Quantile-on-Quantile Regression
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.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- 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 10.1016/j.jbankfin.2015.01.013
- Koenker, R., & Bassett, G. (1978). Regression quantiles. Econometrica, 46(1), 33-50. · DOI 10.2307/1913643
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