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Autor:innen: 
Härdle, Wolfgang Karl
Spokoiny, Vladimir
Wang, Weining
Datum: 
2010
Schriftenreihe/Nr.: 
SFB 649 Discussion Paper No. 2011-005
Verlag: 
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk, Berlin
Zusammenfassung: 
Conditional quantile curves provide a comprehensive picture of a response contingent on explanatory variables. Quantile regression is a technique to estimate such curves. In a flexible modeling framework, a specific form of the quantile is not a priori fixed. Indeed, the majority of applications do not per se require specific functional forms. This motivates a local parametric rather than a global fixed model fitting approach. A nonparametric smoothing estimate of the conditional quantile curve requires to consider a balance between local curvature and variance. In this paper, we analyze a method based on a local model selection technique that provides an adaptive estimate. Theoretical properties on mimicking the oracle choice are offered and applications to stock market and weather analysis are presented.
Schlagwörter: 
conditional quantiles
semiparametric and nonparametric methods
asymmetric Laplace distribution
exponential risk bounds
adaptive bandwidth selection
JEL: 
C00
C14
J01
J31
Dokumentart: 
Working Paper

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