Testing and Valuing Dynamic Correlations for Asset Allocation

By Robert F. Engle, Riccardo Colacito. 2006

313 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/eabc00521a21bf7e6ed5fa5668a1d8711d636c68

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Citations in the corpus

Modeling multivariate autoregressive conditional heteroskedasticity with the double smooth transition conditional correlation GARCH Model (2009, unknown): “This data set has been analyzed by Engle and Colacito (2006) .2 There is no consensus in the literature about how stock and”
MGARCH models: Trade-off between feasibility and flexibility (2018, background): “…returns; see, for example, Bollerslev et al. (1988), Attanasio (1991), De Santis and Gerard (1997), Hansson and Hordahl (1998), Lien and Tse (2002), Engle and Colacito (2006), Andersen et al. (2007), McNeil et al. (2010), Santos et al. (2012) and Santos et al. (2013), for a few selected asset…”
Analytical nonlinear shrinkage of large-dimensional covariance matrices (2020, unknown): “Further justiﬁcation for the minimum variance (MV) loss function is provided by Engle and Colacito (2006) and Ledoit and Wolf (2017a).”
Evaluating Volatility and Correlation Forecasts (2009, background): “16 Recent work by Engle and Colacito [24] has shown that it is possible to rank covariance forecasts using this more general mean-variance optimisation problem.”
Multivariate GARCH models (2008, unknown): “This data set has been analyzed by Engle and Colacito (2006) .”
A Component Model for Dynamic Correlations (2011, methodology): “…and bonds.7 The equity portfolios are formed based on an industry classification.8 The second example focuses on the economic significance of the new models we propose in the paper and uses the methodology proposed by Engle and Colacito (2006) pertaining to minimum variance portfolio management.”
Effectiveness of copula-extreme value theory in estimating value-at-risk: empirical evidence from Asian emerging markets (2012, methodology): “One of the possible solutions is to apply the dynamic conditional correlation (DCC) model proposed by Engle (2002) and Engle and Colacito (2006).”
Selecting volatility forecasting models for portfolio allocation purposes (2015, background): “Engle & Colacito (2006) and Patton & Sheppard (2009) have demonstrated that portfolio variance is minimised when the correct forecast is applied.”
Conditional Correlation Models of Autoregressive Conditional Heteroscedasticity With Nonstationary GARCH Equations (2014, methodology): “Fourier Flexible Form of Gallant (1981). Amado and Teräsvirta (2012, 2013) described the nonstationary component by a linear combination of logistic functions of time and their generalisations and developed a data-driven specification technique for determining the parametric structure of the time-va”
Large Dynamic Covariance Matrices (2019, background): “This section builds upon Engle and Colacito (2006), hereafter abbreviated by EC.”