Question

我正在尝试使用库TTR为所有符号导出技术指标。迭代方法实际上需要花费数小时并消耗大量内存。

是否可以创建函数并按符号对 eod_completewNA_woutRepeats 进行分组并将其应用到每个分组，最终结果是汇总列表（ eod_completewNA_techInd ）？

>

list_symbols是符号名称的字符列表

head(list_symbols)
[1] "ACAD" "ACGL" "ACH"  "ACHC" "ACHN" "ACIW" 

head(tempHolder)

            Date Open High  Low Close Volume
4629  2015-08-24 30.0 32.2 30.0  32.2     20
9876  2015-08-25 33.1 33.7 32.5  33.0    141
15123 2015-08-26 33.0 33.0 33.0  33.0      0
20367 2015-08-27 33.0 33.0 33.0  33.0      0
25609 2015-08-28 35.2 35.2 34.8  34.8    440
30857 2015-08-31 34.8 34.8 34.8  34.8      0

昂贵的操作

for(lister in list_symbols)
{
  tempHolder <- c()
  tempHolder <- eod_completewNA_woutRepeats[which(eod_completewNA_woutRepeats$symbol==lister),,drop=F][,-2]
  colnames(tempHolder) <- c("Date","Open","High","Low","Close","Volume")
  #

  #https://www.oipapio.com/question-12219593
  #rownames(tempHolder) <- tempHolder$date 

  bbands <- c()
  adx <- c()
  ema <- c()
  sma <- c()
  macd <- c()
  rsi <- c()
  stochOsc <- c()

  #ARK breaks this with too many values at the same value

  bbands <- BBands( tempHolder[,c("High","Low","Close")] )
  adx <- ADX( tempHolder[,c("High","Low","Close")] )
  ema <- data.frame(EMA(tempHolder[,"Close"], n=20)[,drop=FALSE])
  sma <- data.frame(SMA(tempHolder[,"Close"], n=20)[,drop=FALSE])

  # MACD
  macd <- MACD( tempHolder[,"Close"] )

  # RSI
  rsi <- RSI(tempHolder[,"Close"])

  # Stochastics
  stochOsc <- stoch(tempHolder[,c("High","Low","Close")])

  View(tempHolder$Date)
  rownames(tempHolder) <- tempHolder$Date

  eod <<- tempHolder[which(tempHolder$Date=="2016-10-14"),,drop=F]
  xts_holder <- as.xts(tempHolder)

  nrow(tempHolder)

  tech_ind <- cbind(lister,tempHolder,bbands,adx,ema,sma,macd,rsi,stochOsc)

  colnames(tech_ind)[1] <- "Symbol"

  if(is.null(eod_completewNA_techInd))
  {
    eod_completewNA_techInd <- tech_ind
  }
  if(!is.null(eod_completewNA_techInd))
  {
    colnames(tech_ind)
    eod_completewNA_techInd <- rbind(eod_completewNA_techInd,tech_ind)

  }
  #print(nrow(eod_completewNA_techInd))
}

我正在绑定单个结果：

tech_ind <- cbind(lister,tempHolder,bbands,adx,ema,sma,macd,rsi,stochOsc)

然后重新绑定以创建聚合

eod_completewNA_techInd <- rbind(eod_completewNA_techInd,tech_ind)

附录

head(eod_completewNA_woutRepeats)
        date symbol    open    high     low   close  volume
1 2015-08-24   ACAD 33.7600 35.8300 32.2300 33.6000 1474700
3 2015-08-24   ACGL 22.6667 22.7233 21.4267 22.3933 2314200
4 2015-08-24    ACH  7.5600  7.9200  7.5400  7.7200  260300
5 2015-08-24   ACHC 69.0900 70.8800 58.7000 69.7100 1823400
6 2015-08-24   ACHN  6.9800  7.2500  6.7100  7.2500 4556400
8 2015-08-24   ACIW 20.9500 21.8600 20.4500 20.9400  916300

减少昂贵的迭代操作，按列分组，然后将功能应用于过滤后的分组并生成附加数据。

0 个答案: