Regime Switching for Dynamic Correlations

By Denis Pelletier. 2006

436 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/6a94db7d73b799546e4f4f59d51c17ed0e5ee0b0

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Citations in the corpus

Modelling multivariate volatilities via conditionally uncorrelated components (2008, methodology): “The forecast for the DCC model follows the procedure of Pelletier (2006).”
Estimation and Forecasting of Dynamic Conditional Covariance: A Semiparametric Multivariate Model (2009, methodology): “The exceptions include the regime switching dynamic conditional correlation model of Pelletier (2006), the smooth transition conditional correlation (STCC) model by Silvennoinen and Teräsvirta (2005), and the asymmetric dynamic conditional correlation model by Cappiello, Engle, and Sheppard (2003),…”
Modeling Conditional Correlations of Asset Returns: A Smooth Transition Approach (2015, methodology): “In this respect the model differs from most other dynamic conditional correlation models such as the ones proposed by Tse and Tsui (2002), Engle (2002), and Pelletier (2006).”
Estimating multivariate volatility models equation by equation (2016, methodology): “This approach, which was initially proposed by Engle and Sheppard (2001) and Engle (2002) in the context of DCC models, was advocated by Pelletier (2006) for regime switching dynamic correlation models and by Aielli (2013) for DCC models, and it was used in several empirical studies (see for…”
Conditional Correlation Models of Autoregressive Conditional Heteroscedasticity With Nonstationary GARCH Equations (2014, methodology): “To compare the accuracy of the one-day-ahead covariance matrix forecasts we use the following criteria (Pelletier, 2006): RMSE1 = {(1/N) ∑ i,j E(Σi,j,t+1|t − yi,t+1yj,t+1)} and MAD1 = (1/N ) ∑ i,j E|Σi,j,t+1|t − yi,t+1yj,t+1|”
Multivariate GARCH models (2008, positive): “If N is not very small, Pelletier (2006) recommends two-step estimation.”
A Component Model for Dynamic Correlations (2011, background): “Pelletier (2006). Regime-switching DCC models may be also thought of has capturing changes in the overall level of correlation (albeit with revisiting regularly the same regime through time).”
Volatility Transmission Models: A Survey (2006, positive): “Several studies highlight the relevance of the variable trade volume as explicative variable for the conditional variance (see Peña (1992), Pyun et al.”
Modeling multivariate autoregressive conditional heteroskedasticity with the double smooth transition conditional correlation GARCH Model (2009, positive): “An interesting model combining aspects from both the CCC–GARCH and the DCC–GARCH has been suggested by Pelletier (2006).”
Efficient estimation of a multivariate multiplicative volatility model (2010, neutral): “Therefore, √ Th(σ̂(u)− σ(u)) = ∆(u) √ Th ( θ̂(u)− θ(u) ) + op(1) and so (29) follows.”
Financialization, Crisis and Commodity Correlation Dynamics (2013, methodology): “where 0 is the true parameter and J 1 ( 0) is the population information matrix evaluated at = 0: Estimation follows a similar process to that outlined in Silvennoinen and Teräsvirta (2009). We divide the parameter vector into two sets: parameters for the correlations and for the transition function”