similar to: rugarch: GARCH with Johnson Su innovations

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 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 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)"

Dear Users, I would like to simulate an AR(1) (y_t=ct1+y_t-1+e_t) model in R where the innovations are supposed to follow a t-GARCH(1,1) proccess. By t-GARCH I want to mean that: e_t=n_t*sqrt(h_t) and h_t=ct2+a*(e_t)^2+b*h_t-1. where n_t is a random variable with t-Student distribution. If someone could give some guidelines, I can going developing the model. I did it in matlab, but the loops

Dear all, I have a serious problem to solve my model. I study over exploitation of fish in the bay of biscay (france). I know only the level of catch and the fishing effort (see data below) by year. My model is composed by the following equations: * the growth function Gt(St) = r*St*(1-St/sbar) with Gt the growth of each period t r intrinsec growth of the stock sbar carriyng capacity of the

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

Hi I am using the ugarchspec function from the rgarch package to fit a mean variance model jointly. Following is the code I'm using: > spec = ugarchspec(variance.model = list(model="eGARCH", garchOrder=c(1,1)), mean.model = list(armaOrder=c(1,1))) On doing this, I get the following error: Error in ugarchspec(variance.model = list(model = "eGARCH", garchOrder = c(1,

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

Hi, i am unable to install the rugarch package. More than that i do not even find this package in my list of possible packages. Its possible than the name has changed, or the package is not longer availiable? Is there a similar package avaliable for garch modelling except the fGarch what i am using now? many Thanks Roland -- View this message in context:

Dear all, I want to backtest my Value at Risk output using the VaRTest() function in the rugarch package. I do not understand if the numeric vector of VaR which needs to be calculated is in negative or positive terms. Usually VaR is expressed in positive terms. Do I have to use positive values for VaR in the VaRTest() formula? Thanks for your help. [[alternative HTML version deleted]]

Hi guys, does anyone know if there is the possibility to fit a gamma distribution using ugarch?honestly i don't know if maybe is possible to fix some parameters that reduce ghyp or ged in a gamma distribution.. thanks a lot sara -- View this message in context: http://r.789695.n4.nabble.com/gamma-distribution-in-rugarch-package-tp4637893.html Sent from the R help mailing list archive at

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

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

I can't install rugarch package because installation of nloptr package fails . I use opensuse 12.3 # uname -a Linux candide 3.7.10-1.11-desktop #1 SMP PREEMPT Thu May 16 20:27:27 UTC 2013 (adf31bb) x86_64 x86_64 x86_64 GNU/Linux my gcc version is 4.8.1 I compiled and installed R 3.01 . then I tried to install rugarch package but it fails because it can't install depended package nloptr.

Hello - Here's what I'm trying to do. I want to fit a time series y with ARMA(1,1) + GARCH(1,1), there are also an exogeneous variable x which I wish to include, so the whole equation looks like: y_t - \phi y_{t-1} = \sigma_t \epsilon_t + \theta \sigma_{t-1} \epsilon_{t-1} + c x_t where \epsilon_t are i.i.d. random variables \sigma_t^2 = omega + \alpha \sigma_{t-1}^2 + \beta

---------- Forwarded message ---------- From: ma yuchao <ma.yuchao@gmail.com> Date: 2006-5-20 ÉÏÎç4:01 Subject: hello, everyone To: R-help@stat.math.ethz.ch Hello, R people: I have a question in using fSeries package--the funciton garchFit and garchOxFit if adding a regression to the mean formula, how to estimate the model in R? using garchFit or garchOxFit? For example,

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))

-- View this message in context: http://r.789695.n4.nabble.com/Generalized-DCC-GARCH-ML-estimation-tp2245125p2245125.html Sent from the R help mailing list archive at Nabble.com.