- Equity
- Drawdown
Trades:
44
Profit Trades:
18 (40.90%)
Loss Trades:
26 (59.09%)
Best trade:
3.15 USD
Worst trade:
-2.02 USD
Gross Profit:
21.60 USD
(189 335 pips)
Gross Loss:
-19.94 USD
(199 598 pips)
Maximum consecutive wins:
4 (3.78 USD)
Maximal consecutive profit:
3.78 USD (4)
Sharpe Ratio:
0.03
Trading activity:
40.33%
Max deposit load:
0.89%
Latest trade:
4 hours ago
Trades per week:
44
Avg holding time:
7 minutes
Recovery Factor:
0.25
Long Trades:
4 (9.09%)
Short Trades:
40 (90.91%)
Profit Factor:
1.08
Expected Payoff:
0.04 USD
Average Profit:
1.20 USD
Average Loss:
-0.77 USD
Maximum consecutive losses:
6 (-3.48 USD)
Maximal consecutive loss:
-4.05 USD (4)
Algo trading:
95%
Drawdown by balance:
Absolute:
0.00 USD
Maximal:
6.68 USD (3.37%)
Relative drawdown:
By Balance:
3.37% (6.68 USD)
By Equity:
0.80% (1.56 USD)
Distribution
| Symbol | Deals | Sell | Buy | |
|---|---|---|---|---|
| BTCUSD | 42 | |||
| XAUUSD | 2 | |||
|
10
20
30
40
50
|
10
20
30
40
50
|
10
20
30
40
50
|
| Symbol | Gross Profit, USD | Loss, USD | Profit, USD | |
|---|---|---|---|---|
| BTCUSD | -1 | |||
| XAUUSD | 3 | |||
|
10
20
30
40
|
10
20
30
40
|
10
20
30
40
|
| Symbol | Gross Profit, pips | Loss, pips | Profit, pips | |
|---|---|---|---|---|
| BTCUSD | -11K | |||
| XAUUSD | 267 | |||
|
50K
100K
150K
200K
250K
300K
350K
400K
|
50K
100K
150K
200K
250K
300K
350K
400K
|
50K
100K
150K
200K
250K
300K
350K
400K
|
- Deposit load
- Drawdown
Best trade:
+3.15
USD
Worst trade:
-2
USD
Maximum consecutive wins:
4
Maximum consecutive losses:
4
Maximal consecutive profit:
+3.78
USD
Maximal consecutive loss:
-3.48
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 "Pepperstone-MT5-Live01" and the subscriber's quotes, as well as on order execution delays. Lower values mean better quality of copying.
|
OctaFX-Real2
|
0.00 × 3 | |
|
ICTrading-MT5-4
|
0.00 × 1 | |
|
VantageInternational-Live 10
|
0.00 × 1 | |
|
GlobalPrime-Trade
|
0.00 × 1 | |
|
DerivSVG-Server-03
|
0.00 × 3 | |
|
FxPro-MT5 Live03
|
0.00 × 1 | |
|
Headway-Real
|
0.00 × 1 | |
|
ACYSecurities-Live
|
0.00 × 1 | |
|
VantageInternational-Live 15
|
0.00 × 1 | |
|
FPMarketsLLC-Live
|
0.00 × 1 | |
|
Traderscale-Trade
|
0.00 × 1 | |
|
ICMarketsEU-MT5-5
|
0.00 × 4 | |
|
OxSecurities-Live
|
0.14 × 7 | |
|
ICMarketsEU-MT5-2
|
0.74 × 27 | |
|
ICMarketsSC-MT5
|
1.08 × 531 | |
|
Exness-MT5Real26
|
1.36 × 59 | |
|
Exness-MT5Real7
|
1.57 × 408 | |
|
Exness-MT5Real3
|
2.09 × 107 | |
|
FxPro-MT5 Live02
|
2.40 × 15 | |
|
Pepperstone-MT5-Live01
|
2.52 × 9717 | |
|
FusionMarkets-Live
|
2.71 × 2279 | |
|
TradeMaxGlobal-Live
|
3.36 × 459 | |
|
Exness-MT5Real5
|
3.60 × 3698 | |
|
ICMarkets-MT5-2
|
3.71 × 1934 | |
|
FusionMarketsAU-Live
|
3.93 × 120 | |
🤖 BTCUSD AI Ensemble Scalper — Fully Automated
Advanced machine learning trading system using 3 AI models voting together (Random Forest + XGBoost + LightGBM). A trade is only placed when 2 out of 3 models agree — filtering out weak signals and reducing false entries.
Strategy Highlights:
• Ensemble ML with 28 engineered features per prediction
• EMA Trend Filter — only trades WITH the trend, never against it
• Dynamic position sizing based on ATR and account risk
• Partial profit taking at 1R (close 50%, move SL to breakeven)
• Smart exit logic — closes stagnant trades automatically
• Crash detector — halts trading during extreme volatility
• Adaptive cooldown after losses
Performance (Demo Backtest — 7 days):
• Win Rate: 61.7%
• Profit Factor: 3.49
• Zero losing days
• Average 55 trades/day
• Trades 24/7 (crypto never sleeps)
Risk Management:
• 0.5% risk per trade
• Circuit breaker at 5 consecutive losses
• 10-minute cooldown after losses
• Maximum 0.01 lot per trade
How it works:
The bot analyzes BTCUSD on M5 timeframe using momentum, volatility, session, and trend features. Three independent ML models each cast a vote (BUY/SELL/HOLD). Only when the majority agrees with sufficient confidence does a trade execute. This ensemble approach dramatically reduces noise and improves consistency.
Built with Python, scikit-learn, XGBoost, and LightGBM. Running on Pepperstone Razor (raw spreads).
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