similar to: fSeries GARCH(1,1)

I'm trying to use garchFit from fSeries, with Student or Skewed Student conditionnal distribution. Let's say that eps (vector) is my series of daily log-returns: data(EuStockMarkets) eps = diff(log(EuStockMarkets[,"CAC"])) library(fSeries) g = garchFit(series = eps, formula.var = ~garch(2,2), cond.dist = "dstd") s = g at fit$series All the coefficients are ok

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

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

Good morning everyone, I use for the first time the package fSeries and i try to run the example given by Diethelm Würtz. But when i run its example which is the following # # Example: # Model a GARCH time series process # # Description: # PART I: Estimate GARCH models of the following type ARCH(2) # and GARCH(1,1) with normal conditional distribution functions. # PART II: Simulate

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 have a rather complex problem... I will have to explain everything in detail because I cannot solve it by myself...i just ran out of ideas. So here is what I want to do: I take quotes of two indices - S&P500 and DJ. And my first aim is to estimate coefficients of the DCC-GARCH model for them. This is how I do it: library(tseries) p1 = get.hist.quote(instrument =

Dear all, I'm using garchFit from fSeries package and I am not getting the desired results (error message : could not find function "garchFit" ). Would you please advise as to how I can build an ARIMA(p, d, q) - GARCH(p,q) model using R see the attached data and R-output. Thanking you in advance Kind regards Mangalani Peter Makananisa Statistical Analyst South

---------- 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,

Dear R People: I'm trying to use the garchFit function from the library(fSeries) However, R freezes every time that I use it. Is anyone else having this problem, please? Thanks in advance! R Version 2.2.1 Windows. Sincerely, Erin Hodgess Associate Professor Department of Computer and Mathematical Sciences University of Houston - Downtown mailto: hodgess at gator.uhd.edu

Hello, I have a rather complex problem... I will have to explain everything in detail because I cannot solve it by myself...i just ran out of ideas. So here is what I want to do: I take quotes of two indices - S&P500 and DJ. And my first aim is to estimate coefficients of the DCC-GARCH model for them. This is how I do it: library(tseries) p1 = get.hist.quote(instrument =

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,

Dear R-helper, I wish to implement the APARCH model as described in the fSeries documentation. But I get the following: >library(fSeries) [...] > ?aparchFit No documentation for 'aparchFit' in specified packages and libraries: you could try 'help.search("aparchFit")' > help.search("aparchFit") No help files found with alias or concept or

Hello, I have a univariate data set, and the unconditional variance is 1. I would like to fit a GARCH(1,1) model to the data set with a constraint: \omega (the constant parameter in GARCH(1,1)) is equal to 1-\alpha-\beta. So the unconditional variance can be controled to be \omega /(1-\alpha-\beta) = 1. I was using garchFit (fGARCH package) but did not find the way to control. Any help?

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

I have a problem with garchFit fuction in fSeries package. I found the following reply on one of the R list: "GARCH-Modelling is not easy, and indeed for your dataset the default "Sequential Quadratic Programming" solver doesn't converge. I observed this also for some other time series. There is already an updated version on the server,

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

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()

-Bugs and fixes reported to Diethelm Wuertz. -In the interim. To make the Ox functions part of the fSeries package work please follow the following steps. ------------------------------------------------- 1. Install R-project. 2. Install fSeries. 3. Download: http://www.core.ucl.ac.be/~laurent/G@RCH/site/xbdcons/garch42.zip (G@RCH package for Ox) 4. Download:

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:

Helo, please look at the log below: after loading the fSeries library, I can not use the log function. Is this a bug or what am I doing wrong? Because of this, I'm unable to use the garch library. thanks a lot for any help, Balazs Torma > log(1) [1] 0 > require("fSeries") Loading required package: fSeries Loading required package: robustbase Loading required package: