Re: [R] ARCH LM test for univariant time series
Dear Bernhard:
Thanks very much. Unless you object, I shall add it to the
'FinTS' library as ArchTest (comparable to the S-PLUS Finmetrics
'archTest' function) -- with a worked example in '\scripts\ch03.R'.
Best Wishes,
Spencer
Pfaff, Bernhard Dr. wrote:
Dear All,
one can visually inspect ARCH-effects by plotting acf/pacf of the
squared residuals from an OLS-estimation. This can be as simple as a
demeaned series. Further one can run an auxiliary regression by
regressing q lagged squared values and a constant on the squared series
itself. This test statistic (N-q)*R^2 is distributed as chisq with q
degrees of freedom.
Something along the lines:
archlmtest - function (x, lags, demean = FALSE)
{
x - as.vector(x)
if(demean) x - scale(x, center = TRUE, scale = FALSE)
lags - lags + 1
mat - embed(x^2, lags)
arch.lm - summary(lm(mat[, 1] ~ mat[, -1]))
STATISTIC - arch.lm$r.squared * length(resid(arch.lm))
names(STATISTIC) - Chi-squared
PARAMETER - lags - 1
names(PARAMETER) - df
PVAL - 1 - pchisq(STATISTIC, df = PARAMETER)
METHOD - ARCH LM-test
result - list(statistic = STATISTIC, parameter = PARAMETER,
p.value = PVAL, method = METHOD, data.name =
deparse(substitute(x)))
class(result) - htest
return(result)
}
should work and yield equal results as mentioned earlier in this thread.
Best,
Bernhard
Spencer,
The warning message is sent from VAR, it basically lets you
know that the
data it used had no column names and it had to supply them
using y1, y2, y3,
etc. It can be suppressed by including options(warn=-1) in the
function.
Anyway, it seems that the p value from my function does not match
FinMetrics'. I guess the function doesn't work... hmm...
On 2/2/08, Spencer Graves [EMAIL PROTECTED] wrote:
Dear Tom:
Your revised function eliminates the discrepancy in the
degrees of
freedom but is still very different from the numbers reports
on Tsay, p.
102:
archTest(log(1+as.numeric(m.intc7303)), lag=12)
ARCH test (univariate)
data: Residual of y1 equation
Chi-squared = 13.1483, df = 12, p-value = 0.3584
Warning message:
In VAR(s, p = 1, type = const) :
No column names supplied in y, using: y1, y2, y3, y4, y5, y6, y7, y8,
y9, y10, y11, y12 , instead.
TOM: What can you tell me about the warning message?
Thanks for your help with this.
Spencer Graves
tom soyer wrote:
Spencer,
Sorry, I forgot that the default lag in arch is 16. Here
is the fix. Can
you
try it again and see if it gives the correct (or at least similar
compared
to a true LM test) result?
archTest=function(x, lags=12){
#x is a vector
require(vars)
s=embed(x,lags)
y=VAR(s,p=1,type=const)
result=arch(y,lags.single=lags,multi=F)$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..
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)
Re: [R] ARCH LM test for univariant time series
Dear All,
one can visually inspect ARCH-effects by plotting acf/pacf of the
squared residuals from an OLS-estimation. This can be as simple as a
demeaned series. Further one can run an auxiliary regression by
regressing q lagged squared values and a constant on the squared series
itself. This test statistic (N-q)*R^2 is distributed as chisq with q
degrees of freedom.
Something along the lines:
archlmtest - function (x, lags, demean = FALSE)
{
x - as.vector(x)
if(demean) x - scale(x, center = TRUE, scale = FALSE)
lags - lags + 1
mat - embed(x^2, lags)
arch.lm - summary(lm(mat[, 1] ~ mat[, -1]))
STATISTIC - arch.lm$r.squared * length(resid(arch.lm))
names(STATISTIC) - Chi-squared
PARAMETER - lags - 1
names(PARAMETER) - df
PVAL - 1 - pchisq(STATISTIC, df = PARAMETER)
METHOD - ARCH LM-test
result - list(statistic = STATISTIC, parameter = PARAMETER,
p.value = PVAL, method = METHOD, data.name =
deparse(substitute(x)))
class(result) - htest
return(result)
}
should work and yield equal results as mentioned earlier in this thread.
Best,
Bernhard
Spencer,
The warning message is sent from VAR, it basically lets you
know that the
data it used had no column names and it had to supply them
using y1, y2, y3,
etc. It can be suppressed by including options(warn=-1) in the
function.
Anyway, it seems that the p value from my function does not match
FinMetrics'. I guess the function doesn't work... hmm...
On 2/2/08, Spencer Graves [EMAIL PROTECTED] wrote:
Dear Tom:
Your revised function eliminates the discrepancy in the
degrees of
freedom but is still very different from the numbers reports
on Tsay, p.
102:
archTest(log(1+as.numeric(m.intc7303)), lag=12)
ARCH test (univariate)
data: Residual of y1 equation
Chi-squared = 13.1483, df = 12, p-value = 0.3584
Warning message:
In VAR(s, p = 1, type = const) :
No column names supplied in y, using: y1, y2, y3, y4, y5, y6, y7, y8,
y9, y10, y11, y12 , instead.
TOM: What can you tell me about the warning message?
Thanks for your help with this.
Spencer Graves
tom soyer wrote:
Spencer,
Sorry, I forgot that the default lag in arch is 16. Here
is the fix. Can
you
try it again and see if it gives the correct (or at least similar
compared
to a true LM test) result?
archTest=function(x, lags=12){
#x is a vector
require(vars)
s=embed(x,lags)
y=VAR(s,p=1,type=const)
result=arch(y,lags.single=lags,multi=F)$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..
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)$arch.uni[[1]]
return(result)
}
can you, or maybe Bernhard, check and see whether this
function gives
the correct result?
thanks,
On 2/1/08, *Spencer Graves* [EMAIL PROTECTED]
mailto:[EMAIL PROTECTED] wrote:
Hi, Tom:
The 'arch' function in the 'vars' package is
supposed to be
able
to do that. Unfortunately, I was unable to make it
work for a
univariate series. Bernhard Pfaff, the author of
'vars', said
that if I
read the code for 'arch', I could easily retrieve
the necessary
lines
and put them
Re: [R] ARCH LM test for univariant time series
Thanks Bernhard for the beautiful code!!
On 2/4/08, Pfaff, Bernhard Dr. [EMAIL PROTECTED] wrote:
Dear All,
one can visually inspect ARCH-effects by plotting acf/pacf of the
squared residuals from an OLS-estimation. This can be as simple as a
demeaned series. Further one can run an auxiliary regression by
regressing q lagged squared values and a constant on the squared series
itself. This test statistic (N-q)*R^2 is distributed as chisq with q
degrees of freedom.
Something along the lines:
archlmtest - function (x, lags, demean = FALSE)
{
x - as.vector(x)
if(demean) x - scale(x, center = TRUE, scale = FALSE)
lags - lags + 1
mat - embed(x^2, lags)
arch.lm - summary(lm(mat[, 1] ~ mat[, -1]))
STATISTIC - arch.lm$r.squared * length(resid(arch.lm))
names(STATISTIC) - Chi-squared
PARAMETER - lags - 1
names(PARAMETER) - df
PVAL - 1 - pchisq(STATISTIC, df = PARAMETER)
METHOD - ARCH LM-test
result - list(statistic = STATISTIC, parameter = PARAMETER,
p.value = PVAL, method = METHOD, data.name =
deparse(substitute(x)))
class(result) - htest
return(result)
}
should work and yield equal results as mentioned earlier in this thread.
Best,
Bernhard
Spencer,
The warning message is sent from VAR, it basically lets you
know that the
data it used had no column names and it had to supply them
using y1, y2, y3,
etc. It can be suppressed by including options(warn=-1) in the
function.
Anyway, it seems that the p value from my function does not match
FinMetrics'. I guess the function doesn't work... hmm...
On 2/2/08, Spencer Graves [EMAIL PROTECTED] wrote:
Dear Tom:
Your revised function eliminates the discrepancy in the
degrees of
freedom but is still very different from the numbers reports
on Tsay, p.
102:
archTest(log(1+as.numeric(m.intc7303)), lag=12)
ARCH test (univariate)
data: Residual of y1 equation
Chi-squared = 13.1483, df = 12, p-value = 0.3584
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.
TOM: What can you tell me about the warning message?
Thanks for your help with this.
Spencer Graves
tom soyer wrote:
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)$arch.uni[[1]]
return(result)
}
Thanks and sorry about the bug.
On 2/2/08, Spencer Graves [EMAIL PROTECTED] wrote:
Dear Tom, Bernhard, Ruey:
I can't get that to match Tsay's example, but I have other
questions about that.
1. I got the following using Tom's 'archTest'
function (below):
archTest(log(1+as.numeric(m.intc7303)), lags=12)
ARCH test (univariate)
data: Residual of y1 equation
Chi-squared = 10.8562, df = 16, p-value = 0.8183
Warning message:
In VAR(s, p = 1, type = const) :
No column names supplied in y, using: y1, y2, y3, y4, y5,
y6, y7, y8,
y9, y10, y11, y12 , instead.
** First note that the answer has df = 16, even though I
supplied lags = 12.
2. For (apparently) this example, S-Plus FinMetrics
'archTest'
function returned Test for ARCH Effects: LM Test. Null
Hypothesis:
no ARCH effects. Test Stat 43.5041, p.value 0..
Dist. under Null:
chi-square with 12 degrees of freedom.
3. Starting on p. 101, Ruey mentioned the Lagrange
multiplier
test of Engle (1982), saying This test is equivalent to
the usual F
test for no regression, but refers it to a chi-square, not an F
distribution. Clearly, there is a gap here, because the
expected value
of the F distribution is close to 1 [d2/(d2-2), where d2
= denominator
degrees of freedom; http://en.wikipedia.org/wiki/F-distribution],
while
the expected value for a chi-square is the number of
degrees of freedom
Unfortunately, I don't feel I can afford the time to
dig into this
further right now.
Thanks for your help.
Spencer Graves
tom soyer wrote:
Spencer, how about something like this:
archTest=function (x, lags= 16){
#x is a vector
require(vars)
s=embed(x,lags)
y=VAR(s,p=1,type=const)
result=arch(y,multi=F)$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.
Re: [R] ARCH LM test for univariant time series
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.. 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)$arch.uni[[1]]
return(result)
}
can you, or maybe Bernhard, check and see whether this function gives
the correct result?
thanks,
On 2/1/08, *Spencer Graves* [EMAIL PROTECTED]
mailto:[EMAIL PROTECTED] wrote:
Hi, Tom:
The 'arch' function in the 'vars' package is supposed to be able
to do that. Unfortunately, I was unable to make it work for a
univariate series. Bernhard Pfaff, the author of 'vars', said
that if I
read the code for 'arch', I could easily retrieve the necessary lines
and put them in my own function; I have not so far found the time to
try that. If you do, or if you get a better answer than this,
would you
please let me know? I would like to have this capability for the
'FinTS' package, and I would happily write a help page if someone
would
contribute the function -- or use a function in another package. Tsay
(2005) Analysis of Financial Time Series, 2nd ed. (Wiley) includes an
example on p. 103 that could be used for a reference.
Hope this helps.
Spencer Graves
tom soyer wrote:
Hi,
Does anyone know if R has a Lagrange multiplier (LM) test for ARCH
effects for univariant time series?
Thanks!
--
Tom
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] ARCH LM test for univariant time series
Spencer,
Sorry, I forgot that the default lag in arch is 16. Here is the fix. Can you
try it again and see if it gives the correct (or at least similar compared
to a true LM test) result?
archTest=function(x, lags=12){
#x is a vector
require(vars)
s=embed(x,lags)
y=VAR(s,p=1,type=const)
result=arch(y,lags.single=lags,multi=F)$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.. 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
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] ARCH LM test for univariant time series
OK, it's no good. Here is the result:
data(m.intc7303)
archTest(log(1+as.numeric(m.intc7303)), lags=12)
ARCH test (univariate)
data: Residual of y1 equation
Chi-squared = 13.1483, df = 12, p-value = 0.3584
On 2/2/08, tom soyer [EMAIL PROTECTED] wrote:
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.. 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
--
Tom
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] ARCH LM test for univariant time series
Dear Tom:
Your revised function eliminates the discrepancy in the degrees of
freedom but is still very different from the numbers reports on Tsay, p.
102:
archTest(log(1+as.numeric(m.intc7303)), lag=12)
ARCH test (univariate)
data: Residual of y1 equation
Chi-squared = 13.1483, df = 12, p-value = 0.3584
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.
TOM: What can you tell me about the warning message?
Thanks for your help with this.
Spencer Graves
tom soyer wrote:
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.. 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
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] ARCH LM test for univariant time series
Spencer,
The warning message is sent from VAR, it basically lets you know that the
data it used had no column names and it had to supply them using y1, y2, y3,
etc. It can be suppressed by including options(warn=-1) in the function.
Anyway, it seems that the p value from my function does not match
FinMetrics'. I guess the function doesn't work... hmm...
On 2/2/08, Spencer Graves [EMAIL PROTECTED] wrote:
Dear Tom:
Your revised function eliminates the discrepancy in the degrees of
freedom but is still very different from the numbers reports on Tsay, p.
102:
archTest(log(1+as.numeric(m.intc7303)), lag=12)
ARCH test (univariate)
data: Residual of y1 equation
Chi-squared = 13.1483, df = 12, p-value = 0.3584
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.
TOM: What can you tell me about the warning message?
Thanks for your help with this.
Spencer Graves
tom soyer wrote:
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.. 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
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] ARCH LM test for univariant time series
tom soyer wrote:
Spencer,
The warning message is sent from VAR, it basically lets you know that the
data it used had no column names and it had to supply them using y1, y2, y3,
etc. It can be suppressed by including options(warn=-1) in the function.
Anyway, it seems that the p value from my function does not match
FinMetrics'. I guess the function doesn't work... hmm...
Before I concluded the function doesn't work, I'd want to get key
references like Engle (1982) Autoregressive Conditional
Heteroscedasticity with estimates of the variance of the United Kingdom
inflations, Econometrica 50: 987-1007, cited by Tsay (p. 101).
However, that's not on my critical path for today. SG
On 2/2/08, Spencer Graves [EMAIL PROTECTED] wrote:
Dear Tom:
Your revised function eliminates the discrepancy in the degrees of
freedom but is still very different from the numbers reports on Tsay, p.
102:
archTest(log(1+as.numeric(m.intc7303)), lag=12)
ARCH test (univariate)
data: Residual of y1 equation
Chi-squared = 13.1483, df = 12, p-value = 0.3584
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.
TOM: What can you tell me about the warning message?
Thanks for your help with this.
Spencer Graves
tom soyer wrote:
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.. 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
Re: [R] ARCH LM test for univariant time series
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! __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] ARCH LM test for univariant time series
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] 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
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
