配布
| シンボル | ディール | Sell | Buy | |
|---|---|---|---|---|
| NAS100 | 48 | |||
|
10
20
30
40
50
|
10
20
30
40
50
|
10
20
30
40
50
|
| シンボル | 総利益, USD | Loss, USD | 利益, USD | |
|---|---|---|---|---|
| NAS100 | 92 | |||
|
100
200
300
400
500
600
|
100
200
300
400
500
600
|
100
200
300
400
500
600
|
| シンボル | 総利益, pips | Loss, pips | 利益, pips | |
|---|---|---|---|---|
| NAS100 | 2.3K | |||
|
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
- ドローダウン
いろいろなブローカーのリアルアカウント上で実行統計に基づいたスリッページの平均は、いくつかの点で指定されています。それはオーダー実行の遅れに依るのと同様に、プロバイダーの"PepperstoneBS-MT5-Live01"からの引用と購読者の引用の違いに依るものです。値がより低いことがコピーの品質がより良いことを意味しています。
|
Bybit-Live
|
0.00 × 30 |
|
FusionMarkets-Live
|
5.00 × 1 |
Execution Style
-
Uses a multi‑layered strategy mixture combining:
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Market structure mapping
-
CHoCH (Change of Character) confirmation
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Fair Value Gap (FVG) alignment
-
Liquidity sweep detection
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Micro‑trend continuation logic
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Volatility compression/expansion signals
-
-
Trades across multiple market sessions, adapting to:
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Shifts in volatility
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Liquidity cycles
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Micro‑structure changes
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Algorithmic behavior patterns
-
-
AI component provides:
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Micro‑structure pattern recognition
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Probability scoring of potential setups
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Real‑time filtering of low‑quality zones
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Adaptive bias detection (bullish/bearish micro‑trend)
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Noise reduction during choppy conditions
-
-
Human oversight ensures:
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Manual validation of AI‑flagged zones
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Strict adherence to risk parameters
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No emotional or impulsive trades
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No forced entries — only validated setups
-
-
Strategy blends scalping + intraday logic:
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Scalps: micro‑structure breaks, liquidity taps, FVG reactions
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Intraday: continuation setups, structural shifts, trend legs
-
-
Uses fixed risk per trade with:
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Pre‑defined stop placement
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No martingale
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No grid
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No position doubling
-
-
Average trades/day: low to moderate, prioritizing quality over quantity
-
Focuses on clean execution, controlled risk, and high‑probability setups only
-
Designed to perform in:
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Trending environments
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Range‑bound conditions
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High‑volatility spikes
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Algorithmic liquidity hunts
-