growth since 2026
15%
- Equity
- Drawdown
Trades:
11
Profit Trades:
9 (81.81%)
Loss Trades:
2 (18.18%)
Best trade:
11.88 USD
Worst trade:
-14.36 USD
Gross Profit:
30.70 USD
(1 622 pips)
Gross Loss:
-16.04 USD
(800 pips)
Maximum consecutive wins:
8 (27.38 USD)
Maximal consecutive profit:
27.38 USD (8)
Sharpe Ratio:
0.24
Trading activity:
98.07%
Max deposit load:
62.46%
Latest trade:
5 hours ago
Trades per week:
12
Avg holding time:
8 hours
Recovery Factor:
0.91
Long Trades:
6 (54.55%)
Short Trades:
5 (45.45%)
Profit Factor:
1.91
Expected Payoff:
1.33 USD
Average Profit:
3.41 USD
Average Loss:
-8.02 USD
Maximum consecutive losses:
2 (-16.04 USD)
Maximal consecutive loss:
-16.04 USD (2)
Monthly growth:
14.67%
Algo trading:
100%
Drawdown by balance:
Absolute:
12.72 USD
Maximal:
16.04 USD (15.52%)
Relative drawdown:
By Balance:
15.52% (16.04 USD)
By Equity:
13.32% (13.76 USD)
Distribution
| Symbol | Deals | Sell | Buy | |
|---|---|---|---|---|
| EURUSD.FX | 11 | |||
|
5
10
15
20
|
5
10
15
20
|
5
10
15
20
|
| Symbol | Gross Profit, USD | Loss, USD | Profit, USD | |
|---|---|---|---|---|
| EURUSD.FX | 15 | |||
|
10
20
30
40
50
|
10
20
30
40
50
|
10
20
30
40
50
|
| Symbol | Gross Profit, pips | Loss, pips | Profit, pips | |
|---|---|---|---|---|
| EURUSD.FX | 822 | |||
|
250
500
750
1K
1.3K
1.5K
1.8K
2K
2.3K
2.5K
2.8K
3K
|
250
500
750
1K
1.3K
1.5K
1.8K
2K
2.3K
2.5K
2.8K
3K
|
250
500
750
1K
1.3K
1.5K
1.8K
2K
2.3K
2.5K
2.8K
3K
|
- Deposit load
- Drawdown
Best trade:
+11.88
USD
Worst trade:
-14
USD
Maximum consecutive wins:
8
Maximum consecutive losses:
2
Maximal consecutive profit:
+27.38
USD
Maximal consecutive loss:
-16.04
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 "tastyfx-LIVE" and the subscriber's quotes, as well as on order execution delays. Lower values mean better quality of copying.
No data
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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