Trading Strategies Revealed – “Stochastic Divergence” review
Trend reversal trading strategy “Stochastic Divergence” is a popular Stochastic strategy that uses divergences between Stochastic Oscillator and price to predict a change (reversal) in market trend. It is designed mainly for Forex and can be used on all currency pairs on any time frame. Stochastic divergence trading strategy has appeared to be a profitable Forex trading strategy.
How to trade Stochastic Divergence?
A trader should open a buy trade once the following pattern is detected on the chart: the price makes lower lows, while Stochastic Oscillator makes higher lows. This usually means that the trend has started to exhaust and a reversal may happen shortly. The opposite pattern signals about selling possibility – price makes higher highs, while Stochastic Oscillator makes lower highs. An example of divergence and a sell trade is shown on the screenshot below:
Stochastic divergence meaning
Stochastic divergence means that price momentum has started to slow down and signals about soon trend change (either a consolidation or a trend reversal). For example, when the price still moves up after a long bullish run making higher highs while Stochastic Oscillator starts making lower highs – this means that the price momentum slows down and signals about possible trend reversal.
Stochastic settings for divergence
To identify a Stochastic Divergence you should use a divergence indicator that is developed specifically for such task. Its complexity depends on many factors and on which settings (parameters) you want to apply to detect a divergence. Particularly, the following questions should be asked and answered while configuring your Stochastic divergence settings:
- What is the maximum and minimum time range for a divergence that you want to detect
- Which type of divergence do you want to identify – hidden or classic
- Whether or not you want to detect divergences in which price and Stochastic vertex are shifted from each other
- Which type of price and Stochastic swing may be considered as a valid vertex. Specifically how many higher highs/lower lows should be there between a price/Stochastic swing to consider it as a valid vertex for divergence calculation
- Whether or not it is allowed for a price/Stochastic to break a divergence line between 2 divergence vertexes used for the divergence calculation
- Whether or not a divergence is allowed to be calculated between 2 vertexes that are not next to each other (means they have other price/Stochastic vertexes in-between)
- etc.
Initial back-test
We have run a back-test trading both classical and hidden divergences using a most basic Stochastic divergence indicator. For our test as a trade exit rule we have used a Trailing Stop of 30 pips which is launched after a trade has started and is modified each new 1 pip of profit. From our point of view, such approach allows to maximize profit and minimize drawdown.
We have run the test for 2010.01.01-2021.01.24 using Control Points modelling on EURUSD-H1, using leverage 1:10, without reinvestment, assuming spread equals 10 ticks. These are the main parameters of Stochastic divergence trading strategy performance at its non-optimized state:
| ROI | # of trades | Winning ratio | Max. drawdown |
| 14.67% | 6689 | 36.79% | 19.03% |
Trading data analysis
After running the initial test of a simple non-filtered strategy we perform a trading data analysis that allows to identify possible filters to use to make the strategy more profitable reducing the drawdown simultaneously. The following charts may give some possible insights on which filters to apply (time sessions, day of week limitation, trend strength threshold, overbought/oversold conditions, volatility range) to turn this strategy profitable should you decide to use this strategy in your investment portfolio:
Optimization
Stochastic Divergence trading strategy can be used with other indicators to filter out losing trades and make entry signals more accurate. After analysing trading data we have found the following insights which have helped us to increase the profitability of Opening Range Brekout trading strategy and reduce it’s drawdown
- Trades that were opened at a too low and at a too high values of ADX have appeared to bring more losses when trading “Stochastic Divergence” trading strategy during 2009 – 2020. ADX shows the power of the current trend. It is more reasonable to take trades at the trend start.
(ROI increase 1.5% -> 4.8%, Drawdown reduction 19.47% -> 9.63%) - The majority of trades that were opened at a too low value of Stochastic and the majority of trades that were opened at a too high value of Stochastic were losing when trading “Stochastic Divergence” trading strategy during 2009 – 2020. It is risky to take trades in the overbought and oversold zones.
(ROI increase 1.5% -> 7.9%, Drawdown reduction 19.47% -> 7.95%) - Most of the trades that were opened at a too high and a too low values of RSI were losing when trading “Stochastic Divergence” trading strategy during 2009 – 2020. RSI measures the magnitude of most recent price changes to evaluate the overbought and oversold zones.
(ROI increase 1.5% -> 7.5%, Drawdown reduction 19.47% -> 6.54%)
Optimization results
We have analysed data received from a test of Stochastic Divergence trading strategy during 2009 — 2019 years and applied some filters such as Stochastic, ADX and RSI. As a result, the profitability of the strategy has increased from 14.67% up to 7.2% and it’s drawdown has reduced from 19.47% to 4.83% using leverage 1:10.
Post-optimization back-test
Reducing the drawdown more than 4 times has allowed us to increase the leverage that can be used while trading this strategy up to 1:35, which in turn, has resulted in annualized ROI increase up to 252.23%!
Reducing the drawdown has also allowed us to use risk based lot calculation. Below you can see the back-test results using $10,000 initial balance and 10% risk per trade:
| ROI | # of trades | Winning ratio | Max. drawdown |
| 54540% | 1371 | 42,74% | 12,42% |
Analyze your trading strategy!
If you have a trading strategy that you want to analyse, optimize and increase its profitability (or even turn it from losing into a profitable Forex trading strategy) – feel free to contact us! Our trading data analysis team will respond to you within 24 hours clarifying all the details needed.
Custom Programming
Our company specializes on automated trading systems and trading indicators development for the most popular trading platforms, such as MetaTrader 4/5, NinjaTrader 7/8, TradingView, TradeStation and cTrader.
If you need your own automated trading software designed based on your individual requirements, make a request for a free consultation with our team of professional programmers and find out the cost and terms of your project development.
Try our Multi-Divergence MT4 Indicator
One Subscription For All Indicators. View All Products.
MT4 Divergence Indicator is used to identify a common known trading concept (divergence) across different currencies, timeframes and indicators. It includes divergences, calculated based on RSI, Stochastic, MACD, On Balance Volume (OBV) and Awesome Oscillator (AO) indicators. The main concept of a divergence states that a divergence signals about trend continuation or reversal in advance allowing you to use this information in your trading decisions. A divergence is a situation on the market when values of an indicator increase/decrease while price of the trading instrument decreases/increases (so indicator and price diverge on the chart).
Disclaimer: Hypothetical or Simulated performance results have certain limitations, unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not been executed, the results may have under-or-over compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profit or losses similar to those shown. Past performance is not necessarily indicative of future results. The customer is responsible for using the product at his or her own risk and “Nordman Algorithms” is not responsible for any possible losses caused by use of the product, including but not limited to losses.
