Re: [R] exces return by mktcap decile for each year
here is one way of doing it using 'ave':
dat - read.table(textConnection(mc yrret
+ 32902.233 01/01/1995 0.426
+ 15793.691 01/01/1995 0.024
+ 2375.868 01/01/1995 0.660
+ 54586.558 01/01/1996 0.497
+ 10674.900 01/01/1996 0.405
+859.656 01/01/1996 -0.033
+770.963 01/01/1995 -1.248
+423.480 01/01/1995 0.654
+ 2135.504 01/01/1995 0.394
+696.599 01/01/1995 -0.482
+ 5115.476 01/01/1995 0.352
+821.347 01/01/1995 0.869
+ 43329.695 01/01/1995 0.495
+ 7975.151 01/01/1995 0.112
+396.450 01/01/1995 0.956
+843.870 01/01/1995 0.172
+ 2727.037 01/01/1995 -0.358
+114.584 01/01/1995 -1.015
+ 1347.327 01/01/1995 -0.083
+ 4592.049 01/01/1995 -0.251
+674.305 01/01/1995 -0.327
+ 39424.887 01/01/1996 0.198
+ 4447.383 01/01/1996 -0.045
+ 1608.540 01/01/1996 -0.109
+217.151 01/01/1996 0.539
+ 1813.320 01/01/1996 0.754
+145.170 01/01/1996 0.249
+ 3176.298 01/01/1996 -0.202
+ 14379.686 01/01/1996 0.013
+ 3009.059 01/01/1996 -0.328
+ 1781.406 01/01/1996 -0.158
+ 2576.215 01/01/1996 0.514
+ 1236.317 01/01/1996 0.346
+ 3003.735 01/01/1996 0.151
+ 1544.003 01/01/1996 0.482
+ 7588.657 01/01/1996 0.306
+ 1516.625 01/01/1996 0.183
+ 1596.098 01/01/1996 0.674
+ 2792.192 01/01/1996 0.528
+ 1276.702 01/01/1996 0.010
+875.716 01/01/1996 0.189
+ 4858.450 01/01/1995 0.250
+ 2033.623 01/01/1995 -0.582
+ 2164.125 01/01/1995 0.631), header=TRUE)
# quantiles by year (need as grouping in next statement
dat$qByYr - ave(dat$mc, dat$yr, FUN=function(x){
+ cut(x, quantile(x, prob=seq(0, 1, .1)), include.lowest=TRUE)
+ })
# compute the mean for year/quantile
dat$dec.mean - ave(dat$ret, dat$yr, dat$qByYr, FUN=mean)
# mean adjusted return
dat$mean.adjusted - dat$ret - dat$dec.mean
dat
mc yrret qByYr dec.mean mean.adjusted
1 32902.233 01/01/1995 0.42610 0.4605000 -0.03450
2 15793.691 01/01/1995 0.024 9 0.068 -0.04400
3 2375.868 01/01/1995 0.660 6 0.6455000 0.01450
4 54586.558 01/01/1996 0.49710 0.236 0.26100
5 10674.900 01/01/1996 0.405 9 0.3555000 0.04950
6859.656 01/01/1996 -0.033 1 0.2516667 -0.28467
7770.963 01/01/1995 -1.248 3 -0.1895000 -1.05850
8423.480 01/01/1995 0.654 1 0.198 0.45567
9 2135.504 01/01/1995 0.394 5 -0.094 0.48800
10 696.599 01/01/1995 -0.482 2 -0.4045000 -0.07750
11 5115.476 01/01/1995 0.352 8 0.301 0.05100
12 821.347 01/01/1995 0.869 3 -0.1895000 1.05850
13 43329.695 01/01/1995 0.49510 0.4605000 0.03450
14 7975.151 01/01/1995 0.112 9 0.068 0.04400
15 396.450 01/01/1995 0.956 1 0.198 0.75767
16 843.870 01/01/1995 0.172 4 0.0445000 0.12750
17 2727.037 01/01/1995 -0.358 7 -0.3045000 -0.05350
18 114.584 01/01/1995 -1.015 1 0.198 -1.21333
19 1347.327 01/01/1995 -0.083 4 0.0445000 -0.12750
20 4592.049 01/01/1995 -0.251 7 -0.3045000 0.05350
21 674.305 01/01/1995 -0.327 2 -0.4045000 0.07750
22 39424.887 01/01/1996 0.19810 0.236 -0.03800
23 4447.383 01/01/1996 -0.045 8 -0.1235000 0.07850
24 1608.540 01/01/1996 -0.109 5 0.162 -0.27133
25 217.151 01/01/1996 0.539 1 0.2516667 0.28733
26 1813.320 01/01/1996 0.754 5 0.162 0.59167
27 145.170 01/01/1996 0.249 1 0.2516667 -0.00267
28 3176.298 01/01/1996 -0.202 8 -0.1235000 -0.07850
29 14379.686 01/01/1996 0.01310 0.236 -0.22300
30 3009.059 01/01/1996 -0.328 7 -0.0885000 -0.23950
31 1781.406 01/01/1996 -0.158 5 0.162 -0.32033
32 2576.215 01/01/1996 0.514 6 0.521 -0.00700
33 1236.317 01/01/1996 0.346 2 0.2675000 0.07850
34 3003.735 01/01/1996 0.151 7 -0.0885000 0.23950
35 1544.003 01/01/1996 0.482 4 0.578 -0.09600
36 7588.657 01/01/1996 0.306 9 0.3555000 -0.04950
37 1516.625 01/01/1996 0.183 3 0.0965000 0.08650
38 1596.098 01/01/1996 0.674 4 0.578 0.09600
39 2792.192 01/01/1996 0.528 6 0.521 0.00700
40 1276.702 01/01/1996 0.010 3 0.0965000 -0.08650
41 875.716 01/01/1996 0.189 2 0.2675000 -0.07850
42 4858.450 01/01/1995 0.250 8 0.301 -0.05100
43 2033.623 01/01/1995 -0.582 5 -0.094 -0.48800
44 2164.125 01/01/1995 0.631 6 0.6455000 -0.01450
On 7/11/07, Frank Hansen [EMAIL PROTECTED] wrote:
Hi Jim,
Thanks for getting back on this. I did not see your
email on the help list. I or you can post this
solution
You are right I mis-stated about mc. mc is real, it is
yr that is a factor.
Here is a solution, which works, but it is clunky. I
thought there might be a better/more R-like less
for-loop way to
[R] exces return by mktcap decile for each year
I have a data frame, lets call it dat,
with 3 columns ( mc, yr, ret) which represent market
cap, year, and return. mc is a factor, mc, and ret are
real numbers.
I want to add a column to the data calculated as
follows.
For each year, I want to split the data by mc decile,
then calculate the mean ret within that mc decile, and
finally subtract that year's decile mean from the raw
return. Then I want that mean adjusted ret to be the
new column.
I can get the market cap deciles with
my.cut - function(x) {
cut( x, quantile( x, probs=seq(0,1,0.1),
na.rm=TRUE))
}
mc.deciles - by( dat$mc, dat$yr, my.cut)
I don't know how to associate the values in mc.deciles
with a particular row of the original data frame dat.
I don't think I can unlist mc.deciles because the
order won't be the same.
If I could append mc.deciles as a new column to dat,
then I could do something like
by( dat$ret, list( dat$yr, dat$decile), mean)
In which case I would still be faced with finding the
right mean to subtract from each entry in dat$ret.
Maybe I'm just stuck on by() and cut() when there is
an easier way to handle this. Any suggestions? Thanks.
__
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
