[R-SIG-Finance] disaggregate from monthly to daily time series
John P. Burkett
burkett at uri.edu
Tue Jul 28 00:10:43 CEST 2009
Joshua Ulrich wrote:
> Here's some code that follows Brian's suggestion.
Thank you, Brian and Joshua, for your suggestions. Having tried the code
on a Ubuntu box running R 2.8.1, I'm inserting my comments below the
> x <- xts(cumprod(1+rnorm(999)/100),Sys.Date()-999:1)
> m <- timeBasedSeq('2006-11/2009-07', 'Date')
This line elicits the message "Error in strftime(x) : wrong class"
However the line seems to work o.k. if shortened to
m <- timeBasedSeq('2006-11/2009-07')
> mx <- x[m]
This line generates 50 or more warnings of the form
"In timeBasedSeq(x, NULL) : NAs introduced by coercion"
Are those the NAs Brian mentioned?
dim(mx) is 0, 1. Doing "mx" gets the following response:
Is that what was intended?
> M <- merge(mx,x)
> mtod.spline <- xts(spline(1:NROW(M),M[,1],n=NROW(M))$y,index(x))
> mtod.linear <- xts(approx(1:NROW(M),M[,1],n=NROW(M))$y,index(x))
> mtod <- merge(x,mtod.spline,mtod.linear)
The end result on my box is three seemingly identical series: x,
mtod.spline, mtod.linear. I'm still thinking about how they relate the
problem of disaggregating a monthly series into smooth daily series with
the original mean.
> On Mon, Jul 27, 2009 at 1:22 PM, Brian G. Peterson<brian at braverock.com> wrote:
>> Well, leaving aside the fact that this seems like a pretty low-utility idea
>> (ymmv), na.approx or na.spline will do this if you cbind a monthly series to
>> a daily series, and then apply na.approx to the NA's in the (formerly)
>> monthly data.
>> - Brian
>> John P. Burkett wrote:
>>> I would like to disaggregate a monthly average (Consumer Price Index) to
>>> create a daily time series. The new daily series should be smooth
>>> (i.e.--exhibit no unusual jump from the last day of a month to the first day
>>> of the next month) and be consistent with the original monthly data
>>> (i.e.--the average value of the new series for the days of a month should
>>> equal the given value for that month).
>>> If all months had 30 days and I were using S+Finmetrics, I would try to
>>> create the daily series with a command such as
>>> disaggregate(CPI, 30, method="spline", how="mean")
>>> where CPI is the monthly data on the Consumer Price Index.
>>> The fact that months are of different lengths complicates matters.
>>> Suggestions for how to accomplish the disaggregation in R would be greatly
>> Brian G. Peterson
>> Ph: 773-459-4973
>> IM: bgpbraverock
>> R-SIG-Finance at stat.math.ethz.ch mailing list
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>> -- If you want to post, subscribe first.
John P. Burkett
Department of Economics
University of Rhode Island
Kingston, RI 02881-0808
phone (401) 874-9195
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