Question

我有一个数据框，在一段时间内有各种股票回报。收益率为百分比收益或损失（.02表示2％收益或102％之前的收益率值）。

我正在寻找一个函数或方法来累积显示每个时期的回报（百分比）。例如，这将显示stock1的累积/复合增益为前3个时段的.02，.0404，.09242 ......（1.02 * 1.02 * 1.05）。

   mydf = data.frame(period = c('a','b','c','d','e','f'), stock1=c(.02, .02, .05,-.05,-.05,0), stock2=c(0, .01,0,.03,.05,.01))
   mydf
   #help mydf$stk1_percentgain =

Answer 1

这将为您提供按期间累积的回报：

sapply(mydf[,-1], function(x) cumprod(1 + x) - 1)

          stock1    stock2
[1,]  0.02000000 0.0000000
[2,]  0.04040000 0.0100000
[3,]  0.09242000 0.0100000
[4,]  0.03779900 0.0403000
[5,] -0.01409095 0.0923150
[6,] -0.01409095 0.1032382

或者如果你想要一些更具人类可读性的东西：

sapply(mydf[,-1], function(x) paste0(sprintf("%0.2f", (cumprod(1 + x) - 1)*100, 2),"%"))

     stock1   stock2  
[1,] "2.00%"  "0.00%" 
[2,] "4.04%"  "1.00%" 
[3,] "9.24%"  "1.00%" 
[4,] "3.78%"  "4.03%" 
[5,] "-1.41%" "9.23%" 
[6,] "-1.41%" "10.32%"

Answer 2

您可以使用dplyr：

mydf %>% 
  mutate_each(funs(
    paste0(formatC(100 * (cumprod(1 + .) - 1), format = "f", 2), "%")), -period)

给出了：

#  period stock1 stock2
#1      a  2.00%  0.00%
#2      b  4.04%  1.00%
#3      c  9.24%  1.00%
#4      d  3.78%  4.03%
#5      e -1.41%  9.23%
#6      f -1.41% 10.32%

r的累积百分比回报率

2 个答案: