计算R的月度回报 [英] Calculating monthly returns in R
问题描述
我用这个代码计算每日回报:
return =(矩阵(NA,nrow(公司),ncol(公司)-1)
pre>
(j 2:52){
k = 0
我在1:nrow(companies)){
if(!is.na(companies [i,j])& k == 0){
ase = companies [i,j]
k = k + 1
else {if(k == 1){return [i,j-1] =((companies [i,j] -base)/ base)* 100 }
else {temp = 0}
}
}
}
return [1:30,]
我现在想计算相同公司组合的月度回报。我用来计算的公式是:
Return = [(每月最后一天价格) - (其他天))* 100 /(每月最后一天的价格)
我想重复这个过程一年12个月,12年(因为这是我所拥有的数据的持续时间)。我打算写一个for循环来做这个计算。有人可以帮我解决这个问题吗?不幸的是,我不能使用quantmod软件包,因为股票价格来自印度证券交易所,quantmod无法读取价格。 解决方案
你应该明确地使用 quantmod
,你可以。 quantmod
方法 monthlyReturn,dailyReturn,...,allReturns
需要 xts
时间序列作为输入。所以,如果你有每日数据(如收盘价)和相应的日期,你可以构建你的时间序列,并将其传递给所需的 quantmod
方法。
示例:
library(package =quantmod)
价格<-c(7655.88,7612.39,7612.39,7778.78,7756.44,7776.37)
日期< - 作为日期(c(2012-12-26,2012-12-27,2012 -12-30,2013-01-01,2013-01-02,2013-01-03))
ts < - xts(价格,日期)
dailyReturn(ts)
monthlyReturn(ts)#这将返回假数据,因为我们在这个例子中没有一个月的数据
This might be an insignificant question but unfortunately I'm unable to solve it. I have a portfolio of stocks of 50 companies. I have the dates and the closing prices on that particular day for each of the companies. Data for each company varies with respect to the date from which the stock is being traded.
I used this code for calculating the daily returns:
return=matrix(NA,nrow(companies),ncol(companies)-1)
for (j in 2:52){
k=0
for (i in 1:nrow(companies)){
if (!is.na(companies[i,j]) & k==0) {
base= companies[i,j]
k=k+1
}
else {if ( k==1) {return[i,j-1] = ((companies[i,j]-base)/base)*100}
else {temp=0}
}
}
}
return[1:30,]
I now want to calculate the monthly returns for the same portfolio of companies. The formula I am using to calculate this is:
Return = [(Price on Last day of month) - (Price on other day)]*100/(Price on last day of month)
I want to repeat this process for 12 months in a year and for a period of 12 years (since that is the duration of data I have). I am planning to write a for loop to do this calculation. Could someone please help me out with this. Unfortunately, I cannot use the quantmod package since the stock prices are from the Indian Stock Exchange, from which quantmod can't read the prices.
you should definitly use quantmod
, and you can. The quantmod
methods monthlyReturn, dailyReturn, ..., allReturns
require an xts
time series as input. So if you have daily data (e.g. close price) and the corresponding dates you can construct your time series and pass that to the desired quantmod
method.
Example:
library(package="quantmod")
prices <- c(7655.88, 7612.39, 7612.39, 7778.78, 7756.44, 7776.37)
dates <- as.Date(c("2012-12-26", "2012-12-27", "2012-12-30", "2013-01-01", "2013-01-02", "2013-01-03"))
ts <- xts(prices, dates)
dailyReturn(ts)
monthlyReturn(ts) # this will return bogus data because we don't have one month of data in this example
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