1. 技术文章
  2. create an OHLC series from ticker data using R

create an OHLC series from ticker data using R

由 て烟熏妆下的殇ゞ 提交于 2019-11-29 10:42:49
GSee

To illustrate @JoshuaUlrich's comment:

x <- read.csv(header=TRUE, stringsAsFactor=FALSE, 
              text="time,price,volume,
                    7/18/10 0:09,0.04951,20,
                    7/18/10 4:43,0.05941,50.01,
                    7/18/10 18:48,0.0808,5,
                    7/18/10 22:44,0.08585,10,
                    7/18/10 23:00,0.08584,5,
                    7/18/10 23:00,0.08584,5,
                    7/19/10 4:53,0.0909,5,
                    7/19/10 17:24,0.09307,80,
                    7/19/10 18:03,0.08911,100,
                    7/19/10 18:07,0.08752,100,")
# create an xts object
myxts <- xts(x[, 2:3], order.by=as.POSIXct(x[, 1], format='%m/%d/%y %H:%M'))
myxts

myxts
#                       price volume
# 2010-07-18 00:09:00 0.04951  20.00
# 2010-07-18 04:43:00 0.05941  50.01
# 2010-07-18 18:48:00 0.08080   5.00
# 2010-07-18 22:44:00 0.08585  10.00
# 2010-07-18 23:00:00 0.08584   5.00
# 2010-07-18 23:00:00 0.08584   5.00
# 2010-07-19 04:53:00 0.09090   5.00
# 2010-07-19 17:24:00 0.09307  80.00
# 2010-07-19 18:03:00 0.08911 100.00
# 2010-07-19 18:07:00 0.08752 100.00
to.minutes(myxts)
#                     myxts.Open myxts.High myxts.Low myxts.Close myxts.Volume
# 2010-07-18 00:09:00    0.04951    0.04951   0.04951     0.04951        20.00
# 2010-07-18 04:43:00    0.05941    0.05941   0.05941     0.05941        50.01
# 2010-07-18 18:48:00    0.08080    0.08080   0.08080     0.08080         5.00
# 2010-07-18 22:44:00    0.08585    0.08585   0.08585     0.08585        10.00
# 2010-07-18 23:00:00    0.08584    0.08584   0.08584     0.08584        10.00
# 2010-07-19 04:53:00    0.09090    0.09090   0.09090     0.09090         5.00
# 2010-07-19 17:24:00    0.09307    0.09307   0.09307     0.09307        80.00
# 2010-07-19 18:03:00    0.08911    0.08911   0.08911     0.08911       100.00
# 2010-07-19 18:07:00    0.08752    0.08752   0.08752     0.08752       100.00

to.minutes is one of many wrappers for to.period. This is equivalent, but more general:

to.period(myxts, 'minutes', 1)

Azoo series can be reclassed as OHLC with class(data) <- c('zoo', 'OHLC', 'some other class').

From ?quantmod::quantmod.OHLC:

‘quantmod.OHLC’ is actually just a renaming of an object of class ‘zoo’, with the convention of NAME.Open, NAME.High, ... for the column names.

If you don't have the volume column, then there is no code you can write that will add that data. It seems like you just have a series of intraday prices. You can still class these as zoo or xts and do time series analysis. If you want to reduce the resolution of your data, you could always scan over each day and use the functions first, max, min, last to get your O, H, L, C.

from http://r.789695.n4.nabble.com/Convert-tick-data-to-OHLC-td926206.html

ohlc <- function(ttime,tprice,tvolume,fmt) {
    ttime.int <- format(ttime,fmt)
    data.frame(time = ttime[tapply(1:length(ttime),ttime.int,function(x) {head(x,1)})],
    .Open = tapply(tprice,ttime.int,function(x) {head(x,1)}), 
    .High = tapply(tprice,ttime.int,max),
    .Low = tapply(tprice,ttime.int,min),
    .Close = tapply(tprice,ttime.int,function(x) {tail(x,1)}),
    .Volume = tapply(tvolume,ttime.int,function(x) {sum(x)}),
    .Adjusted = tapply(tprice,ttime.int,function(x) {tail(x,1)}))
}
标签
r
finance
xts
易学教程内所有资源均来自网络或用户发布的内容，如有违反法律规定的内容欢迎反馈！
该文章没有解决你所遇到的问题?点击提问,说说你的问题,让更多的人一起探讨吧!