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SUMMARY:Conditional Quantiles and Tail Dependence - Bernard\, C (Universit
 y of Waterloo)
DTSTART:20140926T090000Z
DTEND:20140926T094500Z
UID:TALK54632@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:Co-author: Claudia Czado\n\nConditional quantile estimation is
  a crucial step in many statistical problems. For example\, the recent wor
 k on systemic risk relies on estimating risk conditional on an institution
  being in distress or conditional on being in a crisis (Adrian and Brunner
 meier (2010)\, Brownlees and Engle (2011)). Specifically\, the CoVaR syste
 mic risk measure is based on a conditional quantile when one of the variab
 le is in the tail of the distribution. In this paper\, we study properties
  of conditional quantiles and how they relate to properties of the depende
 nce. In particular\, we provide a new graphical characterization of tail d
 ependence and intermediate tail dependence from plots of conditional quant
 iles with normalized marginal distributions. A popular method to estimate 
 conditional quantiles is the quantile regression (Koenker (2005)\, Koenker
  and Bassett (1978)). We discuss the properties and pitfalls of this estim
 ation approach.\n
LOCATION:Seminar Room 1\, Newton Institute
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