Bollinger Plots are a very good way of providing technical information on plausible Buy or Sell on a particular security. They are based on moving averages and thus are simple to create
However, there are 2 parameters that are inputs to the Bollinger Band
1) The period of days considered for calculating the moving average
Most of the analysts use a 20 day plot, but you can use any period based on the security. e.g. A highly liquid security with high volatility should have a lower period.
The R script can be downloaded here
However, there are 2 parameters that are inputs to the Bollinger Band
1) The period of days considered for calculating the moving average
Most of the analysts use a 20 day plot, but you can use any period based on the security. e.g. A highly liquid security with high volatility should have a lower period.
The R script can be downloaded here
# Bollinger Bands
Ticker = 'AAPL'
URL = paste(c('http://real-chart.finance.yahoo.com/table.csv?s=',Ticker,'&a=01&b=01&c=2015&d=04&e=10&f=2015&g=d&ignore=.csv'),collapse="")
Prices = read.csv(URL)
Prices = Prices[,c(1,5)]
# Simple moving average of a vector of price and the number of days
getMovingAverage = function(dataVector,periodDays,method){
dataVectorOutput = dataVector
lengthofVector = length(dataVector)
for(start in 1:lengthofVector)
{
if(start < periodDays)
{
dataVectorOutput[start] = NA
}
else
{
if(method=="mean") dataVectorOutput[start] = mean(dataVector[start-periodDays:start])
else if(method=="sd") dataVectorOutput[start] = sd(dataVector[start-periodDays:start])
}
}
return(dataVectorOutput)
}
dataVectorOutputMean = getMovingAverage(Prices$Close,20,"mean")
dataVectorOutputSD = getMovingAverage(Prices$Close,20,"sd")
Prices$Middle = dataVectorOutputMean
Prices$Upper = dataVectorOutputMean + dataVectorOutputSD * 2
Prices$Lower = dataVectorOutputMean - dataVectorOutputSD * 2
#Remove all the NULLS
Prices = Prices[!is.na(Prices$Middle),]
# Change the date to something that ggplot will understand
Prices$Date = as.POSIXct(as.character(Prices$Date),"%Y-%m-%d")
# Plot the Bollinger
library(ggplot2)
g = ggplot(Prices,aes(Date,Close,group=1)) + geom_line()
g = g + geom_line(data=Prices,aes(Date,Upper,group="Upper Bollinger",color="Upper Bollinger"),size=1)
g = g + geom_line(data=Prices,aes(Date,Middle,group="Middle Bollinger",color="Middle Bollinger"),size=1)
g = g + geom_line(data=Prices,aes(Date,Lower,group="Lower Bollinger",color="Lower Bollinger"),size=1)
g = g + xlab("Date") + ylab("Prices")
g
A Sample plot for the AAPL Stock was created using the above script
