In this part of my series Implementing Technical Indicators I provide you with the R implementation of another technical indicator. Please refer to my article Technical Indicators: An Introduction for an overview of the concept of technical indicators and for details on the particular one presented in this article.
For an implementation of the Bollinger bands (BOL) trading strategy please see the R code below. The function BOL calculates both indicator values and resulting trading signals, which may afterwards be plotted with help of the function plotBOL. Note that both function use tools introduced in my article Implementing Technical Indicators: Tools.
#
# BOLLINGER BANDS
#
# long / short indicator
#
source("Indicators/IndicatorHelperFunctions.R")
source("Indicators/IndicatorPlottingFunctions.R")
# indicator calculation
BOL = function(v_values, i_window=20, d_leverage=2)
{
checkWindow(v_values, i_window)
i_length = length(v_values)
v_ma = movingAverage(v_values, i_window)
v_sdv = standardDeviation(v_values, i_window)
v_upper_band = v_ma + d_leverage * v_sdv
v_lower_band = v_ma - d_leverage * v_sdv
v_signals = rep(0, i_length)
if (v_values[1] >= v_ma[2]) {
v_signals[1] = 1
} else {
v_signals[1] = -1
}
for (i in 2 : i_length) {
if (v_values[i] >= v_upper_band[i]) {
v_signals[i] = 1
} else if (v_values[i] <= v_lower_band[i]) {
v_signals[i] = -1
} else {
v_signals[i] = v_signals[i-1]
}
}
df_bol = data.frame(v_signals, v_values, v_ma, v_upper_band, v_lower_band)
colnames(df_bol) = c("Signal", "Price", "MA", "uBand", "lBand")
return(df_bol)
}
# indicator plotting
plotBOL = function(v_date, df_bol, s_path)
{
isDataFrame(df_bol)
dateMatch(v_date, df_bol)
v_colors = c("black", "blue", "purple", "purple")
v_legend = c("Price", "MA", "Upper Band", "Lower Band")
plotIndicator(v_date, df_bol$Signal, df_bol[, -1], v_colors, v_legend, s_path)
}