Inhomogeneous Dependence Modeling with Time-Varying Copulae

Bibliographic Data

ID19419720
AuthorsEnzo Giacomini (Humboldt-Universität zu Berlin), Wolfgang Karl Härdle (0000-0001-5600-3014, Humboldt-Universität zu Berlin), Wolfgang Härdle, Vladimir Spokoiny (0000-0002-2040-3427, Humboldt-Universität zu Berlin)
Year2009
Volume27
Issue2
Pages224-234
Publication date2009-04-01
Open AccessNo
TypeARTICLE
VenueJournal of Business and Economic Statistics (JOURNAL)
Journal identifiersISSN: 0735-0015 • E-ISSN: 1537-2707
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1198/jbes.2009.0016
OpenAlexW2059680652
LanguageEN
Citations received2
References cited28

Measuring dependence in multivariate time series is tantamount to modeling its dynamic structure in space and time. In risk management, the nonnormal behavior of most financial time series calls for non-Gaussian dependences. The correct modeling of non-Gaussian dependences is, therefore, a key issue in the analysis of multivariate time series. In this article we use copula functions with adaptively estimated time-varying parameters for modeling the distribution of returns. Furthermore, we apply copulae to the estimation of Value-at-Risk of portfolios and show their better performance over the RiskMetrics approach

Econometrics · Economics · Gaussian · Multivariate normal distribution · Multivariate statistics · Risk management · Statistics · Value at risk · Complex Systems and Time Series Analysis · Computer Science · Financial Risk and Volatility Modeling · Market Dynamics and Volatility · Mathematics · Finance · Geology

Tools

Open DOISci-Hub