Showing posts with label quantile regression. Show all posts
Showing posts with label quantile regression. Show all posts

Tuesday, October 06, 2009

Quantile Regression

For those who want to follow up on the talk yesterday on Quantile Regressions here's a few handy references:

Quantile Regression: Applications and Current Research Areas: Keming Yu, Zudi Lu and Julian Stander, Journal of the Royal Statistical Society. Series D (The Statistician), Vol. 52, No. 3 (2003)
Quantile Regression, R Koenker & K Hallock, J Economic Perspectives, 15(4) 2001
Arias, Omar, Kevin Hallock and Walter Sosa-Escudero. 2001. “Individual Heterogeneity in the Returns to Schooling: Instrumental Variables Quantile Regression Using Twins Data.” Empirical Economics. March, 26:1, pp. 7–40.
Koenker, Roger and Kevin Hallock. 2000. “Quantile Regression: An Introduction.” Available at http://www.econ.uiuc.edu/;roger/research/intro/intro.html&.

Monday, July 06, 2009

Beyond the Central Tendency: Quantile Regression

I’m sure everyone has heard of this before but I’ve been reading up recently on quantile regression. This article by Chris Gowlland, Zhijie Xiao and Qi Zeng offers a nice overview of how the method has developed over the years.

Abridged Abstract from The Journal of Portfolio Mgmt. Spring 2009, Vol. 35, No. 3:

Quantitative investors frequently analyze factor performance using regression based on the familiar ordinary least squares approach. This is highly effective for understanding the central tendency within a dataset, but will often be less useful for assessing the behavior of datapoints close to the upper or lower extremes within a population. But from the perspective of active investors or risk managers, the datapoints at the extremes may be precisely the ones of greatest interest. For such applications, a more appropriate methodology is quantile regression...