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R 中 NA 的累积回报

[英]Cumulative Returns with NA's in R

I have the following data frame:我有以下数据框:

df <- data.frame(Return1=c(NA, NA, .03, .04, .05),
             Return2=c(.25, .33, NA, .045, .90),
             Return3=c(.04, .073, .08, .04, .01))


  Return1 Return2 Return3
1      NA   0.250   0.040
2      NA   0.330   0.073
3    0.03      NA   0.080
4    0.04   0.045   0.040
5    0.05   0.900   0.010

I would like to compute the cumulative returns, but there are missing values in the dataframe.我想计算累积回报,但数据框中缺少值。 I used:我用了:

cumprod(df+1)-1

Getting as a result结果得到

  Return1 Return2   Return3
1      NA  0.2500 0.0400000
2      NA  0.6625 0.1159200
3      NA      NA 0.2051936
4      NA      NA 0.2534013
5      NA      NA 0.2659354

The problem here is that if there is a NA, the subsequent rows down will have as a Result NA.这里的问题是,如果有 NA,则后续行将作为结果 NA。 Is there a way to compute the cumulative returns without NA's affecting the rest of the rows below?有没有办法在不影响下面其余行的情况下计算累积回报?

I would like to obtain as a result:我想得到这样的结果:

  Return1 Return2   Return3
1      NA  0.2500 0.0400000
2      NA  0.6625 0.1159200
3    0.03     NA  0.2051936
4 0.07120  0.7373 0.2534013
5 0.12476  2.3008 0.2659354

I know of a function in the PerformanceAnalytics package called Return.cumulative,but this will only obtain the cumulative return of the entire columns.我知道 PerformanceAnalytics 包中有一个名为 Return.cumulative 的函数,但这只会获得整个列的累积回报。

Any ideas?有任何想法吗?

cumpfun <- function(x){
  x[!is.na(x)] <- cumprod(x[!is.na(x)]+1)-1
  x
}
sapply(df,cumpfun)

#      Return1   Return2   Return3
# [1,]      NA 0.2500000 0.0400000
# [2,]      NA 0.6625000 0.1159200
# [3,] 0.03000        NA 0.2051936
# [4,] 0.07120 0.7373125 0.2534013
# [5,] 0.12476 2.3008937 0.2659354

Note that sapply returns a matrix.请注意, sapply返回一个矩阵。 If you need a data frame, you could use sth like as.data.frame(lapply(df, cumpfun))如果你需要一个数据框,你可以使用像as.data.frame(lapply(df, cumpfun))

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