Spencer,
Sorry, I forgot that the default lag in arch is 16. Here is the fix. Can you
try it again and see if it gives the correct (or at least similar compared
to a true LM test) result?
archTest=function(x, lags=12){
#x is a vector
require(vars)
s=embed(x,lags)
y=VAR(s,p=1,type="const")
result=arch(y,lags.single=lags,multi=F)$arch.uni[[1]]
return(result)
}
Thanks and sorry about the bug.
On 2/2/08, Spencer Graves <[EMAIL PROTECTED]> wrote:
>
> Dear Tom, Bernhard, Ruey:
>
> I can't get that to match Tsay's example, but I have other
> questions about that.
>
> 1. I got the following using Tom's 'archTest' function (below):
>
> > archTest(log(1+as.numeric(m.intc7303)), lags=12)
>
> ARCH test (univariate)
>
> data: Residual of y1 equation
> Chi-squared = 10.8562, df = 16, p-value = 0.8183
>
> Warning message:
> In VAR(s, p = 1, type = "const") :
> No column names supplied in y, using: y1, y2, y3, y4, y5, y6, y7, y8,
> y9, y10, y11, y12 , instead.
>
> >
> ** First note that the answer has df = 16, even though I
> supplied lags = 12.
>
> 2. For (apparently) this example, S-Plus FinMetrics 'archTest'
> function returned "Test for ARCH Effects: LM Test. Null Hypothesis:
> no ARCH effects. Test Stat 43.5041, p.value 0.0000. Dist. under Null:
> chi-square with 12 degrees of freedom".
>
> 3. Starting on p. 101, Ruey mentioned "the Lagrange multiplier
> test of Engle (1982)", saying "This test is equivalent to the usual F
> test for" no regression, but refers it to a chi-square, not an F
> distribution. Clearly, there is a gap here, because the expected value
> of the F distribution is close to 1 [d2/(d2-2), where d2 = denominator
> degrees of freedom; http://en.wikipedia.org/wiki/F-distribution], while
> the expected value for a chi-square is the number of degrees of freedom
>
> Unfortunately, I don't feel I can afford the time to dig into this
> further right now.
>
> Thanks for your help.
> Spencer Graves
>
> tom soyer wrote:
> > Spencer, how about something like this:
> >
> > archTest=function (x, lags= 16){
> > #x is a vector
> > require(vars)
> > s=embed(x,lags)
> > y=VAR(s,p=1,type="const")
> > result=arch(y,multi=F)$arch.uni[[1]]
> > return(result)
> > }
> >
> > can you, or maybe Bernhard, check and see whether this function gives
> > the correct result?
> >
> > thanks,
> >
> > On 2/1/08, *Spencer Graves* <[EMAIL PROTECTED]
> > <mailto:[EMAIL PROTECTED]>> wrote:
> >
> > Hi, Tom:
> >
> > The 'arch' function in the 'vars' package is supposed to be
> able
> > to do that. Unfortunately, I was unable to make it work for a
> > univariate series. Bernhard Pfaff, the author of 'vars', said
> > that if I
> > read the code for 'arch', I could easily retrieve the necessary
> lines
> > and put them in my own function; I have not so far found the time
> to
> > try that. If you do, or if you get a better answer than this,
> > would you
> > please let me know? I would like to have this capability for the
> > 'FinTS' package, and I would happily write a help page if someone
> > would
> > contribute the function -- or use a function in another
> package. Tsay
> > (2005) Analysis of Financial Time Series, 2nd ed. (Wiley) includes
> an
> > example on p. 103 that could be used for a reference.
> >
> > Hope this helps.
> > Spencer Graves
> >
> > tom soyer wrote:
> > > Hi,
> > >
> > > Does anyone know if R has a Lagrange multiplier (LM) test for ARCH
> > > effects for univariant time series?
> > >
> > > Thanks!
> > >
> > >
> >
> >
> >
> >
> > --
> > Tom
>
--
Tom
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