similar to: ARMA-GARCH package in R?

Hello Following some standard textbooks on ARMA(1,1)-GARCH(1,1) (e.g. Ruey Tsay's Analysis of Financial Time Series), I try to write an R program to estimate the key parameters of an ARMA(1,1)-GARCH(1,1) model for Intel's stock returns. For some random reason, I cannot decipher what is wrong with my R program. The R package fGarch already gives me the answer, but my customized function

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 all R user, Please forgive me if my problem is too simple. Actually my problem is basically Statistical rather directly R related. Suppose I have return series ret with mean zero. And I want to fit a Garch(1,1) on this. my is r[t] = h[i]*z[t] h[t] = w + alpha*r[t-1]^2 + beta*h[t-1] I want to estimate the three parameters here; the R syntax is as follows: #

Thank you so much all for your invaluable inputs. On Sat, Jun 4, 2011 at 3:36 AM, Patrick Burns <patrick at burns-stat.com> wrote: > A common thing to do is the Ljung-Box > test on the residuals. ?For garch it > would be the residuals squared. > > Actually for garch it should be the > rank of the squared residuals -- see >

Hi, i am working in the forecast of the daily price crude . The last prices of this data are the following: 100.60 101.47 100.20 100.06 98.68 101.28 101.05 102.13 101.70 98.27 101.00 100.50 100.03 102.23 102.68 103.32 102.67 102.23 102.14 101.25 101.11 99.90 98.53 96.76 96.12 96.54 96.30 95.92 95.92 93.45 93.71 96.42 93.99 93.76 95.24 95.63 95.95 95.83 95.65

Hello R-list-members, I'm trying to model ARMA(0,2) & GARCH(1,1) process using the code below, but according to my textbook, the estimated parameters are wrong. The MA-parameters should be negative. (I've got the same problem using garchFit()). Can anyone tell me what I'm doing wrong? And how can I calculate the hessian matrix? Many thanks, Desislava Kavrakova Code:

Dear everyone, i`m a german economics student, writing my master´s thesis about "Multivariate Volatility Models". After having read about theoretical aspects of Multivariate GARCH ans Stochastic Volatility Models, I would like to compare DCC-GARCH and DC-SV with help of an empirical application. I figuered out that one has to use MCMC-simulation-methods for that. Some days ago I

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 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 all, I got the daily stock return data from 2005 - 2008, calculated from HF minute data. (Thanks to Jeff and Josh). Now, I set 05 - 07yr as the carlibration period for estimating the parameters of ARMA(1,1)-GARCH(1,1) model, aqnd leave 08 for backtesting. So I use the return data observations from 1:760 (yr 05-07) to estimate the volatility on 2nd-Jan-08 (the position 761), then use the

Hi, I've fitted a GARCH(1,1) for the residuals of my time serie (X). X is an ARMA(1,1) process. Now I want to do a n-step forecast for X, knowing these processes. How can I do this? I know that there's a command: predict() for ARIMA processes and so on, but what about GARCH? I've got: arma=arima(x, order=c(1,0,1)) (...) garch11<-garch(residuals(x),order = c(1, 1))

Hello all, I would like how to modelized a time serie with AR-ARCH process. It can be used arma and garch functions in tseries package for build ar process or a garch process, but how can it be modelized a ar-garch model ? Thanks [[alternative HTML version deleted]]

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 <-

Hi R users, Heard that I can't use multivariate GARCH model in R because R has only univariate GARCH models.... So, how can I run a multivariate GARCH model in R? Also, SPLUS has this utility...any ideas how can I use it in R? Thanks Shubha [[alternative HTML version deleted]]

hello, I have been looking at multiple websites on GARCH and have looked at some books and I am getting contradictory models given for GARCH. If I use the GARCH function to fit my model, I am confused as to what the coefficents given refer to. For example if I fit a GARCH(1,1) model, GARCH will give me three coefficients Ao, Ai, and Bi I know Ao refers to the constant of the model. But what

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 =

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

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 aDVISOR, Hope I am not disturbing you. Can you tell me how I can perform Multivariate Garch analysis in R. Also please, it is my humble request let me know some resource materials on Multivariate Garch analysis itself. Sincerely yours, -- Arun Kumar Saha, M.Sc.[C.U.] S T A T I S T I C I A N [Analyst] Transgraph Consulting [www.transgraph.com] Hyderabad, INDIA Contact # Home:

Hi , Are there any multivariate GARCH package (e.g., BEKK) in R? I do see a few "projects" constructing multivariate GARCH package, but wonder if there is anyone that is ready for use. Thanks, Miao [[alternative HTML version deleted]]