Dynamic Cross-Correlation Model Fitting

Description

Fits a DCC model using either multivariate Gaussian or multivariate Student-t innovations. Two types of DCC models are available. The first type is proposed by Engle and the other is by Tse and Tsui. Both models appear in the Journal of Business and Economic Statistics, 2002.

Usage

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dccFit(rt, type = "TseTsui", theta = c(0.9, 0.02), 
    ub = c(0.92, 0.079999), lb = c(0.4, 1e-04), 
    cond.dist = "std", df = 7, m = 0)

Arguments

rt

The T-by-k data matrix of k-dimensional standardized asset returns. Typically, they are the standardized residuals of the command dccPre.

type

A logical switch to specify the type of DCC model. Type="TseTsui" for Tse and Tsui's DCC model. Type = "Engle" for Engle's DCC model. Default is Tse-Tsui model.

theta

The initial parameter values for theta1 and theta2

ub

Upper bound of parameters

lb

Lower bound of parameters

cond.dist

Conditional innovation distribution with std for multivariate Student-t innovations.

df

degrees of freedom of the multivariate Student-t innovations.

m

For Tse and Tsui method only, m denotes the number of returns used in local correlation matrix estimation

Value

estimates

Parameter estimates

Hessian

Hessian marix of the estimates

rho.t

Time-varying correlation matrices. Each row contains elements of a cross-correlation matrix.

Author(s)

Ruey S. Tsay

References

Tsay (2014, Chapter 7). Multivariate Time Series Analysis with R and Financial Applications. John Wiley. Hoboken, NJ.

See Also

dccPre

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