similar to: multivariate Stochastic Volatility and GARCH

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, I am using GARCH (1,1) model to simulate volatility. But seems that I am missing something about how it works in R. The following code produces negative results, though vola cannot be. What is wrong here? library("fSeries") library("fGarch") spec = garchSpec(model = list(omega = 0.01, alpha = 0.13, beta = 0.86)) gat <- garchSim(spec, n = 10) Thanks a lot!

Hi all , I'm running Debian Etch . I just finished configuring SAMBA as PDC to authenticate against LDAP server which works. The system in question uses default debian etch packages. As My Linix/unix accounts can authenticate against it. The LDAP works. I Used the default shipped smbldap-populate script to setup SAMBA. Everything seems to work as Anonymous User or as user

Hi everybody! I've a large dataset, about 2 Mio entries of the format which I would like to import into a frame: <integer><integer><float><string><float><string><string> Because to the huge data amount I've choosen a binary format instead of a text format when exporting from Matlab. My import function is attached below. It works fine for only

Hi all, Does anybody have the source code of stochastic volatility models in R or Matlab, for example, the Bayesian based or the simulation based SV estimations as described by Prof Eric Zivot in the following discussion? https://stat.ethz.ch/pipermail/r-sig-finance/2005q4/000501.html -------------- I am wondering what is the current status of estimating stochastic vol models and what's

Hi, I noticed your message in the digest and I'm having the same problem. I can get into my Win98 machine use smbclient, but I want to mount the drive in /mnt. But when I go to do that, it whines about client names and the like. Have you managed to do it? If so, can you let me know how as I'm almost tearing my hair out here! - Stuart Luscombe

This script below pulls yahoo data via a function in quantmod, then massages the data around to forumalate a 3D graph with RGL library, attached is a ggplot to show the data i'm trying to create a surface with in separate line geoms . the issue is that the 3D graph looks very ugly and cut up because of the limited quantities of points on the front month expirations.. can anyone tell me whats

Dear All, i want to use garch model in return of stock. and the data should presence volatility cluster (Heteroscedasticity). Do you know how to test volatility cluster (the presence of heteroscedasticity) in series data of stock return in R? Is it using Langrange Multiplier (LM) ARCH test? what package i should use? I really need the help. Thanks for the attention. Eko A P

Hi, I want to calculate the Value at Risk with using some distirbutions and a volatility model. I use the following data(http://uploadeasy.net/upload/cdm3n.rar) which are losses (negative returns) of a company of approx. the last 10 years. So I want to calculated the Value at Risk, this is nothing else than the quantile. Since I have losses I consider the right tail of the distribution. Consider

Hi all, Could anybody point me to some overview/survey papers about using particle filters and sequential monte carlo methods to estimate stochastic volatilities? I couldn't find any such articles giving a big-picture view of the literature. How do these estimation methods compare to EMM and other Bayesian methods for estimating stochastic volatilities? Also, I am looking for some

Ok, I try it again with plain text, with a simple R code example and just sending it to the r list and you move it to sig finance if it is necessary. I try to be as detailed as possible. I want to fit a distribution to my financial data using a volatility model to estimate the VaR. So in case of a normal distribution, this would be very easy, I assume the returns to follow a normal distribution

Hello again, for now I figuered out to send a mp3 stream to IceCast with TCP Socket communication. Now I'm challenged with the correct timing for the data packets. Are there any API calls for getting the state of IceCast's buffer? I'm programming now on a scheduler for sending the mp3 frames, depending on the metada of each frame. I hope, that this is precisly enough. Can you tell

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

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

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

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 >

Hello, i want to estimate a complex GARCH-model (see below). http://r.789695.n4.nabble.com/file/n4112396/GJR_Garch.png W stands for the Day of the Week Dummies. r stands for returns of stock market indices. I stands for the GJR-term. I need some help with three problems: 1.) implementation of the GJR-term in the variance equation 2.) compute robust covariance matrix

Hello all, I am trying to use the "garchFit" function in the fSeries Package to fit a Garch(1,1) Model with t distribution. I am using the following codes. fit <- garchFit(~garch(1,1),data,cond.dist="dstd") fitted(fit) I was expecting the fitted(fit) would return the fitted volatility, but the result turns out to be a series of repeated same value. I tried to change the

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

Hi, as i suppose to know in a stationary GARCH(1,1) model the sum of alpha and beta has to be smaller than 1. But if i use the garchfit() function from the package fGarch for my timeseries the sum is bigger than 1. The adf.test tells me a p-value smaller than 0.01 instead. What does this mean for me? Can i trust in the coefficients in this case? mfg user84 -- View this message in context: