returnSummary

library(lubridate)
library(stringr)
library(reshape2)
library(plyr)
library(dplyr)

# read all csv files and merge
# assumes files exist in data folder
dataDir <- "data"
files <- dir(dataDir, full.name = TRUE)
dataList <- llply(files, function(file){
      data <- read.csv(file, stringsAsFactors = FALSE)
      # get code from file path
      pattern <- "/[A-Z][A-Z][A-Z][A-Z]"
      code <- substr(str_extract(file, pattern), 2,
                     nchar(str_extract(file, pattern)))
      # first column's name is funny
      names(data) <- c("Date","Close")
      data$Date <- dmy(data$Date)
      data$Close <- as.numeric(data$Close)
      # code will be used to 'dcast' data
      data$Code <- code
      data
}, .progress = "text")

data <- rbind_all(dataList)

# convert into a wide format
data <- dcast(data, Date ~ Code, value.var="Close")

# apply log difference column wise
dailyRet <- apply(log(data[, 2:dim(data)[2]]), 2, diff, lag=1)

# obtain daily return, variance and correlation
returns <- apply(dailyRet, 2, sum, na.rm = TRUE)
variance <- apply(dailyRet, 2, var, na.rm = TRUE)
correlation <- cor(dailyRet)

returns
variance
correlation