Robust forecasting of dynamic conditional correlation GARCH modelsKris Boudt, Jón Danı́elsson, Sébastien Laurent2012-12-23articleInternational Journal of Forecasting84 citationsclosedNo readable copy stored yet — this record is metadata only.Financial Risk and Volatility ModelingStochastic processes and financial applicationsStock Market Forecasting MethodsAbstractNo abstract was published for this record.Citations in this libraryStored only when both papers are in the corpus — 84 citations exist upstream.References1993On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks2002Dynamic Conditional Correlation1995Comparing Predictive Accuracy1995Multivariate Simultaneous Generalized ARCH2003Modeling and Forecasting Realized Volatility1990Modelling the Coherence in Short-Run Nominal Exchange Rates: A Multivariate Generalized Arch Model1993A long memory property of stock market returns and a new modeln.d.Multivariate GARCH models: a surveyCited by2019Volatility estimation for Bitcoin: Replication and robustness2014Large shocks in the volatility of the Dow Jones Industrial Average index: 1928–20132014Testing for jumps in conditionally Gaussian ARMA–GARCH models, a robust approach2019Value-at-risk and expected shortfall in cryptocurrencies’ portfolio: a vine copula–based approach2015Forecasting realized volatility: HAR against Principal Components Combining, neural networks and GARCH