A review of copula models for economic time seriesAndrew J. Patton2012-04-04articleJournal of Multivariate Analysis587 citationsbronzeNo readable copy stored yet — this record is metadata only.Financial Risk and Volatility ModelingStatistical Distribution Estimation and ApplicationsComplex Systems and Time Series AnalysisAbstractNo abstract was published for this record.Citations in this libraryStored only when both papers are in the corpus — 587 citations exist upstream.References1986Generalized autoregressive conditional heteroskedasticity1982Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation1989A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle1993On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks1999An Introduction to Copulas2002Dynamic Conditional Correlation2001Extreme Correlation of International Equity Markets1987A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of ReturnCited by2018Conditional Tail-Risk in Cryptocurrency Markets2013Copula Methods for Forecasting Multivariate Time Series2018Modelling dynamic dependence and risk spillover between all oil price shocks and stock market returns in the BRICSn.d.Quantile Coherency: A General Measure for Dependence between Cyclical Economic Variables2012The structure and degree of dependence: A quantile regression approach2018Uncertainties and extreme risk spillover in the energy markets: A time-varying copula-based CoVaR approach2018Risk dependence of CoVaR and structural change between oil prices and exchange rates: A time-varying copula model2017Measuring systemic risk in the European banking sector: a copula CoVaR approach