search for: garchsim

...hor: # (C) 2002, Diethelm Wuertz, GPL # ############################################################################ #### # PART I: Estimation: # Settings: set.seed(547) # Bollerslev's GARCH(1,1) with normal innovations: model = list(omega = 1e-6, alpha = 0.1, beta = 0.8, mu = 0) x = garchSim(model, n = 1000) fit = garchFit(as.numeric(x), order = c(1, 1)) print(fit) # Summary and Diagnostic Analysis: summary(fit) # Plot Results: par(mfrow = c(2, 2)) plot(fit) ### Results of the estimations are false. Call: garchFit(x = as.numeric(x), order = c(1, 1)) Coefficient(s): omega...

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.

...CH models. What I would like to do is to perform Monte Carlo simulation. Unfortunately I cannot figure how to modify the code to achieve this. I use the following code to run a single simulation: spec=garchSpec(model=list(ar= 0.440270860, omega=0.000374365,alpha=0.475446583 , mu=0, beta=0)) sim<-garchSim(spec, length(dp)-1,extended=T) Can someone suggest a modification to the code which would allow to obtain multiple simulations? Many thanks, Jurica Brajkovic

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] <- list(garchFit(~garch(1,q),data=data,trace=FALSE)) } Cheers, Marius

...ommand to call in order to forecast future values of my time series using both the fitted ARIMA model and the fitted GARCH model. Using predict() didn't give me the result I was looking for. And I can't find any documentation using help.search, I think what I am looking for is akin to the garchsim and garchpred commands in Mathlab. Any help is appreciated. Thanks!

Hi there, I'm trying to fit a GJR-GARCH Model using fGarch. I wanted to try that by fitting an APARCH model with a fixed delta of 2 and a non-fixed gamma. So I was simply trying to use: spec <- garchFit(~aparch(1,1),data=garchSim(),delta=2) coef(spec) And sometimes, it's working like a charm and delta is indeed exactly 2 in the resulting coefficient vector. Frequently, though, the resulting delta coefficient has some other value, usually somewhere between 0 and 2. Any ideas why? Am I doing something wrong or could thi...

...ng SAS or S-Plus (Finmetrics) and sometimes show a completely different result. I understand that this could be due to the way optimization of MLEs are done, however, I would appreciate any help to obtain consistent results using R. Also is there any garch simulation function available other than garchSim from fseries package? Thanks in advance, Sanjay

...hor: # (C) 2002, Diethelm Wuertz, GPL # ############################################################################ #### # PART I: Estimation: # Settings: set.seed(547) # Bollerslev's GARCH(1,1) with normal innovations: model = list(omega = 1e-6, alpha = 0.1, beta = 0.8, mu = 0) x = garchSim(model, n = 1000) fit = garchFit(as.numeric(x), order = c(1, 1)) print(fit) # Summary and Diagnostic Analysis: summary(fit) # Plot Results: par(mfrow = c(2, 2)) plot(fit) ### Results of the estimations are false. Call: garchFit(x = as.numeric(x), order = c(1, 1)) Coefficient(s): omega...

...s the vector of returns. So the first line of the code is: spec=garchSpec(model=list(ar= 0.440270860, omega=0.000374365,alpha=0.475446583 , mu=0, beta=0))---- The only way I can think of generating 10 000 sample paths is by looping. But in the line of code that tells R to simulate data - sim<-garchSim(simspec, 100000,extended=F) ? I cannot figure out how to make the loop work. I tried to solve this problem by making only one sample path where, for example, instead of making 3 paths each with 100 observations I have one path with 300 observations. But when I do it, I get weird results. Can some...

...lity. 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! [[alternative HTML version deleted]]

Dear R-helpers, I need to read some data from output of garchFit in fGarch. my model is garch(1,1) and i want to read coefficients(omega,alpha,beta) and timeseries(x) and conditional SD(s). because i need them to use in other formula. for example :omega+x[1]+s[3] and maybe i have several simulation then i need a general way to read them, not to read with my eyes for example the quantity of

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

Hello,   Could someone help me please and to tell how to get the probability from empirical DENSITY (not parametric) for each data value (R function). For example, for normal distribution there is such a function like:   “dnorm(q, mean = 0, sd = 1, lower.tail = TRUE, log.p = FALSE)”   I need the same function only for the empirical DENSITY function (which does not correspond to any typical