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LAD Asymptotics under Conditional Heteroskedasticity with Possibly Infinite Error Densities

  • Jin Seo Cho

    (Korea University)

  • Chirok-Han

    (Korea University)

  • Peter C. B. Phillips

    (Yale University, University of Auckland, University of Southampton & Singapore Management University)

Least absolute deviations (LAD) estimation of linear time-series models is considered under conditional heteroskedasticity and serial correlation. The limit theory of the LAD estimator is obtained without assuming the finite density condition for the errors that is required in standard LAD asymptotics. The results are particularly useful in application of LAD estimation to financial time-series data.

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File URL: http://econ.korea.ac.kr/~ri/WorkingPapers/w0917.pdf
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Paper provided by Institute of Economic Research, Korea University in its series Discussion Paper Series with number 0917.

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Length: 12 pages
Date of creation: 2009
Date of revision:
Handle: RePEc:iek:wpaper:0917
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  1. Chirok Han & Jin Seo Cho & Peter C. B. Phillips, 2011. "Infinite Density at the Median and the Typical Shape of Stock Return Distributions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(2), pages 282-294, April.
  2. Koenker, Roger & Zhao, Quanshui, 1996. "Conditional Quantile Estimation and Inference for Arch Models," Econometric Theory, Cambridge University Press, vol. 12(05), pages 793-813, December.
  3. Rogers, Alan J., 2001. "Least Absolute Deviations Regression Under Nonstandard Conditions," Econometric Theory, Cambridge University Press, vol. 17(04), pages 820-852, August.
  4. Peter C.B. Phillips, 1990. "A Shortcut to LAD Estimator Asymptotics," Cowles Foundation Discussion Papers 949, Cowles Foundation for Research in Economics, Yale University.
  5. Bose, Arup & Chatterjee, Snigdhansu, 2001. "Generalised bootstrap in non-regular M-estimation problems," Statistics & Probability Letters, Elsevier, vol. 55(3), pages 319-328, December.
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