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.
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- 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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