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Munich Personal RePEc Archive

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Group by: Date | Item ID
Jump to: 40382 | 50487 | 51224 | 51509 | 51570 | 51706 | 52344 | 52732 | 53874 | 56347 | 56623 | 59099 | 61930 | 66991 | 68621
Number of items: 15.

40382

Zhu, Ke (2012): A mixed portmanteau test for ARMA-GARCH model by the quasi-maximum exponential likelihood estimation approach.

50487

Chen, Min and Zhu, Ke (2013): Sign-based portmanteau test for ARCH-type models with heavy-tailed innovations.

51224

Zhu, Ke and Li, Wai-Keung (2013): A bootstrapped spectral test for adequacy in weak ARMA models.

51509

Zhu, Ke and Ling, Shiqing (2013): Global self-weighted and local quasi-maximum exponential likelihood estimators for ARMA-GARCH/IGARCH models. Published in: Annals of Statistics , Vol. 39, No. 4 (2011): pp. 2131-2163.

51570

Guo, Shaojun and Ling, Shiqing and Zhu, Ke (2013): Factor double autoregressive models with application to simultaneous causality testing.

51706

Zhu, Ke and Yu, Philip L.H. and Li, Wai Keung (2013): Testing for the buffered autoregressive processes.

52344

Zhu, Ke and Li, Wai Keung (2013): A new Pearson-type QMLE for conditionally heteroskedastic models.

52732

Zhu, Ke and Li, Wai Keung (2014): A new Pearson-type QMLE for conditionally heteroskedastic models.

53874

Zhu, Ke and Li, Wai Keung and Yu, Philip L.H. (2014): Buffered autoregressive models with conditional heteroscedasticity: An application to exchange rates.

56347

Chen, Min and Zhu, Ke (2014): Sign-based specification tests for martingale difference with conditional heteroscedasity.

56623

Zhu, Ke and Ling, Shiqing (2014): Model-based pricing for financial derivatives.

59099

Zhu, Ke and Ling, Shiqing (2014): LADE-based inference for ARMA models with unspecified and heavy-tailed heteroscedastic noises.

61930

Zhu, Ke (2015): Bootstrapping the portmanteau tests in weak auto-regressive moving average models.

66991

Zhu, Ke (2015): Hausman tests for the error distribution in conditionally heteroskedastic models.

68621

Li, Dong and Ling, Shiqing and Zhu, Ke (2016): ZD-GARCH model: a new way to study heteroscedasticity.

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