yu, Philip L.H. & Li, Wai Keung, 2013. "Testing for the buffered autoregressive processes," MPRA Paper 51706, University Library of Munich, Germany.

More information

Research fields, statistics, top rankings, if available.

Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 16 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (15) 2012-08-23 2013-10-18 2013-11-14 2013-11-22 2013-11-29 2013-12-06 2013-12-29 2014-03-01 2014-06-22 2014-11-12 2015-02-16 2015-10-04 2016-01-18 2018-04-23 2018-05-14. Author is listed
  2. NEP-ETS: Econometric Time Series (13) 2012-08-23 2013-10-18 2013-11-14 2013-11-22 2013-11-29 2013-12-06 2014-01-17 2014-03-01 2014-11-12 2015-02-16 2015-10-04 2016-01-18 2018-04-23. Author is listed
  3. NEP-ORE: Operations Research (6) 2013-11-14 2013-11-22 2013-12-06 2013-12-29 2014-01-17 2014-03-01. Author is listed

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