similar to: Import ARIMA-GARCH coefficients

Displaying 20 results from an estimated 9000 matches similar to: "Import ARIMA-GARCH coefficients"

2009 Jun 04
2
Import ARIMA coefficients
Hello, I need to know how to import ARIMA coefficients. I already determined the coefficients of the model with other software, but now i need to do the forecast in R. For Example: I have a time series named x and i have fitted an ARIMA(1,0,1) (with other software) AR coef = -.172295 MA coef = .960043 (i know that this is not a good model, it's just an example) I try to
2010 Mar 17
1
Reg GARCH+ARIMA
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 <-
2007 Oct 17
1
Time Series - Function to fit ARIMA and GARCH components
I'm searching for a function to fit a conditional mean structure (ARIMA) and a conditional variance structure (GARCH) to a data set for one model. Particularly, I'm trying to fit an IMA(1,1)+GARCH(1,1) model to a data set. However, I can't seem to find a function that will let me specify both the ARIMA and GARCH components. Any help would be appreciated! -- View this message in
2001 Apr 24
1
ARIMA and GARCH
Hello, I would like to study time series with ARIMA and GARCH models. I installed R-Plus and its libraries but when I try to execute the function arima0, It answers that the function does not exist. Could you help me or give me references of papers dealing with arima and garch in R-Plus? Thanks Beno?t, ___________________________________ Mr. Beno?t LACHERON Rue de l'industrie, 44, 1040
2012 Nov 14
0
ARIMA\GARCH forcasting
Hi, I am new to using R and time series analysis in general. I have written code to combine ARIMA + GARCH in forcasting. I am finding it hard to actually get predicted values once I have model built and fit it to data series. i.e. how can I use predict function to give me n.ahead = k number of values. Thanks in advance, Vinay -- View this message in context:
2009 Jun 10
2
Predict GARCH
hello, i was trying to predict values for a garch, so i did: predict(fitgarch,n.ahead = 20) but this doesn't work. Someone can tell me how to get the 20 values ahead of a garch model. thanks in advance _________________________________________________________________ O Windows Live ajuda-o a manter-se em contacto com todos os seus amigos, num só local.
2009 Jun 23
1
Forecast GARCH model
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))
2006 Feb 18
0
question about GARCH - newbie question
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
2011 Jun 13
0
garch() false convergence
Hi, i did in the last month a research about timeseries with the function ARIMA(). Where i had to know how to predict and forecast new datapoints in the future. Not only the things the functions predict() and forecast() can do. All was ok, as the arima function was in the major parts convergent and i did know how to predict for example in a simple ARIMA(x,0,y)-model. Now i have to do the same
2006 Feb 16
2
function for prediting garch
hello, In my time series data, I was able to successfully fit its ARIMA model (Box-Jenkins) and its GARCH model and estimate their parameters. I was also able to forecast future values of the time series based on my fitted ARIMA model using the predict() function call. However, I'm not sure what is the correct function command to call in order to forecast future values of my time series
1999 Oct 07
2
R + GARCH ???
Dear R-Users, are there any ARIMA/GARCH-packages/functions for R? Best regards, M. Fischer -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at
2003 Apr 16
0
arima function - estimated coefficients and forecasts
I'm using the arima function to estimate coefficients and also using predict.Arima to forecast. This works nicely and I can see that the results are the same as using SAS's proc arima. I can also take the coefficent estimates for a simple model like ARIMA(2,1,0) and manually compute the forecast. The results agree to 5 or 6 decimal places. I can do this for models with and without
2011 Jul 13
1
AR-GARCH with additional variable - estimation problem
Dear list members, I am trying to estimate parameters of the AR(1)-GARCH(1,1) model. I have one additional dummy variable for the AR(1) part. First I wanted to do it using garchFit function (everything would be then estimated in one step) however in the fGarch library I didn't find a way to include an additional variable. That would be the formula but, as said, I think it is impossible to add
2006 Nov 20
1
how to forecast the GARCH volatility?
Dear All, I have loaded package(tseries), but when I run predict.garch(...) R tells me could not find function "predict.garch", however ?predict.garch shows me something. I am confused about this. How can I forecast garch volatility? I have tried: predict(...,n.ahead=...),give me fitted value predict(...,n),give me NA,NA
2010 Sep 28
0
Resumen de R-help-es, Vol 19, Envío 26
Hola Andrés.Necesariamente debe ser con boostrap??Te recuerdo que los modelos ARIMA sirven para modelar la media, pero si el componente volátil (varianza) es significativo , debes usar los modelos GARCH, existe una librería para esto (fGarch)R tiene algunas herramientas para pronósticos. Puedes usar la libraría forecast, que tiene algunos modelos de ajuste, también puedes intentar realizando
2009 Nov 06
1
GARCH Models in R
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
2007 Jun 16
1
GLM dist Gamma-links identity and inverse
Dear users; I am doing GLMs with the Gamma distribution, and I always get errors ("no valid set of coefficients: please supply starting values") or warnings ("NaNs produced in log(x)") when I use the links identity or inverse, but I don´t get them if I use the log link. For example: >
2012 Apr 17
2
Manually reconstructing arima model from coefficients
Colleagues I am a new to R but already love it. I have the following problem: I fitted arima model to my time series like this (please ignore modeling parameters as they are not important now): x = scan("C:/data.txt") x = ts(x, start=1, frequency=1) x.fit<-arima(x, order = c(1,0,0), seasonal = list(order=c(0,0,1))) Now I want to use this model for forecasting and backtesting (!).
2009 Jun 22
2
p-values for ARIMA coefficients
Hi, I'm a beginner using R and I'm modeling a time series with ARIMA. I'm looking for a way to determine the p-values of the coefficients of my model. Does ARIMA function return these values? or is there a way to determine them easily? Thanks for your answer Myriam
2009 Jun 19
1
using garchFit() to fit ARMA+GARCH model with exogeneous variables
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