getSymbols-With-Time.r

# this gist anticipates following:
# existence of GBPJPY.csv with OHLC series in g:\TickData directory
# time series having date time in format %d.%m.%Y %H:%M:%S

# update above assumptions in accordance with your dataset

library(blotter)

symbol = "GBPJPY"

dtfun <- function(x) as.POSIXct(strptime(x, format = "%d.%m.%Y %H:%M:%S", tz = "UTC"))
pair <- as.xts(read.zoo(file = paste0("g:/tickdata/",symbol,".csv"), header=T, sep=',', FUN=dtfun))
assign(symbol, pair, .GlobalEnv)


head(GBPJPY)

#                    Open    High     Low   Close      Volume
#2008-01-01 00:00:00 221.765 221.895 221.666 221.780 74334296875
#2008-01-01 01:00:00 221.803 221.905 221.696 221.791 58417699219
#2008-01-01 02:00:00 221.841 221.863 221.717 221.777  1528300049
#2008-01-01 03:00:00 221.802 221.863 221.742 221.800  1401199951
#2008-01-01 04:00:00 221.818 221.870 221.691 221.803  1499199951
#2008-01-01 05:00:00 221.783 221.858 221.707 221.800  1385599976

summary(GBPJPY)

#   Index                          Open            High            Low            Close           Volume         
# Min.   :2008-01-01 00:00:00   Min.   :117.0   Min.   :117.1   Min.   :116.8   Min.   :116.9   Min.   :0.000e+00  
# 1st Qu.:2009-12-16 05:45:00   1st Qu.:131.8   1st Qu.:132.0   1st Qu.:131.7   1st Qu.:131.8   1st Qu.:0.000e+00  
# Median :2011-12-01 11:30:00   Median :148.4   Median :148.6   Median :148.2   Median :148.4   Median :4.776e+09  
# Mean   :2011-12-01 11:29:46   Mean   :154.5   Mean   :154.6   Mean   :154.3   Mean   :154.5   Mean   :6.725e+09  
# 3rd Qu.:2013-11-15 17:15:00   3rd Qu.:173.4   3rd Qu.:173.5   3rd Qu.:173.3   3rd Qu.:173.4   3rd Qu.:9.356e+09  
# Max.   :2015-10-31 22:00:00   Max.   :222.2   Max.   :222.7   Max.   :222.1   Max.   :222.2   Max.   :4.113e+11