Simple candle filter martingale EA - MetaTrader 4용 expert

This EA uses a candle size filter to initiate a trade.

Attribution: Ideas are mine, code is compiled using fxdreema.

Concept

If the Candle size is > x pips, then the EA will enter into a buy trade.

The candle size is an input in the EA settings.

If the buy trade results in a loss, The EA will enter into the next trade at a scaled up lot size.

The scale factor is adjustable in the EA settings.

Main principle of the concept

The main principle behind all EAs that I design is to control the number of consecutive losses (Rather than to predict where the price is moving next).

This control is accomplished by increasing the Candle size required in the settings until a sufficiently low (safe) amount of consecutive losses occur over a long test period.  (The reason for controlling the consecutive losses is so that we can safely use the martingale strategy).

Settings

I use USDJPY and 4hr chart for testing. Other timeframes will work too.

I usually set the settings for candle size to be 20 or more , preferably 30.

10 or less will usually not work.

TP and SL

The TP and SL I use are normally a ratio of 1:1

and the settings are 50 TP and 50 SL

Settings of 75TP 50SL; 100TP 50SL, work if you use a lower scale factor such as 1.5.

This is because when the Ratio of TP to SL changes, the probability of winning to losing on average changes, and so do the number of consecutive losses (important).

I find as a rule of thumb that the max consec losses is usually 6 times the average losses, and that average losses in a similar ratio of TP:SL ratio (the same or a multiple of the TP:SL ratio or a less favourable ratio).

EXample a TP:SL of 50pips:50pips gives average wins to losses of 2:2 or worse 2:3 due to spread

And max consec losses of example 2x6=12. (We aim to lower these to less than 8, perhaps 6 would be good- using the candle filter)

Feedback is welcome. We can develop more advanced ideas to control consecutive losses and unleash the power of martingale in a random market environment.