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Quantile and expectile smoothing by F-transform

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Abstract

In this paper we illustrate the F-transform based on generalized fuzzy partitions as a tool for quantile and expectile smoothing. This allows to represent a time series in terms of a fuzzy-valued function whose levelcuts are modeled by F-transform and estimated by quantile or expectile regression. The proposed methodology is illustrated on several historical ?nancial time series in order to highlight its strong properties . Length: 17 pages

Suggested Citation

  • Luciano Stefanini, 2015. "Quantile and expectile smoothing by F-transform," Working Papers 1512, University of Urbino Carlo Bo, Department of Economics, Society & Politics - Scientific Committee - L. Stefanini & G. Travaglini, revised 2015.
  • Handle: RePEc:urb:wpaper:15_12
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    File URL: http://www.econ.uniurb.it/RePEc/urb/wpaper/WP_15_12.pdf
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    References listed on IDEAS

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    1. Koenker, Roger & Xiao, Zhijie, 2006. "Quantile Autoregression," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 980-990, September.
    2. De Rossi, Giuliano & Harvey, Andrew, 2009. "Quantiles, expectiles and splines," Journal of Econometrics, Elsevier, vol. 152(2), pages 179-185, October.
    3. Yao, Qiwei & Tong, Howell, 1996. "Asymmetric least squares regression estimation: a nonparametric approach," LSE Research Online Documents on Economics 19423, London School of Economics and Political Science, LSE Library.
    4. Schnabel, Sabine K. & Eilers, Paul H.C., 2009. "Optimal expectile smoothing," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4168-4177, October.
    5. Kovac, A., 2007. "Smooth functions and local extreme values," Computational Statistics & Data Analysis, Elsevier, vol. 51(10), pages 5155-5171, June.
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    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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