In this episode, I'm going to show you the results of our backtesting analysis on the Stochastics Indicator and I think you'll find it extremely useful whether you've used it before to trade or if this is your first time looking it up.

Unlike the results we saw in Show 41 of the podcast, today's mini-case study did see a positive correlation between win rate and overall net profitability of the indicator after making a small change to the way we generated signals.

As we've been trying to prove with case studies on the Simple Moving Average, Absolute Price Oscillator and today with Stochastics; there are clearly winners and losers that we found as part of our 20-year technical analysis research report.

About the Stochastics Indicator (STO)?

The Stochastic Indicator is based on the premise that if stock prices are increasing, then the closing prices tend to be near the upper end of the range. Conversely, in downtrends, the closing price tends to be near the lower end of the range. Therefore, the central purpose of this indicator is to assess where the current price is located in relation to the price range of the last few days. Though different variations of stochastics occur from fast to slow, for the purposes of our research report SIGNALS, we used the Full Stochastics.

Full Stochastics as we backtested is made up of three lines, always oscillating in a range from 0 to 100. The primary %K fast line  (14 day) shows the ratio of differences between current close and lowest price and between highest and lowest prices. The %D slow line is a simple moving average (3 day) of %K fast line's values. Finally, we add the %D smoothing line, which is a simple moving average (3 day) of %D slow line's values. This signal increases in reliability if the crossover occurs while the lines are in the oversold or the overbought territory.

As part of our research, we tested 2 major classes of signals with Stochastics. The first grouping was just purely based on the %K line crossing above or below the %D line. The second grouping also overlayed the requirement that this cross had to occur in pre-defined overbought or oversold zones. The first 20 of which are visible in the image below taken from page 42 of the Appendix. You'll notice that simply adding the overbought/oversold zone requirement to the backtest resulted in the win rate more than doubling over the testing period and the net overall profit turning positive on average.

Again like we saw with some of the previous indicators we've revealed (including the Simple Moving Average and Absolute Price Oscillator) the Stochastics indicator still doesn't create the opportunity to make money long-term with its use.

Sure the win rate is high but long-term even the most optimal settings produced annual CAGR of around 1% per year which dramatically underperforms the benchmark SPY index over the 20-year period.

Pick up your copy of SIGNALS today and finally see which technical analysis indicators you should be using. If you have any questions at all please add them in the comment section below and I'll make sure to personally respond to each and every one of them this week.