TickDataConversion.r

#reads ticks and creates .rda file

library(xts)
library(zoo)
library(blotter)

symbol = "GBPJPY"

tick.data.dir <- paste0('g:\\JForex\\data\\', symbol)
tick.data.outdir <- "g:\\TickData\\"

opts <- options(digits.secs = 0)

#creates RDA files from csv tick data
createRDA <- function(){

  filenames=list.files(path=tick.data.dir, pattern = ".csv", full.names=TRUE)
  for(filename in filenames) {
    print(paste("Processing:", filename))
    ts <- read.csv(filename, header=T)
    assign(symbol, xts(ts[,2:5], as.POSIXct(ts[,1],format="%Y.%m.%d %H:%M:%OS", tz="UTC")))
    rm(ts)
    saveSymbols.days(symbol, base_dir = tick.data.outdir)
    rm(list = ls(pattern = symbol))
    gc() 
  }
}
# creates xts object with OHLC candles
createCustomCandlesticTimeSeries <- function(unit, fragment , from, to, dir){
  .env <- new.env()
  quote <- get(symbol, .env)
  x <- cbind(quote$Bid, Volume=1)
  y <- align.time(to.period(x, unit, fragment,indexAt = 'startof'),n=fragment*60)
  colnames(y) <- c("Open", "High", "Low", "Close","volume")
  return(y)
}

createRDA()
# ts contains 15min OHLC data for given symbol, date range, and RDA data source
ts <- createCustomCandlesticTimeSeries("minutes",15,"2015-01-01","2015-12-31",tick.data.outdir)