R DF referencing 2 different rows in same column (Returns)

Question

I am trying to create a new column in my DF called "Returns" but I'm having difficulty finding how to divide 2 variables in the same column but different rows.

Here's the DF:

Date                  Open High  Low AdjClose  
2014-02-13 2014-02-13 1815 1830 1809     1830 
2014-02-12 2014-02-12 1820 1827 1816     1819 
2014-02-11 2014-02-11 1800 1824 1800     1820 
2014-02-10 2014-02-10 1796 1800 1792     1800 
2014-02-07 2014-02-07 1776 1798 1776     1797 
2014-02-06 2014-02-06 1753 1774 1753     1773

I'm assuming the code looks something like this:

SPXprices.df$Returns <- (SPXprices.df$AdjClose - SPXprices$AdjClose[x,x])/SPXprices$AdjClose[x,x]

I was hoping someone could help me here.

Any insight would be greatly appreciated!

Answer 1

Here is a way to do it by referencing the previous day

returns<-sapply(1:length(SPXprices.df$AdjClose), 
  FUN=function(x) (SPXprices.df$AdjClose[x] - SPXprices.df$AdjClose[x+1])/SPXprices.df$AdjClose[x+1])


SPXprices.df$Returns <- returns

In the sapply function, I am referencing the next day using SPXprices.df$AdjClose[x+1])

Answer 2

Is this what you are looking for?

SPXprices.df <- read.table(header=T, text=
"
Date                  Open High  Low AdjClose  
2014-02-13 2014-02-13 1815 1830 1809     1830 
2014-02-12 2014-02-12 1820 1827 1816     1819 
2014-02-11 2014-02-11 1800 1824 1800     1820 
2014-02-10 2014-02-10 1796 1800 1792     1800 
2014-02-07 2014-02-07 1776 1798 1776     1797 
2014-02-06 2014-02-06 1753 1774 1753     1773
")

#sorting the data
SPXprices.df <- SPXprices.df[order(SPXprices.df$Date),]
#using lagpad from http://stackoverflow.com/a/13128713/2862090 to lag
lagpad <- function(x, k) {
  c(rep(NA, k), x)[1 : length(x)] 
}

#showing the result of lagpad
SPXprices.df$lagAdjClose <- lagpad(SPXprices.df$AdjClose,1)

#calculate returns
SPXprices.df$Returns <- (SPXprices.df$AdjClose - lagpad(SPXprices.df$AdjClose,1))/lagpad(SPXprices.df$AdjClose,1)

SPXprices.df
                Date Open High  Low AdjClose lagAdjClose       Returns
2014-02-06 2014-02-06 1753 1774 1753     1773          NA            NA
2014-02-07 2014-02-07 1776 1798 1776     1797        1773  0.0135363790
2014-02-10 2014-02-10 1796 1800 1792     1800        1797  0.0016694491
2014-02-11 2014-02-11 1800 1824 1800     1820        1800  0.0111111111
2014-02-12 2014-02-12 1820 1827 1816     1819        1820 -0.0005494505
2014-02-13 2014-02-13 1815 1830 1809     1830        1819  0.0060472787