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Mui Boon Loong

2013-Apr-04 07:14 UTC

[R] Help for bootstrapping‏

I have a set of data for US t-bill returns and US stock returns frm 1980-2012. I
am trying to bootstrap the data and obtain the minimum variance portfolio and
repeat this portfolio 1000 times. However I am unable to get the correct code
function for the minimum variance portfolio. When I tried to enter
Opt(OriData+1, 1, 5, 0), I get "error:subscript out of bounds" Please
help!
library("quadprog")
##############################Preparing for datarawdata =
read.table("C:/Desktop/data.txt", header=T)Rf = rawdata[,1]US =
rawdata[,2]data = data.frame(Rf,US)OriData = as.matrix(data)
##############################the GetBSData
functionGetBSData<-function(data){x = 1:396s = sample(x,6,replace=T)bsdata =
data[(s[1]):(s[1]+59),]	for (j in 2:6) {  		a = data[(s[j]):(s[j]+59),]  	
bsdata = rbind(bsdata,a)	}return(bsdata)}
#set.seed(1234)#trial<-GetBSData(OriData)
##############################the Minimisation functionOpt<-function(data,
horizon, col,
lamda){TbillReturn<-numeric(30/horizon)USReturn<-numeric(30/horizon)for (x
in 1: (30/horizon)){
TbillReturn[x]<-prod(data[(12*horizon*(x-1)+1):(12*horizon*(x-1)+12*horizon),col])-1
USReturn[x]<-prod(data[(12*horizon*(x-1)+1):(12*horizon*(x-1)+12*horizon),2])-1}Return<-cbind(TbillReturn,USReturn)MeanVec<-c(mean(TbillReturn),mean(USReturn))VCovMat<-cov(Return)#return(MeanVec,
VCovMat)
a<-c(1,1)a<-cbind(a, diag(1,2))
WtVec<-solve.QP(Dmat=VCovMat*2, dvec=
MeanVec*lamda,Amat=a,bvec=c(1,0,0),meq=1)
#return(MeanVec, VCovMat, WtVec$solution)return(WtVec$solution)}
#Opt(OriData+1, 1, 5, 0)
##############################set.seed(4114)bs=1000						###number of bootstrap
samplesRegion<-5						###Region indecies, check
above.lamdaseq<-seq(0,1,.05)				###the lamda sequence. currently from 0 to 1
by .05.
x<-numeric(bs*length(lamdaseq))		###w1<-matrix(x, bs, length(lamdaseq))	
###To initialise the matrices.w5<-matrix(x, bs, length(lamdaseq))		###1, 5,
10 denote the horizon.w10<-matrix(x, bs, length(lamdaseq))	###
for (i in 1: bs){BSData<-GetBSData(OriData)+1j=1	for (lamda in lamdaseq){	
w1[i,j]<-Opt(BSData, 1, Region, lamda)[1]		w5[i,j]<-Opt(BSData, 5, Region,
lamda)[1]		w10[i,j]<-Opt(BSData, 10, Region, lamda)[1]		j=j+1	}
x<-numeric(length(lamdaseq)*9)		###To initialise the tabletable<-matrix(x,
length(lamdaseq), 9)	###
for (k in 1:length(lamdaseq)){		#k:index for lamda
table[k,1]<-sort(w1[,k])[.05*bs]		###The first 3 cols are for 1-yr
horizon.table[k,2]<-mean(w1[,k])			###From left to right: 5
percentile,table[k,3]<-sort(w1[,k])[.95*bs]		###mean, and 95 percentile.
table[k,4]<-sort(w5[,k])[.05*bs]		###table[k,5]<-mean(w5[,k])			###Col 4-6
are for 5-yr horizon.table[k,6]<-sort(w5[,k])[.95*bs]		###
table[k,7]<-sort(w10[,k])[.05*bs]		###table[k,8]<-mean(w10[,k])			###Col
7-9 are for 5-yr horizon.table[k,9]<-sort(w10[,k])[.95*bs]		###}}
table
TenMinusOne<-numeric(length(lamdaseq))FiveMinusOne<-numeric(length(lamdaseq))TenMinusFive<-numeric(length(lamdaseq))
for (p in
1:length(lamdaseq)){DiffVec<-w10[,p]-w1[,p]TenMinusOne[p]<-length(DiffVec[DiffVec>0])
DiffVec<-w5[,p]-w1[,p]FiveMinusOne[p]<-length(DiffVec[DiffVec>0])
DiffVec<-w10[,p]-w5[,p]TenMinusFive[p]<-length(DiffVec[DiffVec>0])}
diff<-cbind(FiveMinusOne,TenMinusOne)diff<-cbind(diff,
TenMinusFive)sn<-seq(1, length(lamdaseq))f2<-cbind(sn, diff)f2
##############################################END 		 	   		  
	[[alternative HTML version deleted]]

John Kane

2013-Apr-04 11:19 UTC

head link

[R] Help for bootstrapping‏

It looks like you formatted the code in html and it is essentially impossible to
read.  Can you resend in plain text?

Thanks

John Kane
Kingston ON Canada

> -----Original Message-----
> From: boon_loong at hotmail.com
> Sent: Thu, 4 Apr 2013 15:14:05 +0800
> To: r-help at r-project.org
> Subject: [R] Help for bootstrapping?
> 
> I have a set of data for US t-bill returns and US stock returns frm
> 1980-2012. I am trying to bootstrap the data and obtain the minimum
> variance portfolio and repeat this portfolio 1000 times. However I am
> unable to get the correct code function for the minimum variance
> portfolio. When I tried to enter Opt(OriData+1, 1, 5, 0), I get
> "error:subscript out of bounds" Please help!
> library("quadprog")
> ##############################Preparing for datarawdata >
read.table("C:/Desktop/data.txt", header=T)Rf = rawdata[,1]US >
rawdata[,2]data = data.frame(Rf,US)OriData = as.matrix(data)
> ##############################the GetBSData
> functionGetBSData<-function(data){x = 1:396s >
sample(x,6,replace=T)bsdata = data[(s[1]):(s[1]+59),]	for (j in 2:6) {
> a = data[(s[j]):(s[j]+59),]  		bsdata = rbind(bsdata,a)	}return(bsdata)}
> #set.seed(1234)#trial<-GetBSData(OriData)
> ##############################the Minimisation
> functionOpt<-function(data, horizon, col,
>
lamda){TbillReturn<-numeric(30/horizon)USReturn<-numeric(30/horizon)for
> (x in 1: (30/horizon)){TbillReturn[x]<-prod(data[(12*horizon*(x-1)+1):(12*horizon*(x-1)+12*horizon),col])-1
USReturn[x]<-prod(data[(12*horizon*(x-1)+1):(12*horizon*(x-1)+12*horizon),2])-1}Return<-cbind(TbillReturn,USReturn)MeanVec<-c(mean(TbillReturn),mean(USReturn))VCovMat<-cov(Return)#return(MeanVec,> VCovMat)
> a<-c(1,1)a<-cbind(a, diag(1,2))
> WtVec<-solve.QP(Dmat=VCovMat*2, dvec>
MeanVec*lamda,Amat=a,bvec=c(1,0,0),meq=1)
> #return(MeanVec, VCovMat, WtVec$solution)return(WtVec$solution)}
> #Opt(OriData+1, 1, 5, 0)
> ##############################set.seed(4114)bs=1000						###number of
> bootstrap samplesRegion<-5						###Region indecies, check
> above.lamdaseq<-seq(0,1,.05)				###the lamda sequence. currently from 0
> to 1 by .05.
> x<-numeric(bs*length(lamdaseq))		###w1<-matrix(x, bs,
length(lamdaseq))
> ###To initialise the matrices.w5<-matrix(x, bs, length(lamdaseq))		###1,
> 5, 10 denote the horizon.w10<-matrix(x, bs, length(lamdaseq))	###
> for (i in 1: bs){BSData<-GetBSData(OriData)+1j=1	for (lamda in
lamdaseq){
> w1[i,j]<-Opt(BSData, 1, Region, lamda)[1]		w5[i,j]<-Opt(BSData, 5,
> Region, lamda)[1]		w10[i,j]<-Opt(BSData, 10, Region, lamda)[1]		j=j+1	}
> x<-numeric(length(lamdaseq)*9)		###To initialise the
> tabletable<-matrix(x, length(lamdaseq), 9)	###
> for (k in 1:length(lamdaseq)){		#k:index for lamda
> table[k,1]<-sort(w1[,k])[.05*bs]		###The first 3 cols are for 1-yr
> horizon.table[k,2]<-mean(w1[,k])			###From left to right: 5
> percentile,table[k,3]<-sort(w1[,k])[.95*bs]		###mean, and 95 percentile.
> table[k,4]<-sort(w5[,k])[.05*bs]		###table[k,5]<-mean(w5[,k])		
###Col
> 4-6 are for 5-yr horizon.table[k,6]<-sort(w5[,k])[.95*bs]		###
> table[k,7]<-sort(w10[,k])[.05*bs]		###table[k,8]<-mean(w10[,k])		
###Col
> 7-9 are for 5-yr horizon.table[k,9]<-sort(w10[,k])[.95*bs]		###}}
> table
>
TenMinusOne<-numeric(length(lamdaseq))FiveMinusOne<-numeric(length(lamdaseq))TenMinusFive<-numeric(length(lamdaseq))
> for (p in
>
1:length(lamdaseq)){DiffVec<-w10[,p]-w1[,p]TenMinusOne[p]<-length(DiffVec[DiffVec>0])
> DiffVec<-w5[,p]-w1[,p]FiveMinusOne[p]<-length(DiffVec[DiffVec>0])
>
DiffVec<-w10[,p]-w5[,p]TenMinusFive[p]<-length(DiffVec[DiffVec>0])}
> diff<-cbind(FiveMinusOne,TenMinusOne)diff<-cbind(diff,
> TenMinusFive)sn<-seq(1, length(lamdaseq))f2<-cbind(sn, diff)f2
> ##############################################END
> 	[[alternative HTML version deleted]]
> 
> ______________________________________________
> R-help at 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.
____________________________________________________________
FREE 3D EARTH SCREENSAVER - Watch the Earth right on your desktop!

Mui Boon Loong

2013-Apr-04 11:56 UTC

head link

[R] Help for bootstrapping‏

As attached is the txt file for the code. 
Regards,BL
> Date: Thu, 4 Apr 2013 03:19:47 -0800
> From: jrkrideau at inbox.com
> Subject: RE: [R] Help for bootstrapping?
> To: boon_loong at hotmail.com; r-help at r-project.org
> 
> It looks like you formatted the code in html and it is essentially
impossible to read.  Can you resend in plain text?
> 
> Thanks
> 
> John Kane
> Kingston ON Canada
> 
> 
> > -----Original Message-----
> > From: boon_loong at hotmail.com
> > Sent: Thu, 4 Apr 2013 15:14:05 +0800
> > To: r-help at r-project.org
> > Subject: [R] Help for bootstrapping?
> > 
> > I have a set of data for US t-bill returns and US stock returns frm
> > 1980-2012. I am trying to bootstrap the data and obtain the minimum
> > variance portfolio and repeat this portfolio 1000 times. However I am
> > unable to get the correct code function for the minimum variance
> > portfolio. When I tried to enter Opt(OriData+1, 1, 5, 0), I get
> > "error:subscript out of bounds" Please help!
> > library("quadprog")
> > ##############################Preparing for datarawdata > >
read.table("C:/Desktop/data.txt", header=T)Rf = rawdata[,1]US >
> rawdata[,2]data = data.frame(Rf,US)OriData = as.matrix(data)
> > ##############################the GetBSData
> > functionGetBSData<-function(data){x = 1:396s > >
sample(x,6,replace=T)bsdata = data[(s[1]):(s[1]+59),]	for (j in 2:6) {
> > a = data[(s[j]):(s[j]+59),]  		bsdata = rbind(bsdata,a)
}return(bsdata)}
> > #set.seed(1234)#trial<-GetBSData(OriData)
> > ##############################the Minimisation
> > functionOpt<-function(data, horizon, col,
> >
lamda){TbillReturn<-numeric(30/horizon)USReturn<-numeric(30/horizon)for
> > (x in 1: (30/horizon)){
>
TbillReturn[x]<-prod(data[(12*horizon*(x-1)+1):(12*horizon*(x-1)+12*horizon),col])-1
>
USReturn[x]<-prod(data[(12*horizon*(x-1)+1):(12*horizon*(x-1)+12*horizon),2])-1}Return<-cbind(TbillReturn,USReturn)MeanVec<-c(mean(TbillReturn),mean(USReturn))VCovMat<-cov(Return)#return(MeanVec,
> > VCovMat)
> > a<-c(1,1)a<-cbind(a, diag(1,2))
> > WtVec<-solve.QP(Dmat=VCovMat*2, dvec> >
MeanVec*lamda,Amat=a,bvec=c(1,0,0),meq=1)
> > #return(MeanVec, VCovMat, WtVec$solution)return(WtVec$solution)}
> > #Opt(OriData+1, 1, 5, 0)
> > ##############################set.seed(4114)bs=1000						###number of
> > bootstrap samplesRegion<-5						###Region indecies, check
> > above.lamdaseq<-seq(0,1,.05)				###the lamda sequence. currently
from 0
> > to 1 by .05.
> > x<-numeric(bs*length(lamdaseq))		###w1<-matrix(x, bs,
length(lamdaseq))
> > ###To initialise the matrices.w5<-matrix(x, bs, length(lamdaseq))	
###1,
> > 5, 10 denote the horizon.w10<-matrix(x, bs, length(lamdaseq))	###
> > for (i in 1: bs){BSData<-GetBSData(OriData)+1j=1	for (lamda in
lamdaseq){
> > w1[i,j]<-Opt(BSData, 1, Region, lamda)[1]		w5[i,j]<-Opt(BSData,
5,
> > Region, lamda)[1]		w10[i,j]<-Opt(BSData, 10, Region, lamda)[1]	
j=j+1	}
> > x<-numeric(length(lamdaseq)*9)		###To initialise the
> > tabletable<-matrix(x, length(lamdaseq), 9)	###
> > for (k in 1:length(lamdaseq)){		#k:index for lamda
> > table[k,1]<-sort(w1[,k])[.05*bs]		###The first 3 cols are for 1-yr
> > horizon.table[k,2]<-mean(w1[,k])			###From left to right: 5
> > percentile,table[k,3]<-sort(w1[,k])[.95*bs]		###mean, and 95
percentile.
> > table[k,4]<-sort(w5[,k])[.05*bs]		###table[k,5]<-mean(w5[,k])		
###Col
> > 4-6 are for 5-yr horizon.table[k,6]<-sort(w5[,k])[.95*bs]		###
> > table[k,7]<-sort(w10[,k])[.05*bs]		###table[k,8]<-mean(w10[,k])	
###Col
> > 7-9 are for 5-yr horizon.table[k,9]<-sort(w10[,k])[.95*bs]		###}}
> > table
> >
TenMinusOne<-numeric(length(lamdaseq))FiveMinusOne<-numeric(length(lamdaseq))TenMinusFive<-numeric(length(lamdaseq))
> > for (p in
> >
1:length(lamdaseq)){DiffVec<-w10[,p]-w1[,p]TenMinusOne[p]<-length(DiffVec[DiffVec>0])
> >
DiffVec<-w5[,p]-w1[,p]FiveMinusOne[p]<-length(DiffVec[DiffVec>0])
> >
DiffVec<-w10[,p]-w5[,p]TenMinusFive[p]<-length(DiffVec[DiffVec>0])}
> > diff<-cbind(FiveMinusOne,TenMinusOne)diff<-cbind(diff,
> > TenMinusFive)sn<-seq(1, length(lamdaseq))f2<-cbind(sn, diff)f2
> > ##############################################END
> > 	[[alternative HTML version deleted]]
> > 
> > ______________________________________________
> > R-help at 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.
> 
> ____________________________________________________________
> FREE 3D EARTH SCREENSAVER - Watch the Earth right on your desktop!
> Check it out at http://www.inbox.com/earth
> 
>  		 	   		  
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- Boon Loong

2013-Apr-21 16:54 UTC

head link

[R] Pls help to prevent my post from being indexed on google

Hi is it possible to add this line to my earlier post <meta
name="robots" content="noindex"> to prevent it from being
indexed by google? the post is at
https://stat.ethz.ch/pipermail/r-help//2013-April/350857.html
From: boon_loong@hotmail.com
To: r-help@r-project.org
Subject: Help for bootstrappingþ
Date: Thu, 4 Apr 2013 15:14:05 +0800




I have a set of data for US t-bill returns and US stock returns frm 1980-2012. I
am trying to bootstrap the data and obtain the minimum variance portfolio and
repeat this portfolio 1000 times. However I am unable to get the correct code
function for the minimum variance portfolio. When I tried to enter
Opt(OriData+1, 1, 5, 0), I get "error:subscript out of bounds" Please
help!
library("quadprog")
##############################Preparing for datarawdata =
read.table("C:/Desktop/data.txt", header=T)Rf = rawdata[,1]US =
rawdata[,2]data = data.frame(Rf,US)OriData = as.matrix(data)
##############################the GetBSData
functionGetBSData<-function(data){x = 1:396s = sample(x,6,replace=T)bsdata =
data[(s[1]):(s[1]+59),]	for (j in 2:6) {  		a = data[(s[j]):(s[j]+59),]  	
bsdata = rbind(bsdata,a)	}return(bsdata)}
#set.seed(1234)#trial<-GetBSData(OriData)
##############################the Minimisation functionOpt<-function(data,
horizon, col,
lamda){TbillReturn<-numeric(30/horizon)USReturn<-numeric(30/horizon)for (x
in 1: (30/horizon)){
TbillReturn[x]<-prod(data[(12*horizon*(x-1)+1):(12*horizon*(x-1)+12*horizon),col])-1
USReturn[x]<-prod(data[(12*horizon*(x-1)+1):(12*horizon*(x-1)+12*horizon),2])-1}Return<-cbind(TbillReturn,USReturn)MeanVec<-c(mean(TbillReturn),mean(USReturn))VCovMat<-cov(Return)#return(MeanVec,
VCovMat)
a<-c(1,1)a<-cbind(a, diag(1,2))
WtVec<-solve.QP(Dmat=VCovMat*2, dvec=
MeanVec*lamda,Amat=a,bvec=c(1,0,0),meq=1)
#return(MeanVec, VCovMat, WtVec$solution)return(WtVec$solution)}
#Opt(OriData+1, 1, 5, 0)
##############################set.seed(4114)bs=1000						###number of bootstrap
samplesRegion<-5						###Region indecies, check
above.lamdaseq<-seq(0,1,.05)				###the lamda sequence. currently from 0 to 1
by .05.
x<-numeric(bs*length(lamdaseq))		###w1<-matrix(x, bs, length(lamdaseq))	
###To initialise the matrices.w5<-matrix(x, bs, length(lamdaseq))		###1, 5,
10 denote the horizon.w10<-matrix(x, bs, length(lamdaseq))	###
for (i in 1: bs){BSData<-GetBSData(OriData)+1j=1	for (lamda in lamdaseq){	
w1[i,j]<-Opt(BSData, 1, Region, lamda)[1]		w5[i,j]<-Opt(BSData, 5, Region,
lamda)[1]		w10[i,j]<-Opt(BSData, 10, Region, lamda)[1]		j=j+1	}
x<-numeric(length(lamdaseq)*9)		###To initialise the tabletable<-matrix(x,
length(lamdaseq), 9)	###
for (k in 1:length(lamdaseq)){		#k:index for lamda
table[k,1]<-sort(w1[,k])[.05*bs]		###The first 3 cols are for 1-yr
horizon.table[k,2]<-mean(w1[,k])			###From left to right: 5
percentile,table[k,3]<-sort(w1[,k])[.95*bs]		###mean, and 95 percentile.
table[k,4]<-sort(w5[,k])[.05*bs]		###table[k,5]<-mean(w5[,k])			###Col 4-6
are for 5-yr horizon.table[k,6]<-sort(w5[,k])[.95*bs]		###
table[k,7]<-sort(w10[,k])[.05*bs]		###table[k,8]<-mean(w10[,k])			###Col
7-9 are for 5-yr horizon.table[k,9]<-sort(w10[,k])[.95*bs]		###}}
table
TenMinusOne<-numeric(length(lamdaseq))FiveMinusOne<-numeric(length(lamdaseq))TenMinusFive<-numeric(length(lamdaseq))
for (p in
1:length(lamdaseq)){DiffVec<-w10[,p]-w1[,p]TenMinusOne[p]<-length(DiffVec[DiffVec>0])
DiffVec<-w5[,p]-w1[,p]FiveMinusOne[p]<-length(DiffVec[DiffVec>0])
DiffVec<-w10[,p]-w5[,p]TenMinusFive[p]<-length(DiffVec[DiffVec>0])}
diff<-cbind(FiveMinusOne,TenMinusOne)diff<-cbind(diff,
TenMinusFive)sn<-seq(1, length(lamdaseq))f2<-cbind(sn, diff)f2
##############################################END 		 	   		   		 	   		  
	[[alternative HTML version deleted]]

Joshua Wiley

2013-Apr-21 19:32 UTC

head link

[R] Pls help to prevent my post from being indexed on google

Hi,

No that is not really possible for several reasons.  One is that these
posts are not archived on just one web server.  There are multiple
archives managed by different people/places.  Another is that they are
actually scrubbed to plain text, so my guess is that bots would miss
that tag anyway once it is in plain text (but I could be wrong).
Finally, most people when they reply quote previous messages (in fact
this is considered quite courteous so there is a record).  All these
things lead to the fact that when you post on a high volume public
list serv, your posts tend to be, well, public.

Best of luck to you,

Joshua

On Sun, Apr 21, 2013 at 9:54 AM, - Boon Loong <boon_loong at hotmail.com>
wrote:> Hi is it possible to add this line to my earlier post <meta
name="robots" content="noindex"> to prevent it from being
indexed by google? the post is at
https://stat.ethz.ch/pipermail/r-help//2013-April/350857.html
> From: boon_loong at hotmail.com
> To: r-help at r-project.org
> Subject: Help for bootstrapping?
> Date: Thu, 4 Apr 2013 15:14:05 +0800
>
>
>
>
> I have a set of data for US t-bill returns and US stock returns frm
1980-2012. I am trying to bootstrap the data and obtain the minimum variance
portfolio and repeat this portfolio 1000 times. However I am unable to get the
correct code function for the minimum variance portfolio. When I tried to enter
Opt(OriData+1, 1, 5, 0), I get "error:subscript out of bounds" Please
help!
> library("quadprog")
> ##############################Preparing for datarawdata =
read.table("C:/Desktop/data.txt", header=T)Rf = rawdata[,1]US =
rawdata[,2]data = data.frame(Rf,US)OriData = as.matrix(data)
> ##############################the GetBSData
functionGetBSData<-function(data){x = 1:396s = sample(x,6,replace=T)bsdata =
data[(s[1]):(s[1]+59),]        for (j in 2:6) {                a =
data[(s[j]):(s[j]+59),]             bsdata = rbind(bsdata,a)       
}return(bsdata)}
> #set.seed(1234)#trial<-GetBSData(OriData)
> ##############################the Minimisation
functionOpt<-function(data, horizon, col,
lamda){TbillReturn<-numeric(30/horizon)USReturn<-numeric(30/horizon)for (x
in 1: (30/horizon)){       
TbillReturn[x]<-prod(data[(12*horizon*(x-1)+1):(12*horizon*(x-1)+12*horizon),col])-1
USReturn[x]<-prod(data[(12*horizon*(x-1)+1):(12*horizon*(x-1)+12*horizon),2])-1}Return<-cbind(TbillReturn,USReturn)MeanVec<-c(mean(TbillReturn),mean(USReturn))VCovMat<-cov(Return)#return(MeanVec,
VCovMat)
> a<-c(1,1)a<-cbind(a, diag(1,2))
> WtVec<-solve.QP(Dmat=VCovMat*2, dvec=
MeanVec*lamda,Amat=a,bvec=c(1,0,0),meq=1)
> #return(MeanVec, VCovMat, WtVec$solution)return(WtVec$solution)}
> #Opt(OriData+1, 1, 5, 0)
> ##############################set.seed(4114)bs=1000                        
###number of bootstrap samplesRegion<-5                                      
###Region indecies, check above.lamdaseq<-seq(0,1,.05)                       
###the lamda sequence. currently from 0 to 1 by .05.
> x<-numeric(bs*length(lamdaseq))         ###w1<-matrix(x, bs,
length(lamdaseq))          ###To initialise the matrices.w5<-matrix(x, bs,
length(lamdaseq))               ###1, 5, 10 denote the horizon.w10<-matrix(x,
bs, length(lamdaseq))     ###
> for (i in 1: bs){BSData<-GetBSData(OriData)+1j=1        for (lamda in
lamdaseq){                w1[i,j]<-Opt(BSData, 1, Region, lamda)[1]          
w5[i,j]<-Opt(BSData, 5, Region, lamda)[1]              
w10[i,j]<-Opt(BSData, 10, Region, lamda)[1]             j=j+1   }
> x<-numeric(length(lamdaseq)*9)          ###To initialise the
tabletable<-matrix(x, length(lamdaseq), 9) ###
> for (k in 1:length(lamdaseq)){          #k:index for lamda
> table[k,1]<-sort(w1[,k])[.05*bs]                ###The first 3 cols are
for 1-yr horizon.table[k,2]<-mean(w1[,k])                       ###From left
to right: 5 percentile,table[k,3]<-sort(w1[,k])[.95*bs]            ###mean,
and 95 percentile.
> table[k,4]<-sort(w5[,k])[.05*bs]               
###table[k,5]<-mean(w5[,k])                     ###Col 4-6 are for 5-yr
horizon.table[k,6]<-sort(w5[,k])[.95*bs]                ###
> table[k,7]<-sort(w10[,k])[.05*bs]              
###table[k,8]<-mean(w10[,k])                    ###Col 7-9 are for 5-yr
horizon.table[k,9]<-sort(w10[,k])[.95*bs]               ###}}
> table
>
TenMinusOne<-numeric(length(lamdaseq))FiveMinusOne<-numeric(length(lamdaseq))TenMinusFive<-numeric(length(lamdaseq))
> for (p in
1:length(lamdaseq)){DiffVec<-w10[,p]-w1[,p]TenMinusOne[p]<-length(DiffVec[DiffVec>0])
> DiffVec<-w5[,p]-w1[,p]FiveMinusOne[p]<-length(DiffVec[DiffVec>0])
>
DiffVec<-w10[,p]-w5[,p]TenMinusFive[p]<-length(DiffVec[DiffVec>0])}
> diff<-cbind(FiveMinusOne,TenMinusOne)diff<-cbind(diff,
TenMinusFive)sn<-seq(1, length(lamdaseq))f2<-cbind(sn, diff)f2
> ##############################################END
>         [[alternative HTML version deleted]]
>
>
> ______________________________________________
> R-help at 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.
>


--
Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles
http://joshuawiley.com/
Senior Analyst - Elkhart Group Ltd.
http://elkhartgroup.com

Rolf Turner

2013-Apr-21 21:22 UTC

head link

[R] Pls help to prevent my post from being indexed on google

See also:

     fortune("celebrity")

     cheers,

         Rolf Turner

On 22/04/13 07:32, Joshua Wiley wrote:> Hi,
>
> No that is not really possible for several reasons.  One is that these
> posts are not archived on just one web server.  There are multiple
> archives managed by different people/places.  Another is that they are
> actually scrubbed to plain text, so my guess is that bots would miss
> that tag anyway once it is in plain text (but I could be wrong).
> Finally, most people when they reply quote previous messages (in fact
> this is considered quite courteous so there is a record).  All these
> things lead to the fact that when you post on a high volume public
> list serv, your posts tend to be, well, public.
>
> Best of luck to you,
>
> Joshua
>
> On Sun, Apr 21, 2013 at 9:54 AM, - Boon Loong <boon_loong at
hotmail.com> wrote:
>> Hi is it possible to add this line to my earlier post <meta
name="robots" content="noindex"> to prevent it from being
indexed by google? the post is at
https://stat.ethz.ch/pipermail/r-help//2013-April/350857.html
>> From: boon_loong at hotmail.com
>> To: r-help at r-project.org
>> Subject: Help for bootstrapping?
>> Date: Thu, 4 Apr 2013 15:14:05 +0800
>>
>>
>>
>>
>> I have a set of data for US t-bill returns and US stock returns frm
1980-2012. I am trying to bootstrap the data and obtain the minimum variance
portfolio and repeat this portfolio 1000 times. However I am unable to get the
correct code function for the minimum variance portfolio. When I tried to enter
Opt(OriData+1, 1, 5, 0), I get "error:subscript out of bounds" Please
help!
>> library("quadprog")
>> ##############################Preparing for datarawdata =
read.table("C:/Desktop/data.txt", header=T)Rf = rawdata[,1]US =
rawdata[,2]data = data.frame(Rf,US)OriData = as.matrix(data)
>> ##############################the GetBSData
functionGetBSData<-function(data){x = 1:396s = sample(x,6,replace=T)bsdata =
data[(s[1]):(s[1]+59),]        for (j in 2:6) {                a =
data[(s[j]):(s[j]+59),]             bsdata = rbind(bsdata,a)       
}return(bsdata)}
>> #set.seed(1234)#trial<-GetBSData(OriData)
>> ##############################the Minimisation
functionOpt<-function(data, horizon, col,
lamda){TbillReturn<-numeric(30/horizon)USReturn<-numeric(30/horizon)for (x
in 1: (30/horizon)){       
TbillReturn[x]<-prod(data[(12*horizon*(x-1)+1):(12*horizon*(x-1)+12*horizon),col])-1
USReturn[x]<-prod(data[(12*horizon*(x-1)+1):(12*horizon*(x-1)+12*horizon),2])-1}Return<-cbind(TbillReturn,USReturn)MeanVec<-c(mean(TbillReturn),mean(USReturn))VCovMat<-cov(Return)#return(MeanVec,
VCovMat)
>> a<-c(1,1)a<-cbind(a, diag(1,2))
>> WtVec<-solve.QP(Dmat=VCovMat*2, dvec=
MeanVec*lamda,Amat=a,bvec=c(1,0,0),meq=1)
>> #return(MeanVec, VCovMat, WtVec$solution)return(WtVec$solution)}
>> #Opt(OriData+1, 1, 5, 0)
>> ##############################set.seed(4114)bs=1000                    
###number of bootstrap samplesRegion<-5                                      
###Region indecies, check above.lamdaseq<-seq(0,1,.05)                       
###the lamda sequence. currently from 0 to 1 by .05.
>> x<-numeric(bs*length(lamdaseq))         ###w1<-matrix(x, bs,
length(lamdaseq))          ###To initialise the matrices.w5<-matrix(x, bs,
length(lamdaseq))               ###1, 5, 10 denote the horizon.w10<-matrix(x,
bs, length(lamdaseq))     ###
>> for (i in 1: bs){BSData<-GetBSData(OriData)+1j=1        for (lamda
in lamdaseq){                w1[i,j]<-Opt(BSData, 1, Region, lamda)[1]       
w5[i,j]<-Opt(BSData, 5, Region, lamda)[1]              
w10[i,j]<-Opt(BSData, 10, Region, lamda)[1]             j=j+1   }
>> x<-numeric(length(lamdaseq)*9)          ###To initialise the
tabletable<-matrix(x, length(lamdaseq), 9) ###
>> for (k in 1:length(lamdaseq)){          #k:index for lamda
>> table[k,1]<-sort(w1[,k])[.05*bs]                ###The first 3 cols
are for 1-yr horizon.table[k,2]<-mean(w1[,k])                       ###From
left to right: 5 percentile,table[k,3]<-sort(w1[,k])[.95*bs]           
###mean, and 95 percentile.
>> table[k,4]<-sort(w5[,k])[.05*bs]               
###table[k,5]<-mean(w5[,k])                     ###Col 4-6 are for 5-yr
horizon.table[k,6]<-sort(w5[,k])[.95*bs]                ###
>> table[k,7]<-sort(w10[,k])[.05*bs]              
###table[k,8]<-mean(w10[,k])                    ###Col 7-9 are for 5-yr
horizon.table[k,9]<-sort(w10[,k])[.95*bs]               ###}}
>> table
>>
TenMinusOne<-numeric(length(lamdaseq))FiveMinusOne<-numeric(length(lamdaseq))TenMinusFive<-numeric(length(lamdaseq))
>> for (p in
1:length(lamdaseq)){DiffVec<-w10[,p]-w1[,p]TenMinusOne[p]<-length(DiffVec[DiffVec>0])
>>
DiffVec<-w5[,p]-w1[,p]FiveMinusOne[p]<-length(DiffVec[DiffVec>0])
>>
DiffVec<-w10[,p]-w5[,p]TenMinusFive[p]<-length(DiffVec[DiffVec>0])}
>> diff<-cbind(FiveMinusOne,TenMinusOne)diff<-cbind(diff,
TenMinusFive)sn<-seq(1, length(lamdaseq))f2<-cbind(sn, diff)f2
>> ##############################################END
>>          [[alternative HTML version deleted]]
>>
>>
>> ______________________________________________
>> R-help at 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.
>>
>
>
> --
> Joshua Wiley
> Ph.D. Student, Health Psychology
> University of California, Los Angeles
> http://joshuawiley.com/
> Senior Analyst - Elkhart Group Ltd.
> http://elkhartgroup.com
>
> ______________________________________________
> R-help at 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.

R help - Apr 2013 - Help for bootstrapping‏

[R] Help for bootstrapping‏

[R] Help for bootstrapping‏

[R] Help for bootstrapping‏

[R] Pls help to prevent my post from being indexed on google

[R] Pls help to prevent my post from being indexed on google

[R] Pls help to prevent my post from being indexed on google