srch

Hey there, i am new to the forum and deeply grateful to have this stata platform. I have some (more or less) basic questions with analyzing ...

Fit dynamic conditional correlation multivariate GARCH with first- and second-order ARCH components for dependent variables y1 and y2 using tsset data mgarch dcc (y1 y2), arch(1 2) Add regressors x1 and x2 and first-order GARCH component mgarch dcc (y1 y2 = x1 x2), arch(1 2) garch(1) Add z1 to the model for the conditional heteroskedasticity

Mar 21, 2015 · The command in STATA to estimate the DCC model of two variables is: mgarch dcc ( x1 x2=, noconstant) , arch(1) garch(1) distribution(t) $$ \begin{bmatrix} h_1{t} \\ h_2{t} \end{bmatrix} = \begin{bmatrix} w_{10} \\ w_{20} \end{bmatrix} + \begin{bmatrix} a_{11} & a_{12} \\ a_{21} & a_{22}

stata.com mgarch dcc — Dynamic conditional correlation multivariate GARCH models. Description. Quick start. Menu. Syntax. Options. Remarks and examples.

Video Tutorial on Multivariate GARCH DCC Estimation using OxMetrics 6. Providing private online courses in ...

DCC_GARCH Conditional correlation ? Hi I've estimated a DCC-GARCH(1,1) model using STATA. at the end of the stata output, correlation matrix is given and it is also called quasi correlation matrix.

Video Tutorial on Multivariate GARCH DCC Estimation using OxMetrics 6. Providing private online courses in Econometrics Research using Stata, Eviews, R and M...

Show activity on this post. I want to estimate the dynamic conditional correlation GARCH in stata 12. I just ran the following line: mgarch dcc (x y =, noconstant) , arch (1) garch (1) The x and the y variables are log first differences from two price series. My questions are as follows:

Figure 1: Results of GARCH model in STATA. Like ARCH, generate variances for GARCH model using the same command:. predict GTgarch, variance. Here ‘GTgarch’ is the name for predicted series of variances. The results will not appear in ‘Result’ …

Conditional correlation models use nonlinear combinations of univariate GARCH models to represent the conditional covariances. mgarch provides estimators for three popular conditional correlation models—CCC, DCC, VCC—also known as constant, dynamic, and …

26.07.2020 · DCC-GARCH model commands. 27 Jul 2020, 05:18. Dear Statalist, I am doing my dissertation now about the contagion between return prices: UK and US. And follow the literature, I should apply the DCC-GARCH model. I have been looking for the command of this model from stata.com. The independent variables are the lagged of return from the UK and the ...

Mar 04, 2014 · 2 Answers2. Show activity on this post. I assume you want to export to a MS Excel file. Below an example: clear all set more off webuse stocks mgarch dcc (toyota nissan honda = L.toyota L.nissan L.honda, noconstant), arch (1) garch (1) * compute residuals and export to MS Excel predict double resid, residuals export excel using residuals.xls.

Jul 27, 2020 · DCC-GARCH model commands. 27 Jul 2020, 05:18. Dear Statalist, I am doing my dissertation now about the contagion between return prices: UK and US. And follow the literature, I should apply the DCC-GARCH model. I have been looking for the command of this model from stata.com. The independent variables are the lagged of return from the UK and the ...

Title stata.com mgarch dcc — Dynamic conditional correlation multivariate GARCH models DescriptionQuick startMenuSyntax OptionsRemarks and examplesStored resultsMethods and formulas ReferencesAlso see Description mgarch dcc estimates the parameters of dynamic conditional correlation (DCC) multivariate

4mgarch dcc postestimation— Postestimation tools for mgarch dcc Methods and formulas All one-step predictions are obtained by substituting the parameter estimates into the model. The estimated unconditional variance matrix of the disturbances, b, is the initial value for the ARCH and GARCH terms.

Type predict H*,variance; I think log first differences or other types depends on your purpose of setting model, not relevant with Dcc model.

Title stata.com mgarch dcc — Dynamic conditional correlation multivariate GARCH models SyntaxMenuDescriptionOptions Remarks and examplesStored resultsMethods and formulasReferences Also see Syntax mgarch dcc eq eq ::: eq

I've estimated a DCC-GARCH(1,1) model using STATA. at the end of the stata output, correlation matrix is given and it is also called quasi correlation matrix.

Show activity on this post. I want to estimate the dynamic conditional correlation GARCH in stata 12. I just ran the following line: mgarch dcc (x y =, noconstant) , arch (1) garch (1) The x and the y variables are log first differences from two price series. My questions are as follows:

MGARCH stands for multivariate GARCH, or multivariate generalized autoregressive conditional heteroskedasticity. MGARCH allows the conditional-on-past-history covariance matrix of the dependent variables to follow a flexible dynamic structure. Stata fits MGARCH models. mgarch implements diagonal vech and conditional correlation models.

When estimated the DCC-GARCH in stata at the end of the output pairwise quasi correlations are given. What does it mean in practice? is it the mean value of ...

Title stata.com mgarch dcc ... this model is known as the DCC GARCH model. Technical note The DCC GARCH model proposed byEngle(2002) can be written as y t= Cx t+ t t = H 1=2 t H t = D 1=2R tD 1=2 R t= diag(Q t) 1=2Q tdiag(Q t) 1=2 Q t = (1 1 2)R+ 1 e t 1e 0 1 + 2Q t 1 (1) where y t is an m 1 vector of dependent variables;