Reduced form vector directional quantiles
Gabriel Montes-Rojas ()
Journal of Multivariate Analysis, 2017, vol. 158, issue C, 20-30
In this paper, we develop a reduced form multivariate quantile model, using a directional quantile framework. The proposed model is the solution to a collection of directional quantile models for a fixed orthonormal basis, in which each component represents a directional quantile that corresponds to a particular endogenous variable. The model thus delivers a map from the space of exogenous variables (or the σ-field generated by the information available at a particular time) and a unit ball whose dimension is given by the number of endogenous variables, to the space of endogenous variables. The main effect of interest is that of exogenous variables on the vector of endogenous variables, which depends on a multivariate quantile index. An estimator is proposed, using quantile regression time series models, and we study its asymptotic properties. The estimator is then applied to study the interdependence among countries in the European sovereign bonds credit default swap market.
Keywords: Credit default swaps; Multivariate quantiles; Multivariate time-series; Vector autoregression (search for similar items in EconPapers)
JEL-codes: C13 C14 C42 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:158:y:2017:i:c:p:20-30
Ordering information: This journal article can be ordered from
https://shop.elsevie ... _01_ooc_1&version=01
Access Statistics for this article
Journal of Multivariate Analysis is currently edited by de Leeuw, J.
More articles in Journal of Multivariate Analysis from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().