merge zoo with many entries per date with lagged self using ticker

OK, I'm learning :). With more tinkering I found that the zoo lag operator
lags by rows, not by time stamps, so it fails if there are multiple entries
per time stamp. I may be forced to switch to data frame, perform the
following operation, then switch back to zoo.
Here is the manual coding of the operation I'd like (with a small data
frame) to do all in the zoo class (or some other time series):

# create a zoo multiple symbols per month
temp <- data.frame(date=rep(200808:200811, each=3),
symbol=rep(letters[1:3], times=4), ret=1:12)
# find unique date entries
unique.date <- unique(temp$date)
# shift the date num.lags to match future performance with current
stock/date
num.lags <- 1
temp.lag <- temp[which(temp$date > unique.date[num.lags]), ]
for (i in seq(num.lags+1, length(unique.date), 1)) {

+ ? ? temp.lag$date[which(temp.lag$date==unique.date[i])] <-
unique.date[i-num.lags]
+ }

# merge
temp.merged <- merge(temp, temp.lag, by=c("date", "symbol"),
suffixes=c(".now", ".next"))
temp.merged

?? ?date symbol ret.now ret.next
1 200808 ? ? ?a ? ? ? 1 ? ? ? ?4
2 200808 ? ? ?b ? ? ? 2 ? ? ? ?5
3 200808 ? ? ?c ? ? ? 3 ? ? ? ?6
4 200809 ? ? ?a ? ? ? 4 ? ? ? ?7
5 200809 ? ? ?b ? ? ? 5 ? ? ? ?8
6 200809 ? ? ?c ? ? ? 6 ? ? ? ?9
7 200810 ? ? ?a ? ? ? 7 ? ? ? 10
8 200810 ? ? ?b ? ? ? 8 ? ? ? 11
9 200810 ? ? ?c ? ? ? 9 ? ? ? 12

library(zoo)
f <- function(x) as.yearmon(as.character(x), "%Y%m")
z <- read.zoo(temp, split = "symbol", FUN = f)
lag(z, 0:1)