similar to: Reg GARCH+ARIMA

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

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

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 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 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) +

Hi, we have a problem concerning the use and forecasting on the GARCH (1, 1) on financial data. We would like to make predictions on future returns in a loop which moves the window of estimation forward one unit for each iteration. Our code is as follows: > BJORN <- read.table("C:/Users/Osvald/Desktop/DATATILLUPPSATS.txt", + header=TRUE, sep="\t",

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

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

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: >

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] <-

Hallo, i want to fit a GARCH model with a extern regressor (without arma components), so i found the following function in package fGarch. I tryed out a lot of things but usually I get this Error. > garchFit(formula=y~x, formula.var=~garch(1,1),data=w) Error in .garchFit(formula.mean, formula.var, series = x, init.rec, delta, : Algorithm only supported for mci Recursion I think i use the

Hi, I have a NN model build using AMORE and NNET.If i want to reuse the model built on later date.How can i store this model.In what format should i need to store the model.I wont be saving the session.I want to just store the model and recall this model whenever required.Is it possible to store? If yes,can someone provide any packages available. Regards, Raghav [[alternative HTML version

Hello, I have a few questions concerning the DCC-GARCH model and its programming in R. So here is what I want to do: I take quotes of two indices - S&P500 and DJ. And the 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 = "^gspc",start = "2005-01-07",end =

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 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

Hi there I want to cbind a vector(contains 20 values) to a dataframe containg (18 rows).The missing value in the dataframe is however a repeated values but still i want to retain the repeats in the vector and the dataframe values can even get enterd twice. how should i go about it Example: Vector(contains repeating entry) ab de dc ab be dataframe(unique entry) ab a b c d e dc e f g h i de l

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, 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 =

I'm trying to estimate the parameters for GARCH(1,1) process. Here's my code: loglikelihood <-function(theta) { h=((r[1]-theta[1])^2) p=0 for (t in 2:length(r)) { h=c(h,theta[2]+theta[3]*((r[t-1]-theta[1])^2)+theta[4]*h[t-1]) p=c(p,dnorm(r[t],theta[1],sqrt(h[t]),log=TRUE)) } -sum(p) } Then I use nlminb to minimize the function loglikelihood: nlminb(

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