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Quantile Cointegrating Regression

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  • Zhijie Xiao

    ()
    (Boston College)

Abstract

Quantile regression has important applications in risk management, portfolio optimization, and asset pricing. The current paper studies estimation, inference and financial applications of quantile regression with cointegrated time series. In addition, a new cointegration model with varying coefficients is proposed. In the proposed model, the value of cointegrating coefficients may be affected by the shocks and thus may vary over the innovation quantile. The proposed model may be viewed as a stochastic cointegration model which includes the conventional cointegration model as a special case. It also provides a useful complement to cointegration models with (G)ARCH effects. Asymptotic properties of the proposed model and limiting distribution of the cointegrating regression quantiles are derived. In the presence of endogenous regressors, fully-modified quantile regression estimators and augmented quantile cointegrating regression are proposed to remove the second order bias and nuisance parameters. Regression Wald test are constructed based on the fully modified quantile regression estimators. An empirical application to stock index data highlights the potential of the proposed method.

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Bibliographic Info

Paper provided by Boston College Department of Economics in its series Boston College Working Papers in Economics with number 708.

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Length: 33 pages
Date of creation: 31 Jan 2009
Date of revision:
Handle: RePEc:boc:bocoec:708

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Keywords: ARCH/GARCH; Cointegration; Portfolio Optimization; Quantile Regression; Time Varying;

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Citations

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Cited by:
  1. Xiao, Zhijie, 2009. "Functional-coefficient cointegration models," Journal of Econometrics, Elsevier, vol. 152(2), pages 81-92, October.
  2. Uwe Hassler & Paulo M.M. Rodrigues & Antonio Rubia, 2012. "Quantile regression for long memory testing: A case of realized volatility," Working Papers w201207, Banco de Portugal, Economics and Research Department.
  3. Richard C. K. Burdekin & Pierre L. Siklos, 2011. "Enter the Dragon: Interactions between Chinese, US and Asia-Pacific Equity Markets, 1995-2010," CAMA Working Papers 2011-35, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  4. Honda, Toshio, 2013. "Nonparametric LAD cointegrating regression," Journal of Multivariate Analysis, Elsevier, vol. 117(C), pages 150-162.
  5. Cai, Charlie X. & McGuinness, Paul B. & Zhang, Qi, 2011. "The pricing dynamics of cross-listed securities: The case of Chinese A- and H-shares," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 2123-2136, August.
  6. Lijuan Huo & Tae-Hwan Kim & Yunmi Kim, 2013. "Testing for Autocorrelation in Quantile Regression Models," Working papers 2013rwp-54, Yonsei University, Yonsei Economics Research Institute.
  7. Xiao, Zhijie, 2012. "Robust inference in nonstationary time series models," Journal of Econometrics, Elsevier, vol. 169(2), pages 211-223.
  8. Lee, Chien-Chiang & Zeng, Jhih-Hong, 2011. "Revisiting the relationship between spot and futures oil prices: Evidence from quantile cointegrating regression," Energy Economics, Elsevier, vol. 33(5), pages 924-935, September.

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