Question

我已经建立了以下模型，只回测间谍。我的问题是我想将这种交易策略应用于多个代码（例如qqq和间谍）。

我该怎么做？见下文：

getSymbols("spy",from ="2000-01-01", to="2015-01-01")
SPY<-adjustOHLC(SPY)
rsi <- RSI(Cl(SPY),2)
smashort<-SMA(Cl(SPY),10)
smalong<-SMA(Cl(SPY),200)
adx<-ADX(HLC(SPY),10)
adx<-adx[,4]
close<-Cl(SPY)

signal<-ifelse(rsi<15 & close<smashort & smalong<close &adx>27,1,0)
for(i in 1:nrow(signal))
{signal<-ifelse(lag(signal)==1 & close<smashort,1,ifelse(rsi<15 & close<smashort & smalong<close & adx>27,1,0))}
signal<-lag(signal,1)
signal[is.na(signal)] <- 0
ret <- ROC(Cl(SPY))
ret[1] <- 0
equity<-exp(cumsum(ret*signal))
plot(equity)

请参阅下面的多重代码版本：

＆＃13;

stockData <- new.env() #Make a new environment for quantmod to store data in
symbols = c("TLT", "USO")
getSymbols(symbols, src='yahoo',from = "2016-9-01",to = Sys.Date())
for(symbol in symbols){
  assign(symbol,adjustOHLC(get(symbol, pos=.GlobalEnv), symbol.name=symbol, 
                           adjust=c("split"), use.Adjusted=FALSE))
}

x <- list()
for (i in 1:length(symbols)) {
  x[[i]] <- get(symbols[i], pos=stockData)  # get data from stockData environment 
  x[[i]]$sma <-SMA(Cl(x[[i]]),10)
  x[[i]]$rsi <-RSI(Cl(x[[i]]),2)
  x[[i]]$close <-(Cl(x[[i]]))
  x[[i]]$signal<-ifelse(x[[i]]$rsi<15 & x[[i]]$close<x[[i]]$sma,1,0)
	
for(i in length(x[[i]]$signal))
{x[[i]]$signal<-ifelse(lag(x[[i]]$signal)==1 & x[[i]]$close<x[[i]]$sma,1,ifelse(x[[i]]$rsi<15 & x[[i]]$close<x[[i]]$sma,1,0))}


}

＆＃13;

Answer 1

使用quantstrat可以轻松完成您想要做的事情。请参阅包中的demo文件夹（请参阅demo文件夹中的RSI策略），或在线查看有关它的多个教程。

devtools::install_github("braverock/quantstrat")

在您的代码段中，当您尝试循环向量操作时，此部分没有意义：

for(i in length(x[[i]]$signal))
{x[[i]]$signal<-ifelse(lag(x[[i]]$signal)==1 & x[[i]]$close<x[[i]]$sma,1,ifelse(x[[i]]$rsi<15 & x[[i]]$close<x[[i]]$sma,1,0))}

同样for(i in length(x[[i]]$signal))只返回i =向量的长度。也许你想要像for(i in 1:NROW(x[[i]]$signal))这样的东西。

看起来你想要这样的东西：

x <- list()
for (i in 1:length(symbols)) {
    x[[i]] <- get(symbols[i], pos=stockData)  # get data from stockData environment 
    x[[i]]$sma <-SMA(Cl(x[[i]]),10)
    x[[i]]$rsi <-RSI(Cl(x[[i]]),2)
    x[[i]]$close <-(Cl(x[[i]]))
    x[[i]]$signal<-ifelse(x[[i]]$rsi<15 & x[[i]]$close<x[[i]]$sma,1,0)
    x[[i]]$signal2 <-ifelse(lag.xts(x[[i]]$signal) ==1 & x[[i]]$close<x[[i]]$sma,1,ifelse(x[[i]]$rsi<15 & x[[i]]$close<x[[i]]$sma,1,0))
}

Answer 2

谢谢FX Quant Trader。我找到了另一个解决方案。见attache`

＆＃13;

x <- list() 
for (i in 1:length(symbols)) {
  x[[i]] <- get(symbols[i], pos=stockData)  # get data from stockData environment 
  x[[i]]$sma <-SMA(Cl(x[[i]]),10)
  x[[i]]$rsi <-RSI(Cl(x[[i]]),2)
  x[[i]]$close <-(Cl(x[[i]]))
  x[[i]]$signal<-ifelse(x[[i]]$rsi<10 & x[[i]]$close<x[[i]]$sma,1,0)
  for(k in 1:nrow(x[[i]]$signal))
{x[[i]]$signal<-ifelse(lag(x[[i]]$signal)==1 & x[[i]]$close<x[[i]]$sma,1,ifelse(x[[i]]$rsi<10 & x[[i]]$close<x[[i]]$sma,1,0))}

x[[i]]$signal<-lag(x[[i]]$signal,1)
x[[i]]$signal[is.na(x[[i]]$signal)] <- 0

x[[i]]$ret <- ROC(Cl(x[[i]]$close))
x[[i]]$ret[1] <- 0

x[[i]]$equity<-exp(cumsum(ret*x[[i]]$signal))
plot(x[[i]]$equity)
}

＆＃13;

`

多个代码回测

2 个答案: