similar to: gamma distribution in rugarch package

Sir, I am working on fitting distribution on multivariate financial data and then simulate observations from that fitted distribution. I use stepAIC.ghyp() function of 'ghyp' library which select the best fitted distribution from generalized hyperbolic distribution class on the given dataset. data(indices) # Multivariate case: aic.mv <- stepAIC.ghyp(indices, dist =

I was playing around with the ghyp package and simulated series of t-distributed variables when suddenly i was not able to reproduce the log likelihood values reported by the package. When trying to reproduce the likelihood values, I summed the log(dt(x,v)) values and it worked with some simulated series but not all. Is there any obvious flaws with this script? library("ghyp")

hi guys, i have some trouble in creating lagged variables to use as external regressors. i'm trying to use lag(x) but it gives me as result the same time series (x), adding this part at the end: attr(,"tsp") [1] 0 2323 1 where do i wrong?are there other functions to be used? thanks sara -- View this message in context:

Hi, I`m about to switch from STATA to R and have serious troubles to find proper documentations on the internet. Right now I try to find a proper documentation of the eGARCH model being part of the rugarch package. Neither here http://cran.r-project.org/web/packages/rugarch/vignettes/Introduction_to_the_rugarch_package.pdf nor here http://cran.r-project.org/web/packages/rugarch/rugarch.pdf could

My code: spec<-ugarchspec(variance.model = list(model = "sGARCH", garchOrder = c(1, 1), submodel = "Null", external.regressors = NULL, variance.targeting = FALSE), mean.model = list(armaOrder=c(0,0),include.mean =FALSE, archm = FALSE, archpow = 1, arfima = FALSE, external.regressors = NULL, archex = FALSE), distribution.model = "norm", start.pars = list(),

Hi I was trying to implement Egarch (1,1) with Student t distribution using rugarch. But I was not getting any value. Following were the commands that I was using: library(rugarch) spec=ugarchspec(variance.model=list(model="eGARCH", garchOrder=c(1,1)), mean.model=list(armaOrder=c(1,1), arfima=FALSE), distribution.model="std") fit=ugarchfit(data=b,spec=spec) sigma(fit) May I

Hi, i am unable to install the rugarch package. More than that i do not even find this package in my list of possible packages. Its possible than the name has changed, or the package is not longer availiable? Is there a similar package avaliable for garch modelling except the fGarch what i am using now? many Thanks Roland -- View this message in context:

I created a EM algorithm for Generalized hyperbolic distribution. I want to estimate mutheldaplus, sigmatheldaplus, betasigmaplus in my code. After getting use these value , then my iteration have to be begin of this code. But I can not to do iteration part. Can you help me use my code and get iteration ? Do know any useful code for EM algorithm for Generalized Hyperbolic library(QRMlib)

Let me start with the code: library(quantmod) library(rugarch) getSymbols("SPY", from="1900-01-01") rets=na.trim(diff(log(Cl(SPY)))) tt = tail(rets["/2004-10-29"], 1000) spec = ugarchspec(variance.model=list(garchOrder=c(1,1)), mean.model=list(armaOrder=c(2,5)), distribution.model="sged") for(ii in 1:10) { ttFit = ugarchfit( spec=spec,

Dear all, I want to backtest my Value at Risk output using the VaRTest() function in the rugarch package. I do not understand if the numeric vector of VaR which needs to be calculated is in negative or positive terms. Usually VaR is expressed in positive terms. Do I have to use positive values for VaR in the VaRTest() formula? Thanks for your help. [[alternative HTML version deleted]]

I am sorry to ask this group but the maintainer of this package did not leave an email address. Has anyone used or is using the 'rugarch' package with time-series data (ts)? I try to fit a GARCH model to my data using the following: > gf <- ugarchfit(data=l[["MEN"]]$series, spec=spec) and I get: Error in .extractdata(data) : rgarch-->error: class of

I can't install rugarch package because installation of nloptr package fails . I use opensuse 12.3 # uname -a Linux candide 3.7.10-1.11-desktop #1 SMP PREEMPT Thu May 16 20:27:27 UTC 2013 (adf31bb) x86_64 x86_64 x86_64 GNU/Linux my gcc version is 4.8.1 I compiled and installed R 3.01 . then I tried to install rugarch package but it fails because it can't install depended package nloptr.

Dear R-users I would like to integrate something like \int_k^\infty (1 - F(x)) dx, where F(.) is a cumulative distribution function. As mentioned in the "integrate" help-page: integrate(dnorm,0,20000) ## fails on many systems. This does not happen for an adaptive Simpson or Lobatto quadrature (cf. Matlab). Even though I am hardly familiar with numerical integration the implementation

Hey, I'm trying to implement a GARCH model with Johnson-Su innovations in order to simulate returns of financial asset. The model should look like this: r_t = alpha + lambda*sqrt(h_t) + sqrt(h_t)*epsilon_t h_t = alpha0 + alpha1*epsilon_(t-1)^2 + beta1 * h_(t-1). Alpha refers to a risk-free return, lambda to the risk-premium. I've implemented it like this: #specification of the model

Greetings: I'm in the situation where I'm trying to splash information picked off by an asterisk IVR into a Cisco call center environment. I'm under the impression that the ONLY way to do this is to setup socket connections with the Cisco "voice processor", or CVP, and send packets corresponding to GED-125. Cisco has a detailed 100+-page document detailing the internals of

With : PostgreSQL 8.4 or postgresql-8.3 rails 2.3.4 pg 9.x or pg 8.x I test this code: ========================= class NkiBatch < ActiveRecord::Base Bank.connection.transaction do bank = Bank.new(:name => "ddsjdsjdsjk") bank.save! raise ActiveRecord::Rollback.new end end and this: ========================= class NkiBatch < ActiveRecord::Base

Dear R experts, I'm hoping someone can help me to interpret the results of building gam's with mgcv in R. Below are summaries of two gam's based on the same dataset. The first gam (named "gam.mod") has six predictor variables. The second gam (named "gam.mod2") is exactly the same except it is missing one of the predictor variables. What is confusing me is

Hello, I've a problem with seeking using libFLAC++ API. The call to seek_absolute always returns with false, whatever I do. I tried many different ways, finally I tried to reduce my added code to near zero, so I used the cpp decode example in ...\flac-1.2.1\examples\cpp\decode\file\.main.cpp and added only one line: bool b=decoder.seek_absolute(1000); right before ok =

Hi, i need a little help! i must create a dummy variable to insert as external regressor in the variance equation of a garch model; this dummy is referred to the negative sign of returns of an asset, so it has to be 1 when returns are negative and 0 when they are positive, and in my model the dummy is multiplied by another time series, the daily range. (have i explained well?!) thank's a lot

Hello, fellow Rdicts, I have the code for the program below. I need to integrate a function of "x" and "p". I use integrate to integrate over "x" and pass "p" as an additional argument. "p" is specified and given default value in the argument list. Still, integrate() cannot read "p", unless I explicitly insert a numeric value in the