[R-SIG-Finance] re-indexing data under the zoo package

[Gabor Grothendieck]

On Mon, Feb 28, 2011 at 2:38 PM, Gabor Grothendieck
<ggrothendieck at gmail.com> wrote:
> On Mon, Feb 28, 2011 at 12:36 PM, Aidan Corcoran
> <aidan.corcoran11 at gmail.com> wrote:
>> Dear all,
>>
>> I was hoping someone could help me to generate an index based on data
>> in zooreg format. The data are of the form
>>
>>> head(dq)
>>        sphsxs eunrfi irhont
>> 1995(1)  670.8   82.9     NA
>> 1995(2)  686.0   82.9     NA
>> 1995(3)  682.6   83.0     NA
>> 1995(4)  692.7   82.7     NA
>> 1996(1)  686.0   81.5   33.6
>> 1996(2)  697.8   82.0   34.6
>>
>> and I would like to index each of the three variables to 100 in
>> 1996(1). I have made a few failed attempts based on extracting the
>> values at that date
>>
>>> dq[index(dq)==1996.00]
>>        sphsxs eunrfi irhont
>> 1996(1)    686   81.5   33.6
>>
>> and then trying to divide the series by those values
>>
>>> dq/dq[index(dq)==1996.00]
>>     sphsxs eunrfi irhont
>> 1996      1      1      1
>>
>> but this results in a single row. One option might be to replicate the
>> 1996 row using rep, but
>>
>>> rep(dq[index(dq)==1996.00],2)
>> [1] 686.0  81.5  33.6 686.0  81.5  33.6
>>
>> seems to repeat the data within a single vector, and I'm not sure how
>> to get it to repeat the row down through a zoo object (and suspect
>> there might be an easier way).
>>
>> Any help much appreciated.
>>
>
> Any of these will refer to the data at 1996:
>
> library(zoo)
> # dq <- ... shown at end ...
>
> dq[ I(1996) ]
> dq[ "1996" ]
> window(dq, 1996, 1996)
>
> 1. Here is a slight variation of Arun.stat's solution that will
> produce values relative to 1996:
>
> dq100 <- dq
> dq100[] <- t(apply(dq, 1, "/", coredata(dq["1996"])))
>
>> dq100
>           sphsxs   eunrfi   irhont
> 1995(1) 0.9778426 1.017178       NA
> 1995(2) 1.0000000 1.017178       NA
> 1995(3) 0.9950437 1.018405       NA
> 1995(4) 1.0097668 1.014724       NA
> 1996(1) 1.0000000 1.000000 1.000000
> 1996(2) 1.0172012 1.006135 1.029762
>
> 2. Another thing you might consider would be to use "yearqtr" class for dq:
>
> # convert time to yearqtr
> dq.yq <- dq
> time(dq.yq) <- as.yearqtr(time(dq.ym))
>
> # index relative to 1996 Q1
> dq.yq100 <- dq.ym
> dq.yq100 <- t(apply(dq.yq, 1, "/", coredata(dq[as.yearqtr("1996 Q1")])))
>
>> dq.yq100
>             [,1]     [,2]     [,3]
> 1995 Q1 0.9778426 1.017178       NA
> 1995 Q2 1.0000000 1.017178       NA
> 1995 Q3 0.9950437 1.018405       NA
> 1995 Q4 1.0097668 1.014724       NA
> 1996 Q1 1.0000000 1.000000 1.000000
> 1996 Q2 1.0172012 1.006135 1.029762
>
> 3. ts class would work here too since its regularly spaced:
>
> tt <- as.ts(dq)
> tt[] <- t(apply(tt, 1, "/", window(tt, 1996, 1996)))
> tt
>
> Here is the dq used above:
>
> dq <-
> structure(c(670.8, 686, 682.6, 692.7, 686, 697.8, 82.9, 82.9,
> 83, 82.7, 81.5, 82, NA, NA, NA, NA, 33.6, 34.6), .Dim = c(6L,
> 3L), .Dimnames = list(NULL, c("sphsxs", "eunrfi", "irhont")), index = c(1995,
> 1995.25, 1995.5, 1995.75, 1996, 1996.25), class = c("zooreg",
> "zoo"), frequency = 4)

4. and here is one more solution that is slightly simpler as it avoids
the transposition:

dq2 <- dq
dq2[] <- mapply("/", as.data.frame(dq), coredata(dq["1996"]))

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