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Lad Asymptotics Under Conditional Heteroskedasticity With Possibly Infinite Error Densities

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  • Cho, Jin Seo
  • Han, Chirok
  • Phillips, Peter C.B.

Abstract

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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Bibliographic Info

Article provided by Cambridge University Press in its journal Econometric Theory.

Volume (Year): 26 (2010)
Issue (Month): 03 (June)
Pages: 953-962

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Handle: RePEc:cup:etheor:v:26:y:2010:i:03:p:953-962_99

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  1. Chirok Han & Jin Seo Cho & Peter C.B. Phillips, 2009. "Infinite Density at the Median and the Typical Shape of Stock Return Distributions," Cowles Foundation Discussion Papers 1701, Cowles Foundation for Research in Economics, Yale University.
  2. Phillips, P.C.B., 1991. "A Shortcut to LAD Estimator Asymptotics," Econometric Theory, Cambridge University Press, vol. 7(04), pages 450-463, December.
  3. Bose, Arup & Chatterjee, Snigdhansu, 2001. "Generalised bootstrap in non-regular M-estimation problems," Statistics & Probability Letters, Elsevier, vol. 55(3), pages 319-328, December.
  4. Rogers, Alan J., 2001. "Least Absolute Deviations Regression Under Nonstandard Conditions," Econometric Theory, Cambridge University Press, vol. 17(04), pages 820-852, August.
  5. 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.
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