I want to calculate a rolling 10-year-return from 1965-2021. That means that the result should be a table or data frame with the returns over a period of 10 years (1965-1974, 1966-1975, 1967-1976, etc.) like this:
To calculate the 10-year-return, divide the last available stock price from 1974 (e.g. 12/30/1975) by the first available stock price in 1965 (eg. 01/04/1965) and subtract 1.
10-year-return = (last stockprice 1974/first stock price 1965) -1
This calculation is then to be calculated automatically for the following years (1966-1975, 1967-1976, 1968 - 1977 etc.).
I do not know how to implement this in R studio.
Following is my code. The stock prices are in the column N225Adjusted.
library(quantmod)
data.N225 <- getSymbols("^N225",from="1965-01-01", to="2022-03-30", auto.assign=FALSE, src='yahoo') # funktion getSymbols wenn wir Kapitalmarkt haben wollten
class(data.N225)
data.N225[c(1:3, nrow(data.N225)),]
data.N225<- na.omit(data.N225)
N225 <- data.N225[,6]
N225$DiskreteRendite= Delt(N225$N225.Adjusted)
N225[c(1:3,nrow(N225)),]
options(digits=5)
N225$dailyretrunsplusone <- N225$DiskreteRendite 1
N225 <- fortify.zoo(N225)
N225 <- N225[,c(1,2,4)]
The greatest problem is that I need a code that includes the date.
I hope you can help me. Thank you so much in advance!
CodePudding user response:
I used a few packages, but you don't really need scales
.
library(quantmod)
library(scales)
library(tidyverse)
library(lubridate)
data <- getSymbols("^N225", from = "1965-01-01", to = "2022-03-30", auto.assign = F, src = "yahoo")
df <- as_tibble(data.frame(Date = index(data), coredata(data)))
df %>%
na.omit() %>%
group_by(year = year(Date)) %>%
summarise(fprice = first(N225.Adjusted), lprice = last(N225.Adjusted)) %>%
mutate(Returns = (lprice/lag(fprice, n = 9L))-1) %>%
na.omit() %>%
mutate(year_from_to = paste(year-9, year, sep = "-"), Returns = percent(Returns)) %>%
select(year_from_to, Returns)
Giving the following output
#> # A tibble: 49 × 2
#> year_from_to Returns
#> <chr> <chr>
#> 1 1965-1974 205.07%
#> 2 1966-1975 203.61%
#> 3 1967-1976 246.26%
#> 4 1968-1977 284.04%
#> 5 1969-1978 241.96%
#> 6 1970-1979 173.40%
#> 7 1971-1980 255.03%
#> 8 1972-1981 183.22%
#> 9 1973-1982 53.20%
#> 10 1974-1983 132.29%
#> # … with 39 more rows
As required.