Dynamic Conditional Correlation

By Robert F. Engle. 2002

5,484 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/70152f0a5d7090530b888437f5c022e541dc9fd3

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Citations in the corpus

Conditional Euro Area Sovereign Default Risk (2014, positive): “To limit the number of free parameters in the nonlinear optimization problem, we use a correlation targeting approach similar to Engle (2002), Hu (2005), and other studies that are based on a multivariate GARCH framework.”
Developing a stress testing framework based on market risk models (2008, methodology): “While a number of these approaches are potentially useful for stress testing applications, the dynamic conditional correlation method of Engle (2002) is arguably the most useful for portfolios with many assets.”
Asymmetric Volatility, Correlation and Returns Dynamics between the U.S. and U.K. Securitized Real Estate Markets (2006, neutral): “Engle (2002) has shown that observed conditional correlations from different GARCH models can lead to sometimes substantial differences.”
COVID-19 and the Oil Price – Stock Market Nexus: Evidence From Net Oil-Importing Countries (2020, methodology): “We then implement the DCC-GARCH model proposed by Engle (2002) to calculate the time-varying correlation between stock price returns and oil price returns.”
Market interdependence and volatility transmission among major crops (2016, methodology): “4 The BEKK model corresponds to Engle and Kroner (1995) multivariate model also known as Baba, Engle, Kroner and Kraft model; the DCC model is based on Engle (2002).”
Modelling the Dynamic Dependence Structure in Multivariate Financial Time Series (2007, methodology): “Our copula-based model can be regarded as an extension of the standard and the generalized dynamic conditional correlation (DCC) model (Engle, 2002; Cappiello et al., 2003) to a Student copula.”
Better to give than to receive: Predictive directional measurement of volatility spillovers (2012, background): “…it will be interesting in 19 future work to understand better the relationship of our spillover measure to a variety of others based on measures ranging from traditional (albeit time-varying) correlations (e.g., Engle, 2002, 2009) to the recently-introduced CoVaR of Adrian and Brunnermeier (2008).”
Sequential Conditional Correlations: Inference and Evaluation (2009, methodology): “While the CCC model of Bollerslev (1990) and the DCC proposed by Engle (2002) separate the variances from the correlations, allowing for a two-step estimation procedure, SCC further separates the correlations and partial correlations, thus allowing for a true multi-step estimation procedure.”
Merits and Drawbacks of Variance Targeting in GARCH Models (2011, methodology): “In particular, in a multivariate framework, "correlation targeting" has been considered by Engle (2002) for the specification of the dynamic conditional correlation model.”
Risk management with high-dimensional vine copulas: An analysis of the Euro Stoxx 50 (2013, methodology): “Multivariate GARCH models such as the popular DCC model by Sheppard and Engle (2001) and Engle (2002) however use only covariances for dependence modeling among time series, while maintaining positive definite covariance matrices.”
Bitcoin for energy commodities before and after the December 2013 crash: diversifier, hedge or safe haven? (2017, positive): “First, this article employs a bivariate asymmetric DCC model proposed by Cappiello, Engle, and Sheppard (2006) in extension of the standard DCC of Engle (2002) used by Ratner and Chiu (2013).”