[R-SIG-Finance] understanding an error from ugarchfit

[Ole Bueker]

I have also encountered the error "Error in diag(fit$robust.cvar) : nonvalid
'nrow' value (too large or NA)" in my data analysis.

Here is the link to several time series, which all experience either the
above error or the "failed to invest hessian" error, which seems to have a
similar error source (non-convergence).

https://www.dropbox.com/s/ns6okxeib42syxo/NOT_WORKING.csv


The reproducible code for this data is:

spreads <- read.zoo("NOT_WORKING.csv", header=TRUE, sep=",",
format="%d-%m-%y")
spreads <- na.locf(spreads)
returns1 <- diff(log(spreads), 1)
remove(spreads)
returns_crisis <- window(returns1, start="2007-07-23", end="2009-01-30")
returns_post <- window(returns1, start="2009-02-01", end="2014-05-12")

model<-ugarchspec(variance.model=list(model="sGARCH",garchOrder=c(1,1)),
mean.model=list(armaOrder=c(1,0),include.mean=FALSE),distribution.model="ged")

model_crisis <- lapply(returns_crisis, ugarchfit, spec=model,
solver="hybrid")
model_post <- lapply(returns_post, ugarchfit, spec=model, solver="hybrid")


I've tried playing around with adding constrains but was unable to find a
solution (even using the hybrid solver).


My original data contains about 100 additional time series (all covering the
same period, however with more/less NA's depending on the company).
However, these all converge without failure so I have not shared them (I can
upload them if necessary).




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