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Estimating Nonlinear Dynamic Models Using Least Absolute Error Estimation

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Cited by:

  1. Dasgupta, Madhuchhanda & Mishra, SK, 2004. "Least absolute deviation estimation of linear econometric models: A literature review," MPRA Paper 1781, University Library of Munich, Germany.
  2. Xiaohong Chen & Roger Koenker & Zhijie Xiao, 2009. "Copula-based nonlinear quantile autoregression," Econometrics Journal, Royal Economic Society, vol. 12(s1), pages 50-67, January.
  3. Kristensen Johannes Tang, 2014. "Factor-based forecasting in the presence of outliers: Are factors better selected and estimated by the median than by the mean?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(3), pages 1-30, May.
  4. Gabriela Ciuperca, 2011. "Penalized least absolute deviations estimation for nonlinear model with change-points," Statistical Papers, Springer, vol. 52(2), pages 371-390, May.
  5. White, Halbert & Kim, Tae-Hwan & Manganelli, Simone, 2015. "VAR for VaR: Measuring tail dependence using multivariate regression quantiles," Journal of Econometrics, Elsevier, vol. 187(1), pages 169-188.
  6. Chung-Ming Kuan & Christos Michalopoulos & Zhijie Xiao, 2017. "Quantile Regression on Quantile Ranges – A Threshold Approach," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(1), pages 99-119, January.
  7. Jürgen Franke & Peter Mwita & Weining Wang, 2015. "Nonparametric estimates for conditional quantiles of time series," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(1), pages 107-130, January.
  8. Mukherjee, Kanchan, 2000. "Linearization Of Randomly Weighted Empiricals Under Long Range Dependence With Applications To Nonlinear Regression Quantiles," Econometric Theory, Cambridge University Press, vol. 16(3), pages 301-323, June.
  9. F. Cipollini & G.M. Gallo & A. Palandri, 2023. "Modeling and evaluating conditional quantile dynamics in VaR forecasts," Working Paper CRENoS 202308, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
  10. Élise, COUDIN & Jean-Marie DUFOUR, 2017. "Finite-Sample Generalized Confidence Distributions and Sign-Based Robust Estimators in Median Regressions with Heterogeneous Dependent Errors," Cahiers de recherche 01-2017, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  11. Alain Hecq & Li Sun, 2021. "Adaptive Random Bandwidth for Inference in CAViaR Models," Papers 2102.01636, arXiv.org.
  12. 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.
  13. Parente, Paulo M.D.C. & Smith, Richard J., 2011. "Gel Methods For Nonsmooth Moment Indicators," Econometric Theory, Cambridge University Press, vol. 27(1), pages 74-113, February.
  14. Dimitriadis, Timo & Schnaitmann, Julie, 2021. "Forecast encompassing tests for the expected shortfall," International Journal of Forecasting, Elsevier, vol. 37(2), pages 604-621.
  15. Elise COUDIN, Jean-Marie DUFOUR, 2008. "Hodges-Lehmann Sign-based Estimators and Generalized Confidence Distributions in Linear Median Regressions with Moment-free Heterogenous Errors and Dependence of Unknown Form," Working Papers 2008-33, Center for Research in Economics and Statistics.
  16. Demetrescu, Matei, 2006. "An extension of the Gauss-Newton algorithm for estimation under asymmetric loss," Computational Statistics & Data Analysis, Elsevier, vol. 50(2), pages 379-401, January.
  17. 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.
  18. Gourieroux, C. & Jasiak, J., 2008. "Dynamic quantile models," Journal of Econometrics, Elsevier, vol. 147(1), pages 198-205, November.
  19. Kim, Minjo & Lee, Sangyeol, 2016. "Nonlinear expectile regression with application to Value-at-Risk and expected shortfall estimation," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 1-19.
  20. Moshe Buchinsky, 1998. "Recent Advances in Quantile Regression Models: A Practical Guideline for Empirical Research," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 88-126.
  21. Patton, Andrew J. & Ziegel, Johanna F. & Chen, Rui, 2019. "Dynamic semiparametric models for expected shortfall (and Value-at-Risk)," Journal of Econometrics, Elsevier, vol. 211(2), pages 388-413.
  22. Sebastian Bayer & Timo Dimitriadis, 2022. "Regression-Based Expected Shortfall Backtesting [Backtesting Expected Shortfall]," Journal of Financial Econometrics, Oxford University Press, vol. 20(3), pages 437-471.
  23. Jungsik Noh & Sangyeol Lee, 2016. "Quantile Regression for Location-Scale Time Series Models with Conditional Heteroscedasticity," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(3), pages 700-720, September.
  24. Seokwoo Jake Choi & Stephen Portnoy, 2016. "Quantile Autoregression for Censored Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(5), pages 603-623, September.
  25. Timo Dimitriadis & Yannick Hoga, 2022. "Dynamic CoVaR Modeling," Papers 2206.14275, arXiv.org, revised Feb 2024.
  26. Fitzenberger, Bernd, 1998. "The moving blocks bootstrap and robust inference for linear least squares and quantile regressions," Journal of Econometrics, Elsevier, vol. 82(2), pages 235-287, February.
  27. Oberhofer, Walter & Haupt, Harry, 2003. "Nonlinear quantile regression under dependence and heterogeneity," University of Regensburg Working Papers in Business, Economics and Management Information Systems 388, University of Regensburg, Department of Economics.
  28. White, Halbert & Kim, Tae-Hwan & Manganelli, Simone, 2010. "VAR for VaR: measuring systemic risk using multivariate regression quantiles," MPRA Paper 35372, University Library of Munich, Germany.
  29. Timo Dimitriadis & Tobias Fissler & Johanna Ziegel, 2020. "The Efficiency Gap," Papers 2010.14146, arXiv.org, revised Sep 2022.
  30. Dimitriadis, Timo & Liu, Xiaochun & Schnaitmann, Julie, 2020. "Encompassing tests for value at risk and expected shortfall multi-step forecasts based on inference on the boundary," Hohenheim Discussion Papers in Business, Economics and Social Sciences 11-2020, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
  31. Robert F. Engle & Simone Manganelli, 1999. "CAViaR: Conditional Value at Risk by Quantile Regression," NBER Working Papers 7341, National Bureau of Economic Research, Inc.
  32. Cai, Yuzhi, 2007. "A quantile approach to US GNP," Economic Modelling, Elsevier, vol. 24(6), pages 969-979, November.
  33. Koenker, Roger & Park, Beum J., 1996. "An interior point algorithm for nonlinear quantile regression," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 265-283.
  34. Manganelli, Simone & White, Halbert & Kim, Tae-Hwan, 2008. "Modeling autoregressive conditional skewness and kurtosis with multi-quantile CAViaR," Working Paper Series 957, European Central Bank.
  35. Gareth W. Peters, 2018. "General Quantile Time Series Regressions for Applications in Population Demographics," Risks, MDPI, vol. 6(3), pages 1-47, September.
  36. Gabriela Ciuperca, 2011. "Estimating nonlinear regression with and without change-points by the LAD method," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(4), pages 717-743, August.
  37. Fitzenberger, Bernd, 1994. "A note on estimating censored quantile regressions," Discussion Papers 14, University of Konstanz, Center for International Labor Economics (CILE).
  38. Zhao Chen & Runze Li & Yaohua Wu, 2012. "Weighted quantile regression for AR model with infinite variance errors," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(3), pages 715-731.
  39. Khizar Qureshi, 2016. "Value-at-Risk: The Effect of Autoregression in a Quantile Process," Papers 1605.04940, arXiv.org.
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