search for: garchfits

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 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

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 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 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

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] <-

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()

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

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

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) +

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:

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

Hi, Could somebody say if it is possible to compute APARCH-models with garchFit commands. I have earlier used aaa (garchOxFit) and now I try to use bbb (look below) aaa <- garchOxFit(formula.mean=~arma(1,0),formula.var=~aparch(1,1),series=nyk,cond.dist=c('gaussian')) bbb <- garchFit(formula=~arma(1,0)+aparch(1,1),data=nyk) aaa works well, but I need other characteristics of

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, 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, i am a student of tecnical mathematics in austria, and my english is not sooo good, German would be easier, but an answer in english is perfect too. I would need any help to understand the exact output of the function "garchFit". Maybe it would help me just to know what the coefficients are telling me. I do already understand well what functions like arima or garch are doing and

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.

Full_Name: Scott Yonker Version: R for OSX Cocoa OS: Mac OSX Submission from: (NULL) (24.208.185.211) The garchFit function in the Rmetrics libray cannot estimate ARCH models, meaning that the number of beta terms in the model must be greater than zero. For this function neither p nor q can be set to zero without an error. The problem lies in both the specification of the objective function

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, Although my doubt is pretty,as i m not from stats background i am not sure how to proceed on this. Currently i am doing a forecasting.I used ARIMA to forecast and time series was volatile i used garchFit for residuals. How to use the output of Garch to correct the forecasted values from ARIMA. Here is my code: ###delta is the data fit<-arima(delta,order=c(2,,0,1)) fit.res <-