|Symbol||Gross Profit, USD||Loss, USD||Profit, USD|
|Symbol||Gross Profit, pips||Loss, pips||Profit, pips|
Maximum profit (MFE) and maximum loss (MAE) values are recorded for each open order during its lifetime. These parameters additionally characterize each closed order using the values of the maximum unrealized potential and maximum permitted risk. MFE/Profit and MAE/Profit distribution graphs display each order as a point with received profit/loss value plotted along the X-axis, while maximum displayed values of potential profit (MFE) and potential loss (MAE) are plotted along the Y-axis.
Place your cursor over parameters/graph captions to see the best and worst trading series. Find out more about MAE and MFE distributions in the article Mathematics in Trading: How to Estimate Trade Results.
The average slippage based on execution statistics on real accounts of various brokers is specified in pips. It depends on the difference between the provider's quotes from "SquaredDirect-Live2" and the subscriber's quotes, as well as on order execution delays. Lower values mean better quality of copying.
This signal is running on about 25% maximum drawdown risk judging from portfolio backtest.
Copying the signal might cause high slippage because of different spreads during swap time, so I don't recommend to copy it.
It would be better to buy or rent the EA yourself: https://www.mql5.com/en/market/product/40941
The signal also uses the Breaking News Filter.
The portfolio backtests I show are usually done with a fixed lot size of 0.1. This means that you have to look at the fixed drawdown, not the percentage one. For Density Scalper with all pairs, the drawdown was about $600 for 0.1 lots, which you can use to scale to the desired risk level. For example, using 0.3 lots on all pairs would have had about $1800 maximum drawdown together in the backtest.
Things to consider:
The maximum backtest drawdown happened in 2008 and never occurred again in later years. In 2008 the spreads were much larger than they are now and the tick data quality is also much worse for early years. So some developers argue against even using data before 2010/2011. However, since optimization usually leads to underestimation of the expected drawdown, I still prefer to use the 2008 drawdown as the best estimate. 2008 was also the year of a global financial crisis, which might be a risk factor to consider for the future.
Please also keep in mind that there is never any guarantee that the future drawdown will be less than the historical one.