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.

DISCLAIMER: None of the below is intended to be considered as any kind of investment advice. All examples serve as illustrative material only.

For an implementation of the stochastic oscillator (STO) please see the R code below. The function `STO`

calculates the oscillator values, which may afterwards be plotted with help of the function `plotSTO`

. Note that both function use tools introduced in my article Implementing Technical Indicators: Tools.

```
#
# STOCHASTIC OSCILLATOR
#
source("Indicators/IndicatorHelperFunctions.R")
source("Indicators/IndicatorPlottingFunctions.R")
# indicator calculation
STO = function(v_high, v_low, v_close, i_window_k=10, i_window_d=3)
{
checkVectors(v_high, v_low, v_close)
checkWindow(v_close, i_window_k)
checkWindow(v_close, i_window_d)
# %K indicator
v_running_low = runningMin(v_low, i_window_k)
v_running_high = runningMax(v_high, i_window_k)
v_percent_k = 100 * (v_close - v_running_low) / (v_running_high - v_running_low)
# %D indicator
v_percent_d = movingAverage(v_percent_k, i_window_d)
df_sto = data.frame(v_percent_d, v_high, v_low, v_close)
colnames(df_sto) = c("STO", "High", "Low", "Close")
return(df_sto)
}
# indicator plotting
plotSTO = function(v_date, df_sto, s_path)
{
isDataFrame(df_sto)
dateMatch(v_date, df_sto)
v_colors = c("black", "blue", "purple", "green")
v_legend = c("STO", "High", "Low", "Close")
plotIndicator2(v_date, df_sto$STO, df_sto[, -1], v_colors, v_legend, s_path)
}
```