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List: r-sig-finance
Subject: Re: [R-SIG-Finance] Fwd: runMult instead of runSum
From: G See <gsee000 () gmail ! com>
Date: 2011-10-31 15:01:58
Message-ID: CA+xi=qZacWqt5Z3KePfV7hHZStpwnssbpyi6xDGuieOQeGXu+g () mail ! gmail ! com
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Martin,
I'm sorry, I do not understand what you want.
e.g. `ret1[NROW(ret1), 4]` is no different than `last(ret1[,4])`
So, just to take a shot in the dark, something like this will sort the last
row of returns from lowest to highest
last(ret1)[ , order(last(ret1))]
Please try again to explain what you want. What do you mean by "order the
matrix?" (it's already ordered by date ;-)
What do you expect to get for output? How many rows? How many columns?
Also, if your question has more to do with beginner R help than finance,
maybe a better place to ask follow up questions is on the r-help list.
Best,
Garrett
On Sun, Oct 30, 2011 at 4:25 PM, Martin Bauer <Bauermartin@gmx.at> wrote:
> Hi,
>
> How can I order this matrix ?
>
> I have tried this
>
> ret1=(ROC(mP, n=6, type='discrete')
>
> tail(order(ret1[NROW(ret1)]))
>
> ret1[NROW(ret1),4]
> ret1[NROW(ret1),1]
> ret1[NROW(ret1),3]
> ret1[NROW(ret1),2]
>
> but I only get the ordered the first part (AA,AXP,BA,BAC) of the matrix
> instead the hole matrix
>
> any idea why ?
>
> Have a great weekend
>
> Martin
>
> >
> > R> P <- PF(syms, prefer='Adjusted', silent=TRUE)
> > R> mP <- to.monthly(P, OHLC=FALSE)
> > R> # 6 month simple return of each Dow component
> > R> tail(ROC(mP, n=6, type='discrete'))
> > AA AXP BA BAC
> > May 2011 0.28407351 0.2035731077 0.23722861 0.0751604
> > Jun 2011 0.03464052 0.2186982249 0.14537514 -0.1766917
> > Jul 2011 -0.10800971 0.1623512946 0.02564103 -0.2914536
> > Aug 2011 -0.23718713 0.1495587552 -0.06029515 -0.4266667
> > Sep 2011 -0.45594088 0.0008954556 -0.17166324 -0.5398496
> > Oct 2011 -0.31659776 0.0698151951 -0.13522771 -0.4000000
> > CAT CSCO CVX DD
> > May 2011 0.2616811 -0.12031662 0.31547017 0.15129714
> > Jun 2011 0.1467261 -0.22550000 0.14423508 0.10002054
> > Jul 2011 0.0269677 -0.23912004 0.11244071 0.02991712
> > Aug 2011 -0.1084622 -0.14931880 -0.03230860 -0.10561423
> > Sep 2011 -0.3312995 -0.09283196 -0.12502363 -0.26077307
> > Oct 2011 -0.1525943 0.06789413 0.01763505 -0.11636233
> > DIS GE HD HPQ
> > May 2011 0.152866242 0.25913838 0.20906631 -0.1050471
> > Jun 2011 0.040789123 0.04708520 0.04779948 -0.1306122
> > Jul 2011 -0.006431695 -0.09720102 -0.03640912 -0.2262774
> > Aug 2011 -0.221307727 -0.21362530 -0.08971912 -0.4002780
> > Sep 2011 -0.300069622 -0.22741117 -0.09969871 -0.4471805
> > Oct 2011 -0.159860789 -0.14136386 -0.01311475 -0.3018491
> > IBM INTC JNJ JPM
> > May 2011 0.20426720 0.08098933 0.11277945 0.16361650
> > Jun 2011 0.17881297 0.07125427 0.09463722 -0.02866089
> > Jul 2011 0.13197874 0.05738881 0.10324686 -0.08946412
> > Aug 2011 0.07135735 -0.04597156 0.08994534 -0.18622951
> > Sep 2011 0.08184855 0.07614725 0.09395397 -0.33894178
> > Oct 2011 0.10864679 0.09802198 0.01579436 -0.18394128
> > KFT KO MCD MMM
> > May 2011 0.17773973 0.06532988 0.05772496 0.137328642
> > Jun 2011 0.13811075 0.03789408 0.11562542 0.112147326
> > Jul 2011 0.14472801 0.09783845 0.19239311 0.003012746
> > Aug 2011 0.11960026 0.11808885 0.21160547 -0.088932806
> > Sep 2011 0.08884565 0.03271171 0.17062117 -0.222462905
> > Oct 2011 0.07175295 0.03622971 0.20826318 -0.156162100
> > MRK MSFT PFE
> > May 2011 0.0901365706 0.0024203308 0.342405063
> > Jun 2011 0.0014359563 -0.0565899963 0.200353565
> > Jul 2011 0.0521060842 0.0003673769 0.078142695
> > Aug 2011 0.0394026057 0.0137195122 0.006896552
> > Sep 2011 0.0133250697 -0.0071798963 -0.111111111
> > Oct 2011 -0.0008537279 0.0543180930 -0.035053554
> > PG T TRV UTX
> > May 2011 0.114454776 0.16844512 0.16457143 0.17840249
> > Jun 2011 0.003691221 0.09985580 0.06161746 0.13621091
> > Jul 2011 -0.009902597 0.09332322 -0.00744507 0.02965465
> > Aug 2011 0.026820546 0.03200883 -0.14726436 -0.10032715
> > Sep 2011 0.042588588 -0.04195089 -0.16814612 -0.15867512
> > Oct 2011 0.013782302 -0.01620906 -0.04572437 -0.10158192
> > VZ WMT XOM
> > May 2011 0.183733948 0.040425128 0.2131675201
> > Jun 2011 0.067766647 -0.001135933 0.1252609603
> > Jul 2011 0.016647196 -0.047159505 -0.0001261352
> > Aug 2011 0.005071851 0.044784915 -0.1239199905
> > Sep 2011 -0.020248380 0.010907674 -0.1260979425
> > Oct 2011 0.023110386 0.053844735 -0.0624784260
> >
> >
> >
> >
> > On Sat, Oct 29, 2011 at 3:42 PM, Martin Bauer <Bauermartin@gmx.at>
> wrote:
> >
> > > -------- Original-Nachricht --------
> > > Datum: Fri, 28 Oct 2011 18:13:14 +0200
> > > Von: "Martina Bauer" <Bauermartin@gmx.at>
> > > An: r-sig-finance@r-project.or
> > > Betreff: runMult instead of runSum
> > >
> > > Hello,
> > >
> > > Maybe my approach is wrong from the beginning but I would like to
> > > calculate from monthly data - one months and two months and lastly
> three
> > > months return
> > > I know that I have to multiply the monthly performance instead to sum
> up
> > -
> > > but I dont know how to do in R. Finally I should also rank the result
> > > according to n period performance (no clue how to archive this in R)
> > >
> > >
> > > here my code
> > >
> > > require(quantmod)
> > > stock=c("DD","DIS","PFE")
> > > DD.sp=Ad(DD)
> > > dd.m=monthlyReturn(DD.sp)
> > > dd1=runSum(dd.m,n=1)
> > > dd2=runSum(dd.m,n=2)
> > > dd3=runSum(dd.m,n=3)
> > >
> > > DIS.sp=Ad(DIS)
> > > dis.m=monthlyReturn(DIS.sp)
> > > dis1=runSum(DIS.m,n=1)
> > > dis2=runSum(DIS.m,n=2)
> > > dis3=runSum(DIS.m,n=3)
> > >
> > > PFE.sp=Ad(PFE)
> > > pfe.m=monthlyReturn(PFE.sp)
> > > pfe1=runSum(pfe.m,n=1)
> > > pfe2=runSum(pfe.m,n=2)
> > > pfe3=runSum(pfe.m,n=3)
> > >
> > >
> > > I know that my R code is very poor any idea how to improve ?
> > >
> > > THanks in advance
> > > Best Regards
> > >
> > > martin
> > >
> > > --
> > >
> > >
> > >
> > >
> > > --
> > >
> > > _______________________________________________
> > > R-SIG-Finance@r-project.org mailing list
> > > https://stat.ethz.ch/mailman/listinfo/r-sig-finance
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> > > -- Also note that this is not the r-help list where general R questions
> > > should go.
> > >
>
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