根据布林带筛选股票

Question

我正在尝试根据布林带筛选列表中的几只股票。

假设这是列表：c("AMZN","GOOG","TSLA","AAPL")

这就是我尝试启动代码的方式：

stock.list = c("AMZN","GOOG","TSLA","AAPL")
res = list()
for(ss in stock.list) {
stock.data = na.omit(getSymbols(ss, from="1900-01-01", auto.assign=F))
}

我不确定如何进一步进行，但我想将列表中的股票过滤为 select 仅低于 50 天平均值的第二个标准差的股票：addBBands(n=50, sd=2)

我该怎么做？

Answer 1

将收盘价提取到单个 xts 数据框，并使用 zoo 包中的 rollapply 来计算波段。然后就一帆风顺了。

library(quantmod)

stock.list = c("AMZN","GOOG","TSLA","AAPL")

res = list()

# Modifying your loop to store closing prices in a separate data frame
df = xts()
for(ss in stock.list) {
  res[[ss]] <-na.omit(getSymbols(ss, from="1900-01-01", auto.assign=F))
  names(res[[ss]]) <- c("Open", "High", "Low", "Close", "Volume", "Adjusted")
  df <- cbind(df, res[[ss]][, "Close"])
}

names(df) <- stock.list


# Calculate standard deviation and moving average
sigma <- rollapply(df,
                   width = 50,
                   FUN = sd,
                   by.column = TRUE,
                   align = "right",
                   fill = NA)

mu <- rollapply(df,
                width = 50,
                FUN = mean,
                by.column = TRUE,
                align = "right",
                fill = NA)


# Calculate bollinger bands
upperBand <- mu + 1.96 * sigma
lowerBand <- mu - 1.96 * sigma

# Detect signals
breachedUpper <- df > upperBand
breachedLower <- df < lowerBand

# AAPL has breached its upper band
tail(breachedUpper)

根据布林带筛选股票

Screen stocks based on Bollinger bands

r

quantmod