similar to: TSeries GARCH Estimates accuracy

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

Hi All, I,m trying to do a GARCH simulation in R 2.3.0 release in Windows XP. I've seen garchsim function but that is for garch (1,1) and ?garch gives an example for ARCH simulation. Can anyone help me how can i extend the help shown in ?garch to GARCH simulation? Please help me in this regard. Thanks, Sumanta Basak.

hello, In my time series data, I was able to successfully fit its ARIMA model (Box-Jenkins) and its GARCH model and estimate their parameters. I was also able to forecast future values of the time series based on my fitted ARIMA model using the predict() function call. However, I'm not sure what is the correct function command to call in order to forecast future values of my time series

Hello again! Is there a way to include a mean in the garch function in the library(tseries), please? I tried include.mean=T in the function statement but it didn't work thanks in advance! R Version 2.2.1 Windows Sincerely, Erin mailto: hodgess at gator.uhd.edu

Dear Sir, First of all Happy Holidays!,... I am writing to you because I am a bit confused about ARCH estimation. Is there a way to find what garch() exactly does, without the need of reading the source code (because I cannot understand it)? In Eviews (the results at the end) I am getting different results than in R (for those that have the program I do: Quick -> Estimage Equation ->

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, 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

I am wondering how to run 'garch' function of 'tseries' package in R2.6.1. I installed R2.3.1 and R2.6.1 in my PC (Windows XP Home) and run a following simple GARCH function in both versions: >garch(dSP[1:300], order = c(1,1)) where 'dSP' is daily return series of a stock index. R2.6.1 can not finish calculation and also I can not stop the

I'm using R 2.1.1 and just successfully installed packages tseries, fseries. I try to run example http://www.maths.lth.se/help/R/.R/library/tseries/html/garch.html But it shows > x.arch <- garch(x, order = c(0,2)) # Fit ARCH(2) Error: couldn't find function "garch" Then I run command > help.search("garch") it shows the R information.

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 =

Hi all, I recently updated my to R 2.6.0 and tseries package ?tseries? version: 0.10-11. When i was using R Version 2.3.1 (2006-06-01) with tseries 'tseries' version: 0.10-7, the code > garch(dflnRCLC1) ***** ESTIMATION WITH ANALYTICAL GRADIENT ***** Call: garch(x = dflnRCLC1) Coefficient(s): a0 a1 b1 4.985e+00 1.880e-01 6.210e-14 > worked very

Hello I want to predict the future values of time series with Garch When I specified my model like this: library(fGarch) ret <- diff(log(x))*100 fit = garchFit(~arma(1,0,0)+garch(1, 1), data =ret) predict(fit, n.ahead = 10) meanForecast meanError standardDeviation 1 0.01371299 0.03086350 0.03305819 2 0.01211893 0.03094519 0.03350248

Dear all, I would like to know that R has the function for garch-t,gjr- garch,qgarch and egarch. Best Regards, Luck

Hi I compared garch results in R with those give by other software and found that their coefficients are different from each other. So I wondered that a convention the garch funcion in R takes. By testing the output, I noticed it seems that garch function in R by default takes such a convention: y(t) = c + sigma(t) where c=0 and sigma(t) = a(0) + a(1)*epsilon^2 + b(1)*sigma(t-1)^2. I also checked

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

Hello, I have just recently started using R and was wondering whether anybody had a code written for White's heteroscedasticity correction for standard errors. Also, can anybody share a code for the GARCH(1,1) and GARCH-in-mean models for modelling regression residuals? Thanks a lot in advance, Spyros --------------------------------- [[alternative HTML version

Hi, What other information should i post? I now have the two versions on the same machine. With R 2.3.1 and tseries 0.10-7 it works fine. With R 2.6.0 and tseries 0.10-11 the function garch doesnt work. The test was made with the same data, in the same machine. The maintainer did not say anything yet. Regards, Jos? Augusto Jr. ---------- Cabe?alho original ----------- De: "Prof Brian

Dear all, I am using GARCH (1,1) model to simulate volatility. But seems that I am missing something about how it works in R. The following code produces negative results, though vola cannot be. What is wrong here? library("fSeries") library("fGarch") spec = garchSpec(model = list(omega = 0.01, alpha = 0.13, beta = 0.86)) gat <- garchSim(spec, n = 10) Thanks a lot!

Dear R users, I am trying to use tseries' garch function in order to determine the volatility of a return series generated by quantmod. Here is the code that I am using: > library(quantmod) > getSymbols("AAPL") convert daily closing prices into continuous log returns > dret<-dailyReturn(AAPL,type='log') check to see that the autocorrelations decay >

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