我有两个数据框,第一个是3个证券的每日回报,第二个是证券的权重,如下:
daily.return <- data.frame(date = seq.Date(from = as.Date("2015-01-01"),
by = "days",
length.out = 100),
a = runif(100,-0.1,0.1),
b = runif(100,-0.1,0.1),
c = runif(100,-0.1,0.1))
weights <- data.frame(startDate = c(as.Date("2015-01-01"),
as.Date("2015-02-10"),
as.Date("2015-03-15")),
endDate = c(as.Date("2015-02-09"),
as.Date("2015-03-14"),
as.Date("2015-04-10")),
a = c(0.3,0.5,0.2),
b = c(0.4,0.2,0.1),
c = c(0.3,0.3,0.7)
)
我知道如何将数据分成几周等等,如果我们将数据帧转换为xts;但是如何将其每日拆分。根据startDate和endDate的权重返回? 假设一只基金有这三种证券,如何计算基金导航和每日回报?
答案 0 :(得分:1)
这应该可以胜任。
daily.return <- data.frame(date = seq.Date(from = as.Date("2015-01-01"),
by = "days",
length.out = 100),
a = runif(100,-0.1,0.1),
b = runif(100,-0.1,0.1),
c = runif(100,-0.1,0.1))
weights <- data.frame(startDate = c(as.Date("2015-01-01"),
as.Date("2015-02-10"),
as.Date("2015-03-15")),
endDate = c(as.Date("2015-02-09"),
as.Date("2015-03-14"),
as.Date("2015-04-10")),
a = c(0.3,0.5,0.2),
b = c(0.4,0.2,0.1),
c = c(0.3,0.3,0.7)
)
library(quantmod)
daily.xts <- as.xts(daily.return[,-1],daily.return[,1])
# Assuming that the total period is the same in both the data frames
weights.xts <- xts(matrix(NA,nrow(daily.xts),3),order.by=index(daily.xts))
names(weights.xts) <- c("a","b","c")
for (i in 1:nrow(weights)){
temp.inputs <- weights[i,]
temp.period <- paste(temp.inputs[,1],temp.inputs[,2],sep="/")
len <- nrow(weights.xts[temp.period])
weights.xts[temp.period,1:3] <- matrix(rep(as.numeric(temp.inputs[,3:5]),len),len,byrow=T)
}
weighted.returns <- daily.xts * weights.xts
weighted.returns <- as.xts(rowSums(weighted.returns),index(weighted.returns))
names(weighted.returns) <- "Weighted Returns"
weighted.returns$Cumulative <- cumsum(weighted.returns)
plot(weighted.returns$Cumulative)
答案 1 :(得分:0)
您可以使用daily.return
根据权重的开始和结束日期拆分apply
,执行逐行操作
apply(weights, 1, function(x) daily.return[daily.return$date >= x[1]
& daily.return$date <= x[2], ])
这将根据weights
中的范围提供3个数据帧的列表。
修改强>
如果我理解正确,您希望a
的{{1}},b
,c
列中的每个值与{{1}中的相应列相乘}}。
daily.return