在R错误中调整股票分割？

我有一个包含收盘价的日内数据集，我想根据股票分割调整股票价格。我发现quantmod包中的adjustOHLC几乎可以有效地工作

这里是我的数据集中许多未调整的代码之一，名为：AGII

datset <- structure(c(52.15, 52.17, 52.135, 52.155, 52.1, 52.1, 52.23, 
52.145, 52.185, 52.15, 52.215, 52.185, 52.15, 52.32, 52.415, 
52.4, 52.41, 52.42, 52.51, 52.39, 52.42, 52.02, 52, 52.12, 52.12, 
52.15, 52.06, 52.13, 52.13, 52.02, 52.02, 52.12, 52.06, 52.06, 
52, 52.025, 51.97, 51.96, 52.02, 52, 52.005, 52, 52.09, 52.17, 
52.15, 52.47, 52.51, 52.76, 52.58, 52.73, 52.65, 52.75, 52.7295, 
52.56, 52.5, 52.5, 52.46, 52.43, 52.3, 52.467, 52.48, 52.48, 
52.53, 52.657, 52.633, 52.55, 52.565, 52.56, 52.57, 52.735, 52.71, 
52.72, 52.55, 52.55, 52.34, 52.54, 52.46, 52.54, 52.45, 52.74, 
52.67, 52.8, 52.61, 52.63, 52.74, 52.78, 52.78, 52.59, 52.79, 
52.81, 52.81, 52.725, 52.69, 52.6, 52.675, 52.58, 52.67, 52.67, 
47.63, 47.57, 47.59, 47.57, 47.73, 47.64, 47.64, 47.64, 47.75, 
47.74, 47.78, 47.78, 47.83, 47.86, 47.99, 47.94, 47.94, 48, 47.97, 
47.97, 48.01, 47.88, 47.86, 47.96, 47.93, 47.98, 47.98, 48.06, 
48.01, 47.96, 47.93, 47.93, 48.02, 48.01, 48.04, 48.06, 48.12, 
48.1599, 48.1599, 48.18, 48.15, 48.19, 48.16, 48.11, 48.115, 
48.1, 48.08, 48.07, 48.04, 48.02, 47.995, 47.91), .indexTZ = "", class = c("xts", 
"zoo"), .indexCLASS = c("POSIXct", "POSIXt"), tclass = c("POSIXct", 
"POSIXt"), tzone = "", index = structure(c(1424481300, 1424482200, 
1424483100, 1424484000, 1424484900, 1424485800, 1424486700, 1424487600, 
1424488500, 1424489400, 1424490300, 1424491200, 1424492100, 1424493000, 
1424493900, 1424494800, 1424495700, 1424496600, 1424497500, 1424498400, 
1424735100, 1424736000, 1424736900, 1424737800, 1424738700, 1424739600, 
1424740500, 1424741400, 1424742300, 1424743200, 1424744100, 1424745000, 
1424745900, 1424746800, 1424747700, 1424748600, 1424749500, 1424750400, 
1424751300, 1424752200, 1424753100, 1424754000, 1424754900, 1424755800, 
1424756700, 1424757600, 1424821500, 1424822400, 1424823300, 1424824200, 
1424825100, 1424826000, 1424826900, 1424827800, 1424828700, 1424829600, 
1424830500, 1424831400, 1424832300, 1424833200, 1424834100, 1424835000, 
1424835900, 1424836800, 1424837700, 1424838600, 1424839500, 1424840400, 
1424841300, 1424842200, 1424843100, 1424844000, 1424907900, 1424908800, 
1424909700, 1424910600, 1424911500, 1424912400, 1424913300, 1424914200, 
1424915100, 1424916000, 1424916900, 1424917800, 1424918700, 1424919600, 
1424920500, 1424921400, 1424922300, 1424923200, 1424924100, 1424925000, 
1424925900, 1424926800, 1424927700, 1424928600, 1424929500, 1424930400, 
1424994300, 1424995200, 1424996100, 1424997000, 1424997900, 1424998800, 
1424999700, 1425000600, 1425001500, 1425002400, 1425003300, 1425004200, 
1425005100, 1425006000, 1425006900, 1425007800, 1425008700, 1425009600, 
1425010500, 1425011400, 1425012300, 1425013200, 1425014100, 1425015000, 
1425015900, 1425016800, 1425080700, 1425081600, 1425082500, 1425083400, 
1425084300, 1425085200, 1425086100, 1425087000, 1425087900, 1425088800, 
1425089700, 1425090600, 1425091500, 1425092400, 1425093300, 1425094200, 
1425095100, 1425096000, 1425096900, 1425097800, 1425098700, 1425099600, 
1425100500, 1425101400, 1425102300, 1425103200), tzone = "", tclass = c("POSIXct", 
"POSIXt")), .Dim = c(150L, 1L), .Dimnames = list(NULL, "AGII"))

由于这是一个更大数据集的一部分&我需要调整许多标记，因此我编写了以下循环：

library(quantmod)
dataset <- xts()
NOMS <- names(datset)

for(i in 1:length(NOMS)) {
  NOMS[i]-> symbol
  # Symbol might not be found so I try "skip" the ticker with "try()"
  tryit <- try(adjustOHLC(to.period(datset[,symbol],"minutes",15), adjust=c("split"), symbol.name=symbol))
  if(inherits(tryit, "try-error")){
    ADJ = datset[,symbol]
    colnames(ADJ)<- symbol
    dataset <- merge.xts(dataset,ADJ)
  } else {
    # If ticker is found, then adjust it
    ADJ = adjustOHLC(to.period(datset[,symbol],"minutes",15), adjust=c("split"), symbol.name=symbol)
    ADJ <- Cl(ADJ)
    colnames(ADJ)<- symbol
    dataset <- merge.xts(dataset,ADJ)
  }
}

---

如何在不被夸大的情况下获得适当的分割？

首先，这些功能设计用于处理每日数据，而不是日内数据

其次，问题是日期对象被认为是UTC午夜，而您的datset对象没有时区。因此，调整算法认为分割发生在UTC午夜的任何时间，而UTC恰好在系统的时区内

s <- getSplits(symbol)
indexTZ(s) <- indexTZ(x)       # ensure the objects have the same timezone
index(s) <- index(s)           # force an index recalculation
indexClass(s) <- "POSIXct"     # convert index to POSIXct
r <- adjRatios(s, NA, datset)  # calculate adjustment ratios
y <- adjustOHLC(x, ratio=r$Split, symbol.name=symbol)
chartSeries(Cl(y))

解决方法是在将分割数据的时区调整为与本地时区相同后，自己完成这项工作

s <- getSplits(symbol)
indexTZ(s) <- indexTZ(x)       # ensure the objects have the same timezone
index(s) <- index(s)           # force an index recalculation
indexClass(s) <- "POSIXct"     # convert index to POSIXct
r <- adjRatios(s, NA, datset)  # calculate adjustment ratios
y <- adjustOHLC(x, ratio=r$Split, symbol.name=symbol)
chartSeries(Cl(y))

请注意，您仍然可以看到调整后的数据出现峰值，因为分割可能在2015年2月26日午夜不适用。你可以通过滞后调整比率来解决这个问题

r2 <- na.locf(lag(r), fromLast=TRUE)
y2 <- adjustOHLC(x, ratio=r2$Split, symbol.name=symbol)
chartSeries(Cl(y2))

---

这里有一个函数可以对日内数据进行雅虎风格的股息/分割调整：@GSee谢谢这个函数非常棒@GSee qmao软件包是否与mac osx Yosemite和R版本3.1.2兼容？我尝试过install.packagesqmao&也尝试过install.packages~/Desktop/R/qmao_1.6.10.tar.gz，repos=NULL，type=source，但运气不好…：是的，但它不在CRAN上，所以您需要使用install.packagesqmao，repos=http://r-forge.r-project.org 或者devtools：：安装\u githubgsee/qmao，或者您也可以。qmao有许多依赖项需要安装first@GSee谢谢，我现在可以安装qmao了，但我需要先加载gdata、Shining和pander。。。qmao太棒了！

r2 <- na.locf(lag(r), fromLast=TRUE)
y2 <- adjustOHLC(x, ratio=r2$Split, symbol.name=symbol)
chartSeries(Cl(y2))