similar to: GARCH, installing tserise package

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 =

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

Ukech U. Kidi wrote: > dax<- diff(log(DAX_CAC$DAX[1:1865])) > m1<- garch(dax) > Error: couldn't find function "garch" > m1<- garch(dax[1:1865]) > Error: couldn't find function "garch" > m1<- garch(dax[1:1865]) I am sorry, but I forgot to change the addres to r-help in the reply. Well, I am not sure, wheere do you want to get

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 =

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

Hey Guys, i want to do a CAPM-GARCH model. I didn?t find anything posted online. (If there is something - shame on me - i didn?t find it.) My Problem: What is the difference if I let the residuals ?e? follow a garch process ? How do I do my regression analysis now? I began reading about regression analyis with heteroscedasticity, but didn?t get it. So i started programming. First

Dear R users, Could you please help me out. I am in trouble as I am unable to model graphs to explain the GARCH (1 , 1) model, the Hill estimator (of alpha), and the Pareto estimator. I just got introduce to R. I am working on a paper which must be worked from R. You look at the difficulty I had from the text below. [1] "DAX" "DAX_CAC" "DAX_CAC40"

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.

I have done the usual estimation of GARCH models, applied to my historical dataset (commodities futures) with a maximum likelihood function and selected the best model on the basis of information criteria such as Akaike and Bayes. Can somebody explain me please the calibration scheme for a GARCH model? I was not able to find a paper, dealing with exactly this algorithm for my case. I only

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.

Hi R, I have three queries regarding handling GARCH functions in R. Below I document the same: Unlike S-Plus, R doesn't handle Multivariate GARCH models. R has a package for BEKK GARCH model but not for DVEC GARCH models. The GARCH function in S-PLUS has the capability of fixing some model parameters at certain values to evaluate the fit of a particular model. But the same optionality is

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()

tseries_0.3-0 at CRAN now contains the following new features: NelPlo Nelson-Plosser Macroeconomic Time Series garch Fit GARCH Models to Time Series get.hist.quote Download Historical Finance Data jarque.bera.test Jarque-Bera Test na.remove NA Handling Routines for Time Series garch contains a GARCH estimation routine together

tseries_0.3-0 at CRAN now contains the following new features: NelPlo Nelson-Plosser Macroeconomic Time Series garch Fit GARCH Models to Time Series get.hist.quote Download Historical Finance Data jarque.bera.test Jarque-Bera Test na.remove NA Handling Routines for Time Series garch contains a GARCH estimation routine together

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: >

Hi, everyone, I currently run into a problem about DCC-Garch model. I use the package cc-garch and the function dcc.estimation. One of the output of this function is DCC matrix, which shows conditional correlation matrix at every time period you gives. However, I cannot figue out how the function calculate the conditional correlation matrix at the first time period, since there is no data to be

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 >

I need to change the code of Garch to the FCGARCH (a non-linear multi-regime GARCH). I don't know nothing about R. I'd like to know how can I get the code of the garch in order to change it and make the fit for the FC-GARCH. Any non-linear code will be helpfull because if doesn't help in the programming it helps in getting familiar with R. Thank you Renato -- PhD Student Renato

I'm having no luck getting GARCH parameter estimations. It seems simple enough, but I don't know what I'm doing. I'm a newbie both at R and GARCH models, so whatever is going wrong, it's probably very basic. Here's what I do: 1. I first load the tseries package with: library("tseries") 2. I then load the data with: g <-

Hi everybody, I'm trying to fit a Garch(1,1) process to the DAX returns. My data consists of about 2300 10day-logreturns in chronologically descending order (see attachment). But if I use the garch function I get a very high alpha_1 and a quite low beta, which doesn't make that much sense. I think I am missing something, but have no idea what it might be. I'd appreciate it a lot