Merging irregular time series - r

Question

I have two time series, one being a daily time series and the other one a discrete one. In my case I have share prices and ratings I need to merge but in a way that the merged time series keeps the daily dates according to the stock prices and that the rating is fitted to the daily data by ticker and date.
A simple merge command would only look for the exact date and ticker and apply NA to non-fitting cases. But I would like to look for the exact matches and fill the dates between with last rating.
Daily time series:
ticker date stock.price
AA US Equity 2004-09-06 1
AA US Equity 2004-09-07 2
AA US Equity 2004-09-08 3
AA US Equity 2004-09-09 4
AA US Equity 2004-09-10 5
AA US Equity 2004-09-11 6
Discrete time series
ticker date Rating Last_Rating
AA US Equity 2004-09-08 A A+
AA US Equity 2004-09-11 AA A
AAL LN Equity 2005-09-08 BB BB
AAL LN Equity 2007-09-09 AA AA-
ABE SM Equity 2006-09-10 AA AA-
ABE SM Equity 2009-09-11 AA AA-
Required Output:
ticker date stock.price Rating
AA US Equity 2004-09-06 1 A+
AA US Equity 2004-09-07 2 A+
AA US Equity 2004-09-08 3 A
AA US Equity 2004-09-09 4 A
AA US Equity 2004-09-10 5 A
AA US Equity 2004-09-11 6 AA
I would be very greatful for your help.

Answer 1

Maybe this is the solution you want.
The function na.locf in the time series package zoo can be used to carry values forward (or backward).
library(zoo)
library(plyr)
options(stringsAsFactors=FALSE)
daily_ts=data.frame(
ticker=c('A','A','A','A','B','B','B','B'),
date=c(1,2,3,4,1,2,3,4),
stock.price=c(1.1,1.2,1.3,1.4,4.1,4.2,4.3,4.4)
)
discrete_ts=data.frame(
ticker=c('A','A','B','B'),
date=c(2,4,2,4),
Rating=c('A','AA','BB','BB-'),
Last_Rating=c('A+','A','BB+','BB')
)
res=ddply(
merge(daily_ts,discrete_ts,by=c("ticker","date"),all=TRUE),
"ticker",
function(x)
data.frame(
x[,c("ticker","date","stock.price")],
Rating=na.locf(x$Rating,na.rm=FALSE),
Last_Rating=na.locf(x$Last_Rating,na.rm=FALSE,fromLast=TRUE)
)
)
res=within(
res,
Rating<-ifelse(
is.na(Rating),
Last_Rating,Rating
)
)[,setdiff(colnames(res),"Last_Rating")]
res
Gives
# ticker date stock.price Rating
#1 A 1 1.1 A+
#2 A 2 1.2 A
#3 A 3 1.3 A
#4 A 4 1.4 AA
#5 B 1 4.1 BB+
#6 B 2 4.2 BB
#7 B 3 4.3 BB
#8 B 4 4.4 BB-