Eurusd and Correlated Pairs
This is a EURUSD type robot based on complex algorithm using pattern recognition and wide market data. It can be used on EURUSD or any correlated pair, on the 15min , 30min charts. The bars parameter (last but one input on the list) has to be set between 25 and 12 respectively!
30 minute chart >>> use the default 12 setting or increase it up to 25.
15 min chart >>> change the 12 into 25!
4 Hour Chart >>> set the parameter to 3!
actual simulation shows a trading account can double in size, in 6 months, with trading on the 30min chart, and setting this prameter to higher values, such as 25. but we need to confirm and further fine tune this.
Further updates will follow. Full presentation of this EA is very difficult, and only part of the core algorithm is used here, because we test one function at a time.
Benefits of this algorithm:
1) Not fooled by EURUSD brief momentum!
2) Solid trend following
3)Smoother profit curve (less drawdown, despite losing trades, and flat days, the EA makes very good figures over 3 months, and still makes some profit over any single month). It's not clear whether 15min or 30min works best. But profitability passed our ciritical 3 month test, showing better than expected results.
4)Future-proof - this algorithm is not affected by long term changes in volatility!
The bottomline is that this EA works very well, and has passed our basic tests at minimum account risk, while showing good profitability. Please note
trades can last up to several hours at a time. Do you own checks on live market and strategy tester to verify this. You will likely like what you will see.
We use the same robot for small account trading, there's nothing stopping clients from trading on both the 15min and 30min charts, and possibly experimenting with the H1 charts, all at the same time, as you know each EA runs on a separate chart, you only need to set different magic numbers and lot size.
This family of EAs works on patterns between 4 lines of data, the coding part involves basic pattern recognition and simplified machine learning
through the use of finite state machine algorithms to detect patterns such as line cross overs, oscilations, and more.