将多个 XTS 对象合并为一个 XTS 对象

Question

我想将几个 xts 对象合并为一个 xts 对象。这样我就可以得到收盘价对象之间的相关矩阵。

下面的代码提取外汇数据

require(xts)

symbols <- c("AUDJPY", "AUDUSD", "CHFJPY", "EURCHF", "EURGBP", "EURJPY",
             "EURUSD", "GBPCHF", "GBPJPY", "GBPUSD", "NZDUSD", "USDCAD",
             "USDCHF", "USDJPY", "XAGUSD", "XAUUSD")

fxhistoricaldata <- function(Symbol, timeframe, download = FALSE, bandwidth) {   

  # setup temp folder
  temp.folder <- tempdir()
  filename <- paste(temp.folder, '/',"fxhistoricaldata_",Symbol ,"_" ,timeframe,".csv", sep='')

  if(download) {
    downloadfile <- paste("http://api.fxhistoricaldata.com/v1/indicators?instruments=" ,Symbol ,"&expression=open,high,low,close&item_count=10000&format=csv&timeframe=" ,timeframe,sep='')
    download.file(downloadfile, filename,  mode = 'wb')
  }

  tempdf <- read.csv(filename)
  colnames(tempdf) <- c("Curr","Date","Open","High","Low","Close")
  tempdf <- tempdf[c("Date","Open","High","Low","Close")]
  result <- xts(tempdf[,-1], order.by=as.POSIXct(tempdf[,1]))

  return(result)
}

AUDJPY <- fxhistoricaldata('AUDJPY' ,'day',download=T,5)
AUDUSD <- fxhistoricaldata('AUDUSD' ,'day',download=T,5)
CHFJPY <- fxhistoricaldata('CHFJPY' ,'day',download=T,5)
EURCHF <- fxhistoricaldata('EURCHF' ,'day',download=T,5)
EURGBP <- fxhistoricaldata('EURGBP' ,'day',download=T,5)
EURJPY <- fxhistoricaldata('EURJPY' ,'day',download=T,5)
EURUSD <- fxhistoricaldata('EURUSD' ,'day',download=T,5)
GBPCHF <- fxhistoricaldata('GBPCHF' ,'day',download=T,5)
GBPJPY <- fxhistoricaldata('GBPJPY' ,'day',download=T,5)
GBPUSD <- fxhistoricaldata('GBPUSD' ,'day',download=T,5)
NZDUSD <- fxhistoricaldata('NZDUSD' ,'day',download=T,5)
USDCAD <- fxhistoricaldata('USDCAD' ,'day',download=T,5)
USDCHF <- fxhistoricaldata('USDCHF' ,'day',download=T,5)
USDJPY <- fxhistoricaldata('USDJPY' ,'day',download=T,5)
XAGUSD <- fxhistoricaldata('XAGUSD' ,'day',download=T,5)
XAUUSD <- fxhistoricaldata('XAUUSD' ,'day',download=T,5)

我想要的结果看起来像这样，收盘价低于代码名称，但对于所有代码名称

          AUDJPY    AUDUSD  
2016-01-01   1.200     1.300
2016-01-02   1.21      1.31

xts 对象之一的示例

Answer 1

考虑构建一个 xts 对象列表，在列名称前加上相应的符号，然后运行 merge.xts:

xtsList <- lapply(symbols, function(s) {
    df <- get(s)
    colnames(df) <- paste0(s, "_", colnames(df))
    return(df)
})

masterxts <- do.call(merge, xtsList)

Answer 2

使用 getSymbols 找到了更好的解决方案。感谢大家的帮助。

require(lubridate)
require(quantmod)


symbols <- c("AUD/JPY",
             "AUD/USD",
             "CHF/JPY",
             "EUR/CHF",
             "EUR/GBP",
             "EUR/JPY",
             "EUR/USD",
             "GBP/CHF",  
             "GBP/JPY",
             "GBP/USD",
             "NZD/USD",
             "USD/CAD",
             "USD/CHF",
             "USD/JPY",
             "XAG/USD",
             "XAU/USD"
)

fixedsymbols <- lapply(symbols, function(x) {
                   gsub("/", "", x)
              })

getSymbols(symbols,src="oanda", from="2014-08-05", to="2017-01-17")

xtsList <- lapply(fixedsymbols, function(s) {
  df <- get(s)
  colnames(df) <- colnames(df)
  return(df)
})

masterxts <- do.call(merge, xtsList)

Answer 3

这可以通过使用 quantmod add-on qmao 轻松完成。以几个股票代码为例，下载数据（或从文件导入数据）为 xts-objects，然后一次性创建一个包含价格或 returns 的对象。假设您想从每日 returns:

创建一个相关矩阵

library(qmao)
tickers <- c('MSFT','AAPL','AMZN')
getsSymbols(tickers, from = '2010-01-01')
# xts-object of daily returns (RF stands for `Return Frame`,PF returns a
# Price Frame)
returns <- RF(tickers, silent = TRUE, type = 'discrete')

> tail(returns)
                    MSFT         AAPL         AMZN
2017-01-10 -0.0003192848  0.001008513 -0.001279876
2017-01-11  0.0091025233  0.005373176  0.003920085
2017-01-12 -0.0091786360 -0.004175365  0.018297408
2017-01-13  0.0014374700 -0.001760998  0.004301657
2017-01-17 -0.0027113556  0.008064508 -0.009080505
2017-01-18 -0.0004797537 -0.000083350 -0.002766377

获取相关矩阵：

> cor(returns,use = 'pairwise.complete.obs')
          MSFT      AAPL      AMZN
MSFT 1.0000000 0.4655617 0.4701170
AAPL 0.4655617 1.0000000 0.4390303
AMZN 0.4701170 0.4390303 1.0000000

看看函数 PF 和 RF 它们非常紧凑且非常有用。

将多个 XTS 对象合并为一个 XTS 对象

Merging Multiple XTS Objects into a single XTS object

r

xts

quantmod