growth since 2025
10%
- Equity
- Drawdown
Trades:
61
Profit Trades:
33 (54.09%)
Loss Trades:
28 (45.90%)
Best trade:
6.15 USD
Worst trade:
-3.35 USD
Gross Profit:
35.58 USD
(8 887 pips)
Gross Loss:
-25.63 USD
(6 398 pips)
Maximum consecutive wins:
8 (4.27 USD)
Maximal consecutive profit:
7.08 USD (2)
Sharpe Ratio:
0.11
Trading activity:
100.00%
Max deposit load:
10.10%
Latest trade:
1 day ago
Trades per week:
7
Avg holding time:
2 days
Recovery Factor:
0.90
Long Trades:
30 (49.18%)
Short Trades:
31 (50.82%)
Profit Factor:
1.39
Expected Payoff:
0.16 USD
Average Profit:
1.08 USD
Average Loss:
-0.92 USD
Maximum consecutive losses:
6 (-5.63 USD)
Maximal consecutive loss:
-5.86 USD (4)
Monthly growth:
7.44%
Annual Forecast:
90.30%
Algo trading:
100%
Drawdown by balance:
Absolute:
6.73 USD
Maximal:
11.08 USD (10.62%)
Relative drawdown:
By Balance:
10.52% (10.96 USD)
By Equity:
3.37% (3.49 USD)
Distribution
| Symbol | Deals | Sell | Buy | |
|---|---|---|---|---|
| EURUSD | 61 | |||
|
20
40
60
|
20
40
60
|
20
40
60
|
| Symbol | Gross Profit, USD | Loss, USD | Profit, USD | |
|---|---|---|---|---|
| EURUSD | 10 | |||
|
20
40
60
|
20
40
60
|
20
40
60
|
| Symbol | Gross Profit, pips | Loss, pips | Profit, pips | |
|---|---|---|---|---|
| EURUSD | 2.5K | |||
|
2.5K
5K
7.5K
10K
13K
15K
18K
20K
|
2.5K
5K
7.5K
10K
13K
15K
18K
20K
|
2.5K
5K
7.5K
10K
13K
15K
18K
20K
|
- Deposit load
- Drawdown
Best trade:
+6.15
USD
Worst trade:
-3
USD
Maximum consecutive wins:
2
Maximum consecutive losses:
4
Maximal consecutive profit:
+4.27
USD
Maximal consecutive loss:
-5.63
USD
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 "Trading.comMarkets-MT5" and the subscriber's quotes, as well as on order execution delays. Lower values mean better quality of copying.
These signals are generated by a proprietary AI framework purpose-built for forex, integrating deep neural networks with structural market analysis across multiple timeframes. Trained on extensive historical and streaming data, the system models non-linear dynamics and evolving market regimes to surface statistically high-confidence trade setups. The result is an adaptive, multi-horizon signal engine engineered to convert complex data flows into precise, execution-ready insights.
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