ugarchspec: external regressors

args(ugarchspec)

Hi All,

I am running rugarch Version: 1.3-5 and am trying to simulate the paper:
?High-low range in GARCH models of stock return volatility? SSRN:
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2753336, for my thesis.

I am able to run sGARCH with no problems. The paper though, calls to
?estimate a GARCH(0,1) model with an exogenous variable? This is where it
goes all pear shape. I have modelled the volatility using the TTR package:
?train.vGK <- volatility(train.ohlc, calc="garman")
train.vParkinson <- volatility(train.ohlc, calc="parkinson")?

The result is an xts object, as expected considering my input class is xts,
and the dimensions after some adjustments:

str(close.djdr)

An ?xts? object on 1993-01-15/2009-04-24 containing:
  Data: num [1:4100, 1] 0.000979 0.001161 -0.005788 -0.004309 0.003387 ...
 - attr(*, "dimnames")=List of 2
  ..$ : NULL
  ..$ : chr "daily.returns"
  Indexed by objects of class: [Date] TZ: UTC
  xts Attributes:
 NULL

str(train.vParkinson)

An ?xts? object on 1993-01-15/2009-04-24 containing:
  Data: num [1:4100, 1] 0.0866 0.0853 0.0875 0.088 0.0772 ...
 - attr(*, "dimnames")=List of 2
  ..$ : NULL
  ..$ : chr "vParkinson"
  Indexed by objects of class: [Date] TZ: UTC
  xts Attributes:
 NULL

When I try to run the ugarchspec, it fails miserably:

spec1X=ugarchspec(variance.model=list(model="sGARCH"),

+ external.regressors = train.vParkinson[,1],  #What is the correct form
here? I have lagged it: train.xreg = lag(train.vParkinson,1)
+ mean.model=list(armaOrder=c(0,0)))
Error in .local(variance.model, mean.model, distribution.model,
start.pars,  :
  unused argument (external.regressors = c(0.0866063373770964,
0.0853297963049413, 0.0875414180301314, 0.0880414499227675,
0.0771631965517572, 0.0707091044790502, 0.0778057119517414,
0.0775765066940466, 0.077820690394834, 0.0752388231276861,
0.072436404409338, 0.07452357235863, 0.0710133687112722,
0.0817565181849798, 0.0900172823007909, 0.0930080887667925,
0.0896830143657568, 0.089774572544706, 0.0904325308768051,
0.092930283058663, 0.0964456153316399, 0.123570155397932,
0.125244790062196, 0.138922401992731,
0.135292796408894, 0.134903364202769, 0.136922606737311, 0.138012028037638,
0.136775934192342, 0.136172719004911, 0.136364919382056, 0.122106445616322,
0.121111651605594, 0.0962623729322267, 0.0981395485851856,
0.117961280078613, 0.114364914549088, 0.112811619226829, 0.1139844134944,
0.120975655704514, 0.117871553416396, 0.106136285136668, 0.106057886734732,
0.113735726997588, 0.108700010793231, 0.085947506860437,
0.0853823006923295, 0.0834373451373239, 0.0829486747947965,

So, I lag my exon variable
train.xreg = lag(train.vParkinson,1)
train.test = as.matrix(train.xreg, ncol = 1)

Then set a matrix, but I don?t think this is required as I am using xts
class (see: https://stat.ethz.ch/pipermail/r-sig-finance/2014q3/012708.html)

I have tried to change the class of train.vParkinson to matrix, data.frame,
with the square brackets, without the square brackets, read several threads
on a similar problem. What am I doing wrong?

The data is extracted with quant mod:
#     1.1.1 Set start and end date for collection in YYYYMMDD (numeric)
format
train.date.start<-19930103 #Monday
train.date.end<-20090424 #Friday - changed the original date which was
20090427


#     1.1.2 Collect historical data for DJIA Index
train.djd <- getYahooData("^DJI", start=train.date.start,
end=train.date.end, freq="daily")
chartSeries(train.djd[,1:5])

close.djdr = dailyReturn(djd[,4], type="log") #daily returns close on close
close.djdr = close.djdr[-(1:9)]

Thanks in advance.
Kirro

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