"Bounce from the simple moving average" strategy

FX Helper
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Joined: Mon Apr 01, 2013 3:55 am

"Bounce from the simple moving average" strategy

#1 Postby FX Helper » Thu Apr 07, 2016 4:47 am

Why this strategy can be interesting?
1. The strategy is extremely simple and therefore can be assimilated and used by a trader with any level of trading experience (or even without such one)
2. The strategy is based on the assumption that when a significant momentum appears on the chart, the price is more likely to continue to move in the same direction, rather than reverse.

If you see a car racing with a high speed, then surely there is a chance that it will slow down very quickly, turn around and accelerate rapidly in the reverse direction. However, most likely it will continue to move in the same direction at least for some time, even if the driver has already begun to slow down and get ready for a reversal.

Strategy's description
There is just one indicator required, which is the simple moving average (SMA).

Conditions for opening sell orders:
1. The price moves away from the moving average for a pre-defined number of pips down (the sag)
Bounce1.png (79.97 KiB) Viewed 8916 times

2. This sag should be formed at least with four candlesticks

Bounce2.png (61.24 KiB) Viewed 8916 times

3. The price returns back to the moving average
Bounce3.png (58.63 KiB) Viewed 8916 times

4. The market sell order is opened when the price reaches the moving average

Conditions for opening buy orders:
1. The price moves away from the moving average for a pre-defined number of pips up
2. This sag should be formed at least with four candlesticks
3. The price returns back to the moving average
4. The market buy order is opened when the price reaches the moving average

Conditions for closing orders:
The order should be always closed either by stop loss or by take profit. The values of stop losses and take profits are fixed in every single trade.
Bounce4.png (49.16 KiB) Viewed 8916 times

Backtesting results
Backtesting conditions.png
Backtesting conditions.png (15.4 KiB) Viewed 8916 times

In total, we have tested 3 MA’s periods * 3 Time Frames * 3 bounce sizes * 3 stop loss values * 3 take profit values = 243 variations. We cannot be sure that the option that won among 243 variables is the one that brings the biggest profit. However, we can say that, according to the test, it is able to generate profits.

The main purpose of the posts in the closed forum is to encourage you to use the manual testing to determine the profitability of your strategy first. Then switch to the automated testing, and finally complete the whole process of testing using the “Strategy optimizer” feature.

If you decide to test this strategy:
• on the historical rates of another broker
• on other periods or types of the moving average
• on other time frames
• with other values of stop loss, take profit and the bounce size,
then please describe the results of your tests in this section, so other traders could benefit from your work and save their precious time.

H1 time frame*
H1 time frame table.png
H1 time frame table.png (22.21 KiB) Viewed 8916 times

* All detailed statistics is available in this file:
(21.86 KiB) Downloaded 157 times

As you can see from the table above, the parameters of the strategy are the main key to successful trading.

The best result was shown with the:
• stop loss of 60 pips;
• take profit of 20 pips;
• bounce size of 20 pips;
• SMA’s period of 10.
The amount of the total income has reached 14,729 pips in 12 years (1,473 pips a year on average).

The worst result had the following parameters:
• stop loss = 60 pips;
• take profit = 20 pips;
• bounce size = 60 pips;
• SMA’s period = 30.
The total loss amounted to -886 pips.

It should be mentioned that the undisputed leader on the hourly time frame is the moving average with a period of 10 and the bounce size of either 200 or 400 points (5 digits after point).

Other useful statistics for the best result:
• Profitable trades 3,312 (79.44%), losing trades – 857 (20.56%)
• The maximum number of profitable trades in a row – 32
• The maximum number of losing trades in a row – 5
• The average number of trades per month – 35

Putting it all to use
1. Let's say you open a demo account with $1,000 on it
2. Next, choose a strategy with the most profitable options, based on the “bounce from a simple moving average” strategy with a period of 10
3. Open the trades with 0.01 lot (each pip changing is equal to 10 cents)
4. A year later, most likely you will have $1,000 + $147 = $1,147

Although the ability to earn $147 per each thousand dollars every single year looks not that bad, it makes more sense to use a larger lot.

Note. The potential risks are much more important than potential profits and that is why they should be taken into account first. We have analyzed the risks of the most profitable parameters and concluded that the best parameters among of all tested are as follows:
• MA Period – 10
• Stop loss – 20
• Take profit – 20
• The bounce size – 40

The method of how we tested the risks will be described later.

Because the above-mentioned parameters will be put to use further on, it is important to see statistics on them:
• Profitable trades 1,838 (58.63%), losing trades – 1,297 (41.37%)
• The maximum number of profitable trades in a row – 13
• The maximum number of losing trades in a row – 11
• The average number of trades per month – 26
• Net profit is 10,775 pips in 10 years (90 pips per month on average)

The method of deposit’s exponential growth
This method is in the consecutive exponential lot increase after every profitable month. Let's look at two examples of this technique a bit deeper.

Example 1.
Assume that your initial deposit is $1,000. The backtesting has shown that in a month on average you can expect to make 10 775/120 months = 90 pips per month. If the lot size is equal to 0.2, i.e. 1 pip change will result in a $2 profit or loss, we get the following deposit growth plan:

Potential trading #1.png
Potential trading #1.png (15.32 KiB) Viewed 8916 times

The Excel-file with calculation for 3 years is here:
Calculation for 3 years.zip
(10.21 KiB) Downloaded 121 times

Thus, if the month is closed with the profit, we need to calculate the percentage increase of your deposit. After that, we can multiply the current value of the lot.
In this example, the trader earned 18% in 1 month, which is $180. Because the month was closed with profit we need to increase the lot size by the profit value i.e. 18%.

Good lot for this strategy is: 0.20 * 1.18 = 0.24

Example 2.
Of course, the probability of closing every single month with profit is very low. That is why, let's imagine the following situation:

Potential trading #2.png
Potential trading #2.png (14.43 KiB) Viewed 8916 times

If the month has been closed at zero profit or at a loss, it is necessary to leave the same lot size. This example is provided to you in order to be prepared for getting unprofitable months as well as quite profitable and “zero” months when the number of profitable and losing trades will be almost the same.

It should also be noted that any potentially large profits always involve potentially large losses. In order to assess the risks, you can use the following procedure.

How to calculate risks
Download the "Risk Calculation" file:
Risks calculation.zip
(224.15 KiB) Downloaded 152 times

There you will find a list of nearly 3,000 transactions on the above-mentioned best parameters.

The column “M” displays a profit / loss from each transaction. Profit is always approximately equal to 20 pips, and losses are always about -20 pips. The formula of the “N” column’s calculation is based on the “M” column and shows the cumulative number of profitable / unprofitable trades at the moment. For example, in July, six trades have been opened:

Cumulative coefficient.png
Cumulative coefficient.png (11.33 KiB) Viewed 8916 times

After the first two losing trades, the coefficient is obviously equal to negative two. Then comes the profitable trade and the coefficient is increased by one: -2 + 1 = -1. Next profitable trade increases the (-1) value by one and makes the cumulative coefficient equal to (-1) + 1 = 0.

The main task of our analysis is to find the largest negative cumulative rate for this particular currency pair and time frame.

This will allow us to comprehend the maximum acceptable drawdown degree and will determine the correct lot.

Correct lot is the lot, which provides the highest profit possible, and at the same time ensures that you not will lose the entire deposit.

The 0.01 lot definitely does not fit because of the too low potential income value. This analysis will determine the best indicator of the lot.

Download the file with detailed transactions

According to the file, the biggest negative cumulative coefficient is equal to 11. It means during the last 10 years, never had a drawdown of more than 11 trades in a row occurred. Because the sample is large, there is no reason to assume that more than 11 cumulative negative transactions will appear in future.

What is the most optimal lot?

Optimal lot.png
Optimal lot.png (23.47 KiB) Viewed 8916 times

The Excel-file with lot calculation is available here:
Lot calculation.zip
(7.19 KiB) Downloaded 133 times

If you choose the lot size of 0.25 ($2.5 per a pip), and you will lose 11 trades cumulatively, then the total loss will be $550 and $450 will remain on your deposit. Therefore, you will be able to afford to lose no more than nine additional trades.

1. Easy Strategy (only 1 indicator and unambiguous signals to the opening and closing of the orders).
2. Profitable strategy

1. Substantial amount of associated costs is involved: the commission fee to the broker, periodical swaps and what is more important spreads. Given that about 4,000 orders were opened, one should understand that if you broker charges one pip more than our calculations then you will earn 4,000 less pips in 10 months.

In this regard, it is important to find a broker with the lowest spread (preferably a few tenths of 1 pip), with moderate commissions and swaps. Since, on the one hand, we do not know the services of a broker you prefer to use, and, on the other hand, are not affiliated with any of the brokers, that is why you will have to make your own adjustments to our estimates, in accordance with the parameters of your broker.

4-hour time frame*

H4 time frame table.png
H4 time frame table.png (22.89 KiB) Viewed 8916 times

* All detailed statistics are available here:
(21.48 KiB) Downloaded 143 times

Bounce size, stop loss and take profit are calculated for the data with five digits after point.

It is noteworthy that the moving average’s period of 10 has shown the best results on 4-hour time frame as well. The winner variation had the stop loss = 60 pips, take profit = 20 pips, the bounce size of 40 pips.

Other useful statistics for the best result:
• Winning trades 734 (78.33%), losing trades – 203 (21.66%)
• The maximum number of profitable trades in a row – 30, losing trades in a row – 6
• The average number of transactions per month - 8

Most parameters ultimately gave a positive result

2488 pips / 120 months = 20 pips in a month, which clearly is not enough for you to use these parameters on the real market.

Daily time frame

D1  time frame table.png
D1 time frame table.png (22.5 KiB) Viewed 8916 times

An interesting fact for the D1 - the best and the worst results had the same size of the take profit (600 points).

The file with detailed statistics is available for download:
(19.34 KiB) Downloaded 126 times


1. Too many negative results
2. Profits in 1177 pips in 10 years is hardly enough to cover the costs of trading. In the best case, you will be able to break even

Based on 243 variations, we concluded that the most optimal parameters were:
• SMA Period – 10
• Stop loss – 20
• Take profit – 20
• Bounce size – 40
We recommend you not to put on trust our words but make use of these parameters on a demo account to confirm (or dismiss) our backtesting results.

Forex Tester Software, Inc. is not responsible of your potential profits or losses. We test the strategies on Forex Tester and provide you with the statistics received on historical data. The decision to either use our results or dismiss it is completely up to you.

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