average values for time series

Fri, Apr 29, 2005 2:17 AM

Dear all,
I followed Dirk's suggestions and got:

 > IBM <- priceIts("IBM",quote="Close")
Errore in validObject(.Object) : invalid class "its" object: Missing 
values in dates

I tried with other securities but I get the same error.

x1 <- priceIts(instrument=c("^ftse"), start="1998-01-01", quote = "Close")
Errore in validObject(.Object) : invalid class "its" object: Missing 
values in dates

I would appreciate if you could give me any hints.

Best regards,
Massimo

Dirk Eddelbuettel wrote:

On 27 April 2005 at 06:37, Jonathan Q. wrote:
| New to R, currently use FAME.  One of the things I like about FAME is
| that if I have a series, say the near month for a commodity, I can set
| the series property so when i view weekly data, the data is the
| average of the daily data.  alternatively, for other series like stock

There are probably several ways to do that. 

| prices I can have the series always display the last value (i.e.,
| monthly would take last value in month vs the average).  also able to

The its package does that pretty well:

library(its)				## verbose output suppressed here
IBM<-priceIts("IBM",quote="Close")	## fetches from Yahoo!
head(IBM)

           IBM Close
1991-01-02    112.12
1991-01-03    112.50
1991-01-04    112.12
1991-01-07    110.25
1991-01-08    109.00
1991-01-09    106.87

head(extractIts(IBM, find="last", period="week"))

           IBM Close
1991-01-04    112.12
1991-01-11    108.12
1991-01-18    117.62
1991-01-25    122.62
1991-02-01    126.87
1991-02-08    129.50

head(extractIts(IBM, find="last", period="month"))

           IBM Close
1991-01-31    126.75
1991-02-28    128.75
1991-03-28    113.87
1991-04-30    103.00
1991-05-31    106.12
1991-06-28     97.12

I just taught myself how to the other part with zoo -- pretty slick:

library(zoo)				## once again verbose output nixed
IBMzoo <- zoo(IBM)			## turn its object into zoo object
head(aggregate(IBMzoo, format(dates(IBM), "%Y-%m"), mean))


1991-01 115.4127
1991-02 132.2053
1991-03 123.3240
1991-04 109.6800
1991-05 104.2241
1991-06 100.8970


This runs aggregate() over the zoo() object where the on-the-fly factor is
computed from the underlying POSIXt date representation, and the aggregating
function, here mean, is then passed over each unique factor set.

Hope this helps,  Dirk

average values for time series

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