Quantile coherency: A general measure for dependence between cyclical economic variables
Result description
In this paper, we introduce quantile coherency to measure general dependence structures emerging in the joint distribution in the frequency domain and argue that this type of dependence is natural for economic time series but remains invisible when only the traditional analysis is employed. We define estimators that capture the general dependence structure, provide a detailed analysis of their asymptotic properties, and discuss how to conduct inference for a general class of possibly nonlinear processes. In an empirical illustration we examine the dependence of bivariate stock market returns and shed new light on measurement of tail risk in financial markets. We also provide a modelling exercise to illustrate how applied researchers can benefit from using quantile coherency when assessing time series models.
Keywords
The result's identifiers
Result code in IS VaVaI
Alternative codes found
RIV/00216208:11230/19:10399926
Result on the web
https://academic.oup.com/ectj/article-abstract/22/2/131/5303852
DOI - Digital Object Identifier
Alternative languages
Result language
angličtina
Original language name
Quantile coherency: A general measure for dependence between cyclical economic variables
Original language description
In this paper, we introduce quantile coherency to measure general dependence structures emerging in the joint distribution in the frequency domain and argue that this type of dependence is natural for economic time series but remains invisible when only the traditional analysis is employed. We define estimators that capture the general dependence structure, provide a detailed analysis of their asymptotic properties, and discuss how to conduct inference for a general class of possibly nonlinear processes. In an empirical illustration we examine the dependence of bivariate stock market returns and shed new light on measurement of tail risk in financial markets. We also provide a modelling exercise to illustrate how applied researchers can benefit from using quantile coherency when assessing time series models.
Czech name
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Czech description
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Classification
Type
Jimp - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
50201 - Economic Theory
Result continuities
Project
GA16-14179S: New measures of dependence between economic variables
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Econometrics Journal
ISSN
1368-4221
e-ISSN
—
Volume of the periodical
22
Issue of the periodical within the volume
2
Country of publishing house
GB - UNITED KINGDOM
Number of pages
22
Pages from-to
131-152
UT code for WoS article
000493351000003
EID of the result in the Scopus database
2-s2.0-85063408023
Basic information
Result type
Jimp - Article in a specialist periodical, which is included in the Web of Science database
OECD FORD
Economic Theory
Year of implementation
2019