rowSums but keeping NA values

If you have a variable number of columns you could try this approach:

mm <- merge(dd1,dd2)
mm$m <- rowSums(mm, na.rm=TRUE) * ifelse(rowSums(is.na(mm)) == ncol(mm), NA, 1)
# or, as @JoshuaUlrich commented:
#mm$m <- ifelse(apply(is.na(mm),1,all),NA,rowSums(mm,na.rm=TRUE))
tail(mm, 10)
#                  dd1        dd2        m
#2013-08-02        NA         NA       NA
#2013-08-03        NA         NA       NA
#2013-08-04        NA         NA       NA
#2013-08-05 1.2542692 -1.2542692 0.000000
#2013-08-06        NA  1.3325804 1.332580
#2013-08-07        NA  0.7726740 0.772674
#2013-08-08 0.8158402 -0.8158402 0.000000
#2013-08-09        NA  1.2292919 1.229292
#2013-08-10        NA         NA       NA
#2013-08-11        NA  0.9334900 0.933490

Use logical indexing with [ and is.na(·) to localize the entries where both are NA and then replace them with NA.

Try this:

> mm[is.na(mm$dd1) & is.na(mm$dd2), "m"] <- NA
> mm
                 dd1        dd2        m
2013-08-02        NA         NA       NA
2013-08-03        NA         NA       NA
2013-08-04        NA         NA       NA
2013-08-05 1.2542692 -1.2542692 0.000000
2013-08-06        NA  1.3325804 1.332580
2013-08-07        NA  0.7726740 0.772674
2013-08-08 0.8158402 -0.8158402 0.000000
2013-08-09        NA  1.2292919 1.229292
2013-08-10        NA         NA       NA
2013-08-11        NA  0.9334900 0.933490