Trading Strategies Revealed – “Moving Average Crossover” review

Trend following trading strategy “Moving Average Corssover” is a strategy that uses 3 moving averages to identify the crossover point and Parabolic SAR indicator for trend confirmation.

How to trade with Moving Averages?

A trader should open a long trade when EMA(10) crosses EMA(25) and EMA(50) upwards and Parabolic SAR is below the price (signalling long). A short position should be opened when EMA(10) crosses EMA(25) and EMA(50) downwards and Parabolic SAR is above the price (signalling short).

An exit from a position is executed when the price crosses back downwards/upwards through all 3 EMA’s on the chart. The strategy doesn’t use any take take profit level.

Which indicators best complement the Moving Average?

According to the strategy, one of the best indicator that can used together with Moving Average is Parabolic SAR. In the strategy it is used to confirm the overall trend and so to filter out false MA crossovers.

Based on analysis that is presented further on in the article, other indicators that can be successfully used in combination with Moving Average are ADX, Stochastic and RVI. All these help to filter even more false entry signals and to make the strategy much more profitable.

Initial back-test

To run a back-test we have coded a complete Moving Average Crossover trading strategy as a MetaTrader 4 Expert Advisor. During preliminary analysis we have identified that the best time frame for Moving Average Crossover trading strategy is 1 hour (H1). We have run a back-test of Moving Average Crossover strategy standart Moving Average Indicator to define the trend direction and cross point. 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 2009.01.01-2019.28. using Every Tick modelling on EURUSD-H1, using 1:15 leverage, without reinvestment, assuming spread equals 10 ticks. These are the main parameters of Moving Average Crossover trading strategy performance at its non-optimized state:

ROI# of tradesWinning ratioMax. drawdown
-5.72%183734.52%88.52%

Optimization

Moving Average Crossover 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 Fibonacci Retracement trading strategy up tp 30% reducing it’s drawdown in 6.5 times:

  1. Most trades that were opened at a higher value of ADX were losing when trading “Moving Average Crossover” during 2009 – 2019.  “Moving Average Crossover” is a trend following trading strategy while ADX shows the power of a trend. At a higher value of ADX the probability that the trend will reverse is higher. (ROI increase -5% -> 15%, Drawdown reduction 80% ->39%)
  2. Most Sell trades that were opened at a low Stochastic were losing when trading “Moving Average Crossover” during 2009 – 2019. Stochastic shows overbought and oversold zones and it looks unreasonable to sell when market is oversold. (ROI increase -5% -> 24%, Drawdown reduction 80% ->27%)
  3. Trades that were opened at boundary values of RVI brought more losses when trading “Moving Average Crossover” during 2009 – 2019. RVI measures the power of a trend and it is commonly suggested to avoid opening trades at its boundary values. (ROI increase -5% -> 4%, Drawdown reduction 80% ->51%)

Optimization results

We have analysed data received from a test of Moving Average Crossover trading strategy during 2009 — 2019 years and applied some filters such as Stochastic, ADX, RVI. As a result, the profitability of the strategy has increased from -5.07% up to 30.05% and it’s drawdown has reduced from 88.62% to 13.48% using leverage 1:15.

Post-optimization back-test

Reducing the drawdown more than 6.5 times has allowed us to increase the leverage that can be used while trading this strategy up to 1:40, which in turn, has resulted in annualized ROI increase up to 80.26%!

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 4% risk per trade:

ROI# of tradesWinning ratioMax. drawdown
522%49040%33.8%

Analyze your trading strategy!

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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.