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rloggingreturnstockln

log return calculation by many companies r

I have a file like this.

head(Historical_Stock_Prices_R)
    Date1     MSFT    AAPL   GOOGL
1 25-01-05 21.02985 4.873362 88.56
2 26-01-05 21.02177 4.886890 94.62
3 27-01-05 21.10259 4.913269 94.04

want to calculate log return using this formula ln(current price/previous price) and my expected output is like this

 Date1        MSFT   AAPL    GOOGL          
26-01-05    -0.04%  0.28%    6.62%
27-01-05     0.38%  0.54%   -0.61%

tried to solve by this codes from previous stack overflow answer but fail

logs=data.frame( cbind.data.frame(newdates[-1], 

diff(as.matrix(log(Historical_Stock_Prices_R[,-1])))))
Solution

  • Try this:

    df = read.table(text="
Date1     MSFT    AAPL   GOOGL
1 25-01-05 21.02985 4.873362 88.56
2 26-01-05 21.02177 4.886890 94.62
3 27-01-05 21.10259 4.913269 94.04",header=T)

cbind.data.frame(date=df$Date1[-1],apply(df[,2:4],2,function(x) log(x[-1]/x[-length(x)])*100))

#       date        MSFT      AAPL      GOOGL
# 2 26-01-05 -0.03842896 0.2772061  6.6188582
# 3 27-01-05  0.38372143 0.5383395 -0.6148647