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Regresi Kuantil-pada-Kuantil Fourier×Regresi Quantile-on-Quantile (QQ)×
BidangEkonometrikaEkonometrika
KeluargaRegression modelRegression model
Tahun asal2015-2020s2015
PencetusExtension combining Sim & Zhou (2015) QQ regression with Fourier flexible-form smoothingSim and Zhou
TipeNonparametric quantile regression with Fourier smoothingNonparametric quantile regression
Sumber perintisSim, N., & Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking and Finance, 55, 1-8. DOI ↗Sim, N., & Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking and Finance, 55, 1-8. DOI ↗
AliasFourier QQ regression, Fourier-QQR, Fourier quantile regression with quantile regressors, smooth structural-break QQ regressionQQ regression, QQ approach, quantile-on-quantile approach, nonparametric quantile regression
Terkait66
RingkasanFourier quantile-on-quantile regression extends the quantile-on-quantile (QQ) framework of Sim and Zhou (2015) by embedding Fourier trigonometric terms into the local linear quantile model. This allows the estimated dependence between the quantiles of one variable and the quantiles of another to vary smoothly over time, capturing gradual structural change without imposing a known break date.Quantile-on-quantile regression is a nonparametric technique that estimates how the quantiles of one variable depend on the quantiles of another. By combining standard quantile regression with local linear smoothing, it produces a full two-dimensional surface of slope coefficients indexed by both the quantile of the outcome and the quantile of the predictor, revealing heterogeneous and asymmetric dependency structures invisible to standard regression.
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ScholarGateBandingkan metode: Fourier Quantile-on-Quantile Regression · Quantile-on-Quantile Regression. Diakses 2026-06-18 dari https://scholargate.app/id/compare