similar to: Forecast GARCH model

Hi, I am trying to fit a multivariate time series model using DCC GARCH model and forecast it. The data looks like this: > head(datax) x vibration_x Speed 1 2017-05-16 17:53:00 -0.132 421.4189 2 2017-05-16 17:54:00 -0.296 1296.8882 3 2017-05-16 17:55:00 -0.572 0.0000 4 2017-05-16 17:56:00 -0.736 1254.2695 5 2017-05-16 17:57:00 0.000

Hi, I am completely new to GARCH models and trying to fit a multivariate time series model using DCC GARCH model and forecast it. The data looks like this: > head(datax) x vibration_x Speed 1 2017-05-16 17:53:00 -0.132 421.4189 2 2017-05-16 17:54:00 -0.296 1296.8882 3 2017-05-16 17:55:00 -0.572 0.0000 4 2017-05-16 17:56:00 -0.736 1254.2695 5

Hello, I'm quite new to R but tried to learn as much as possible in the last few months. My problem is that I would like to estimate the model of Leon et al. (2005). I have shortly summarised the most important equations in the following pdf file: http://hannes.fedorapeople.org/leon2005.pdf My main question is now how could I introduce these two additional terms into the Likelihood

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 <-

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

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: #

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: >

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, 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, 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 am trying to forecast volatility 2 periods forward using a ARCH(1) model: predict(garch(fit2,order=c(0,1),n.ahead=2)) ***** ESTIMATION WITH ANALYTICAL GRADIENT ***** Error in qr(com.hess$hess, ...) : unused argument(s) (n.ahead ...) What did I do wrong? Thank you. Best regards, Peter Arnold, CFA President PRA Investment Counsel, Inc. 704-341-8193 www.prainvestment.com

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

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:

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 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

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 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, I want to fit a mean and variance model jointly. For example I might want to fit an AR(2)-GARCH(1,1) model i.e. r_t = constant_term1 + b*r_t-1 + c*r_t-2 + a_t where a_t = sigma_t*epsilon_t where sigma^2_t = constant_term2 + p*sigma^2_t-1 + q*a^2_t-1 i.e. R estimates a constant_term1, b, c, constant_term2, p, q TIA Aditya

Dear R People: Is there a way to forecast with GARCH modeling as found in tseries, please? When I use the predict command, I get an output of length 100, regardless of what I put in the n.ahead steps. R Version 1.9.0 Thanks in advance. Sincerely, Laura mailto: lauraholt_983 at hotmail.com download! http://toolbar.msn.click-url.com/go/onm00200413ave/direct/01/

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