similar to: Help with ugarchspec function

Hi I want to implement Egarch (1,1) with t distribution model using RExcel and VBA. May I know the syntax. Following is the code that I 'm using. rinterface.RRun "spec=ugarchspec(variance.model=list(model=(eGARCH),garchOrder=c(1,1)), mean.model=list(armaOrder=c(1,1), arfima=FALSE), distribution.model=(std))" rinterface.RRun "fit = ugarchfit(Data = b, spec = spec)"

Hi I was trying to implement Egarch (1,1) with Student t distribution using rugarch. But I was not getting any value. Following were the commands that I was using: library(rugarch) spec=ugarchspec(variance.model=list(model="eGARCH", garchOrder=c(1,1)), mean.model=list(armaOrder=c(1,1), arfima=FALSE), distribution.model="std") fit=ugarchfit(data=b,spec=spec) sigma(fit) May I

Let me start with the code: library(quantmod) library(rugarch) getSymbols("SPY", from="1900-01-01") rets=na.trim(diff(log(Cl(SPY)))) tt = tail(rets["/2004-10-29"], 1000) spec = ugarchspec(variance.model=list(garchOrder=c(1,1)), mean.model=list(armaOrder=c(2,5)), distribution.model="sged") for(ii in 1:10) { ttFit = ugarchfit( spec=spec,

Hi, I have used R rmgarch package to implement EGARCH ADCC model from which I can extract conditional covariance matrix. Now I would like to introduce positive and/or negative shocks to see the asymmetric response of covariance. I have come to know that impulse response function (IRF) or volatility IRF is not compatible for any asymmetric models, therefore, the only way to introduce shocks into

Hey, I'm trying to implement a GARCH model with Johnson-Su innovations in order to simulate returns of financial asset. The model should look like this: r_t = alpha + lambda*sqrt(h_t) + sqrt(h_t)*epsilon_t h_t = alpha0 + alpha1*epsilon_(t-1)^2 + beta1 * h_(t-1). Alpha refers to a risk-free return, lambda to the risk-premium. I've implemented it like this: #specification of the model

My code: spec<-ugarchspec(variance.model = list(model = "sGARCH", garchOrder = c(1, 1), submodel = "Null", external.regressors = NULL, variance.targeting = FALSE), mean.model = list(armaOrder=c(0,0),include.mean =FALSE, archm = FALSE, archpow = 1, arfima = FALSE, external.regressors = NULL, archex = FALSE), distribution.model = "norm", start.pars = list(),

Hi, I am trying to fit a multivariate time series model using DCC GARCH model and forecast it. The data looks like this: > head(datax) x vibration_x Speed 1 2017-05-16 17:53:00 -0.132 421.4189 2 2017-05-16 17:54:00 -0.296 1296.8882 3 2017-05-16 17:55:00 -0.572 0.0000 4 2017-05-16 17:56:00 -0.736 1254.2695 5 2017-05-16 17:57:00 0.000

Hi, I am completely new to GARCH models and trying to fit a multivariate time series model using DCC GARCH model and forecast it. The data looks like this: > head(datax) x vibration_x Speed 1 2017-05-16 17:53:00 -0.132 421.4189 2 2017-05-16 17:54:00 -0.296 1296.8882 3 2017-05-16 17:55:00 -0.572 0.0000 4 2017-05-16 17:56:00 -0.736 1254.2695 5

Dear R users, I hope this email finds you well, My name is Mariam and I am currently using R in my thesis project. I is about modeling investors' sentiment. My R skills are very modest and I am trying to solve a Garch in mean equation using the "rgarch" package. The main issue I am facing is with the mean equation, and I need a code for it or a lead on how to edit already existing

Dear All, Sorry to bother. I'd like to estimate GARCH-M( GARCH IN THE MEAN) model. And find that a package called rgarch could help. But I always can't instal rgarch package successfully. I posted my problems and got some suggestions but still failed. Does any one knows other method that could do GARCH-M model? I appreciate your time and help! Cheers, Xi -- View this message in context:

Hey everybody, i am using the rugarch-package and its great! I have a pretty easy problem, but i just dont get it, so thanks if you can help me. Normally i use: / data(DATANAME) spec = ugarchspec() fit = ugarchfit(data = x[,1], spec = spec) fit slotNames(fit) names(fit at fit) coef(fit) infocriteria(fit) likelihood(fit) nyblom(fit) signbias(fit) head(as.data.frame(fit)) head(sigma(fit))

I am sorry to ask this group but the maintainer of this package did not leave an email address. Has anyone used or is using the 'rugarch' package with time-series data (ts)? I try to fit a GARCH model to my data using the following: > gf <- ugarchfit(data=l[["MEN"]]$series, spec=spec) and I get: Error in .extractdata(data) : rgarch-->error: class of

hello, i was trying to predict values for a garch, so i did: predict(fitgarch,n.ahead = 20) but this doesn't work. Someone can tell me how to get the 20 values ahead of a garch model. thanks in advance _________________________________________________________________ O Windows Live ajuda-o a manter-se em contacto com todos os seus amigos, num só local.

Dear all- Package /fGarch/ version 2100.78 in R version 2.8.1 (2008-12-22) running on linux 2.6.22.9-91.fc7 In trying to fit garch models in above environment. I am getting "reasonable" fitted coefficients, but the fitObject@fitted are all the same. This is true even for the help page example: library(fGarch) R> X.timeSeries = as.timeSeries(msft.dat) R> head( +

Hello, I was wondering if anyone knew how to fit a series using a Garch-M (Garch in the mean) model. From what I gathered from the documentation, it does not seem to be implemented in either fGarch, fSeries, or tSeries. Perhaps there is an option that allows this functionality. Otherwise, if it's possible to modify an existing function I would appreciate any guidance on how to go about

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HI, I need urgently garch and egarch models. After looking through the R mail archives I found http://www.egss.ulg.ac.be/garch/default.htm which is an Ox package. After downloading and installing it in R (Version 1.4.1 through the windows dialog "Packages") I received the following warning: install.packages("D:/benjamin/bartels/R/packages/garch22/garch_v22.zip",

Hi, I`m about to switch from STATA to R and have serious troubles to find proper documentations on the internet. Right now I try to find a proper documentation of the eGARCH model being part of the rugarch package. Neither here http://cran.r-project.org/web/packages/rugarch/vignettes/Introduction_to_the_rugarch_package.pdf nor here http://cran.r-project.org/web/packages/rugarch/rugarch.pdf could

Hi, Could you please help me with EGARCH and GJR? Is it possible to use EGARCH and GJR in R? I have used below mentioned code for GARCH in R, but I never used EGARCH and GJR in R. Thank you in advance! daten<-read.table("H://Daten//Zeitreihen//dax_1.csv", sep=";", header=T) DAX.kurs<-daten DAX.kurs<-ts(DAX.kurs,names="DAX-Kurs")

Hallo, I am a student specializing statistics and econometrics in germany. I know there is a way to program EGARCH-processes (time series analyses) in R. If you are ackquainted with statistics already you know that there is nothing but a theorethical use of GARCH-Package in R. Not only because the distribution is gaussian, but also because the skewdness and leptokurthosis are not quite good