similar to: garchFit

---------- 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,

Hello, I’ve fitted a Garch(2,1) model with function 'garchFit()' from the package 'fGarch': > m1 <- garchFit(formula = ~garch(2,1),data = X,trace = F) * See 'summary(m1)' OUTPUT BELOW * PROBLEM: My alpha1 term is not significant and I would like to make a NEW model, say m2, that does not contain alpha1, but I am not sure how to specify this with the garchFit()

Hi all, I was trying garchFIt() of fSeries to fit volatility of monthly log returns of S&P500. I tried residuals of normal, student t, skew normal, skew t. But all innovations except normal got exaxtly same coefficients, even if I changed their parameters of skew and shape. Is this correct for the data or something wrong? I am attaching the code, thank you. Muster #GARCH analysis of

I used garchFit function to fit 1600 observations of EURO/USD 2-day returns in GARCH(1,1) model. As part of the summary I got warning message: NaNs produced in: sqrt(diag(fit$cvar)) And didn't get any estimates for 3 params' std.error, t value or probability: Error Analysis: Estimate Std. Error t value Pr(>|t|) mu -0.004827 0.020141 -0.240 0.811 ar1 0.010311

hello everybody, I would like to fit a model to a times series (testing set) for out of sample predictions using garchFit(). I would like to keep the coefficients of ARMA/GARCH model fixed (as found by fitting the model to my training set). The arima fitting function has such an option for that (fixed=NULL) but the garchFit() doesnt. It is very important for me to keep the same coefficients

Dear all, I have problem here : I'm using garchFit from fSeries package, here is part of the script : > data <- read.table("d:/data.txt") > a <- garchFit(~garch(1,1),ts(data)) I also attached the file here. In my experience, I got my R not responding. I also tried with > a <- garchFit(~garch(1,1),ts(data*10)) and it's worked. I

Dear expeRts, How can I specify the order p,q of a GARCH(p,q) model within a loop? Here's a minimal example showing that an "Formula and data units do not match"-error appears: library(fGarch) spec <- garchSpec(model = list(alpha = 0.1, beta = c(0.4, 0.4))) data <- garchSim(spec, n = 100) x <- list() for(q in 1:3){ print(q) x[q] <-

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 using garchFit {fGarch} to fit some GARCH processes. I noticed that the result contains "Log Likelihood" value (right above "Description"), but when I use .. at fit$llh to retrieve Log Likelihood value, the sign switched. I am confused about which value I should choose to report... Any help here? Thanks a lot! Ted -- View this message in context:

Hi all, I post it on both r-help and r-finance since I don't know where is most appropriate for this topic. Sorry if it bothers you. I did garch fitting on S&P500 monthly returns with garchFit from fSeries. I got same coefficients from all cond.dist except normal. I thought that is probabaly usual for the data. But when I play with it, I got another question. I plot skew normal with

Hi, I have a problem using garchFit, when I use : x<-model$resid fit = garchFit(~garch(1, 1), data = x, cond.dist="dst") fit at fitted it gives me error : object "fit" not found Why it doesn't recognize fit? Thanks, Shirin

Hi, as i suppose to know in a stationary GARCH(1,1) model the sum of alpha and beta has to be smaller than 1. But if i use the garchfit() function from the package fGarch for my timeseries the sum is bigger than 1. The adf.test tells me a p-value smaller than 0.01 instead. What does this mean for me? Can i trust in the coefficients in this case? mfg user84 -- View this message in context:

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

Hi, could anyone tell me how predict() predicts the meanError or standardDerivation of a garchFit(1,1)-model, knowing the coefficients mu, omega, alpha1, beta1 and of course all datapoints? Thanks and sorry for my poor english. -- View this message in context: http://r.789695.n4.nabble.com/predict-of-garchFit-tp3826335p3826335.html Sent from the R help mailing list archive at Nabble.com.

Hi, I am attempting to fit a ARMA/GARCH regression model without success. ### ARIMA-GARCH model with regressor ### ### Time series data: A multivariate data set. cov.ts.dq = cov.ts[1:4,"dq1"][!is.na(cov.ts[,"dq1"])] cov.ts.day = ts.intersect(dq = diff(q.ts), day = lag(q.ts, -1)) ### The following R scripts work: (summary(no.day.fitr <- garchFit(dq ~ arma(0,3) +

Dear all, I've recently switched from EViews to R with RMetrics/fSeries (newest version of july 10) for my analysis because of the much bigger flexibility it offers. So far my experiences had been great -prior I had already worked extensively with S-Plus so was already kind of familiar with the language- until I got to the fSeries package. My problem with the documentation of fSeries is that

Hello I am trying to use predict from an arma-Garch model (arma(2, 2) + garch(1, 1)) and I am getting the following error: Error en arima(x = object@data, order = c(max(u, 1), 0, max(v, 1)), init = c(ar, : non-stationary AR part from CSS Does anybody know what can be the reason of this error? The model I have estimated is the following: Title: GARCH Modelling Call: garchFit(formula =

Dear R experts, I am trying to estimate an ARMA 2,2 model with garch errors. I used the following code on R 2.9. #library library(fGarch) #data data1<-ts(read.table("C:/Users/falcon/Desktop/Time Series/exports/goods1.csv"), start=c(1992,1), frequency=12) head(data1) #garch garchFit(formula.mean= ~arma(2,2),formula.var=~garch(1,1), data=data1) but get this error: >

Hello, The function garchFit in the package fGarch allows for choosing a conditional distribution, one of which is the t-distribution. The function allows specification of the shape parameter of the distribution (equal to the degrees of freedom for the t-distribution), for which the default is set to 4. The function also includes an option "include.shape", which is "a logical flag

Dear R users, I need to estimate an ARCH(1,0) model with t-residuals. To do this I use garchFit function from fGarch library. However, I get the following error message: Error in.garchInitParameters (formula.mean = formula.mean, formula.var = formula.var, ): object "alpha" not found I tried to estimate this model with different series, but I always get this error message. For example,