Local quantile regression
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- Cai, Zongwu & Wang, Xian, 2008. "Nonparametric estimation of conditional VaR and expected shortfall," Journal of Econometrics, Elsevier, vol. 147(1), pages 120-130, November.
- Robert F. Engle & Simone Manganelli, 2004.
"CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
- Engle, Robert F & Manganelli, Simone, 1999. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," University of California at San Diego, Economics Working Paper Series qt06m3d6nv, Department of Economics, UC San Diego.
- Robert Engle & Simone Manganelli, 2000. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Econometric Society World Congress 2000 Contributed Papers 0841, Econometric Society.
- Kong, Efang & Linton, Oliver & Xia, Yingcun, 2010.
"Uniform Bahadur Representation For Local Polynomial Estimates Of M-Regression And Its Application To The Additive Model,"
Econometric Theory, Cambridge University Press, vol. 26(5), pages 1529-1564, October.
- Efang Kong & Oliver Linton & Yingcun Xia, 2009. "Uniform Bahadur Representation for LocalPolynomial Estimates of M-Regressionand Its Application to The Additive Model," STICERD - Econometrics Paper Series 535, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Bernd Fitzenberger & Ralf Wilke, 2006.
"Using quantile regression for duration analysis,"
AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 105-120, March.
- Bernd Fitzenberger & Ralf A. Wilke, 2006. "Using Quantile Regression for Duration Analysis," Springer Books, in: Olaf Hübler & Jachim Frohn (ed.), Modern Econometric Analysis, chapter 8, pages 103-118, Springer.
- Fitzenberger, Bernd & Wilke, Ralf A., 2005. "Using Quantile Regression for Duration Analysis," ZEW Discussion Papers 05-65, ZEW - Leibniz Centre for European Economic Research.
- Härdle, Wolfgang K. & Song, Song, 2010. "Confidence Bands In Quantile Regression," Econometric Theory, Cambridge University Press, vol. 26(4), pages 1180-1200, August.
- Ruppert,David & Wand,M. P. & Carroll,R. J., 2003. "Semiparametric Regression," Cambridge Books, Cambridge University Press, number 9780521785167, November.
- H. A. Hauksson & M. Dacorogna & T. Domenig & U. Mller & G. Samorodnitsky, 2001.
"Multivariate extremes, aggregation and risk estimation,"
Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 79-95.
- Michel Dacorogna & Höskuldur Ari Hauksson & Thomas Domenig & Ulrich Müller & Gennady Samorodnitsky, 2001. "Multivariate extremes, aggregation and risk estimation," CeNDEF Workshop Papers, January 2001 P2, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
- Yu, Keming & Jones, M. C., 1997. "A comparison of local constant and local linear regression quantile estimators," Computational Statistics & Data Analysis, Elsevier, vol. 25(2), pages 159-166, July.
- Cai, Zongwu & Xu, Xiaoping, 2009.
"Nonparametric Quantile Estimations for Dynamic Smooth Coefficient Models,"
Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 371-383.
- Cai, Zongwu & Xu, Xiaoping, 2008. "Nonparametric Quantile Estimations for Dynamic Smooth Coefficient Models," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1595-1608.
- Xiaoping Xu & Zongwu Cai, 2013. "Nonparametric Quantile Estimations For Dynamic Smooth Coefficient Models," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
- Ruppert,David & Wand,M. P. & Carroll,R. J., 2003. "Semiparametric Regression," Cambridge Books, Cambridge University Press, number 9780521780506, November.
- Inyoung Kim & Noah D. Cohen & Raymond J. Carroll, 2003. "Semiparametric Regression Splines in Matched Case-Control Studies," Biometrics, The International Biometric Society, vol. 59(4), pages 1158-1169, December.
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More about this item
Keywords
conditional quantiles; semiparametric and nonparametric methods; asymmetric Laplace distribution; exponential risk bounds; adaptive bandwidth selection;All these keywords.
JEL classification:
- C00 - Mathematical and Quantitative Methods - - General - - - General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- J01 - Labor and Demographic Economics - - General - - - Labor Economics: General
- J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
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