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# Entry Trade — Proses Masuk Posisi
> **File utama:** `main_live.py`
> **File pendukung:** `src/smc_polars.py`, `src/ml_model.py`, `src/smart_risk_manager.py`, `src/session_filter.py`
---
## Apa Itu Entry Trade?
Entry Trade adalah keseluruhan proses dari **mendeteksi peluang** hingga **mengirim order ke broker**. Bot menggunakan **10+ filter** yang harus SEMUA lolos sebelum satu trade dieksekusi.
**Analogi:** Entry Trade seperti **proses boarding pesawat** — harus punya tiket (signal), passport valid (confirmation), lulus security check (risk), tepat waktu (session), dan gate terbuka (position limit).
---
## Checklist Entry (Semua Harus PASS)
```
1. [SESSION] Session filter izinkan trading?
2. [RISK MODE] Trading mode bukan STOPPED?
3. [SMC SIGNAL] Ada signal dari SMC Analyzer?
4. [ML CONFIRM] XGBoost confidence >= 50%?
5. [ML AGREE] ML tidak strongly disagree (>65% berlawanan)?
6. [QUALITY] Market quality bukan AVOID/CRISIS?
7. [CONFIRM] Signal konsisten 2 bar berturut?
8. [PULLBACK] Bukan sedang pullback/retrace?
9. [COOLDOWN] Sudah 5 menit sejak trade terakhir?
10. [POS LIMIT] Posisi terbuka < 2?
11. [LOT SIZE] Lot > 0 setelah semua adjustment?
SEMUA PASS -> Execute Trade
SATU GAGAL -> Skip, tunggu loop berikutnya
```
---
## Step-by-Step Flow
### Step 1: Session Filter
```python
# main_live.py Lines 472-483
session_ok, session_reason, session_multiplier = self.session_filter.can_trade()
if not session_ok:
return # Skip — bukan waktu trading
# Simpan multiplier untuk lot sizing nanti
self._current_session_multiplier = session_multiplier
```
**Bisa block:** Weekend, Friday >23:00, danger zone (00:00-06:00), low volatility session.
---
### Step 2: Risk Mode Check
```python
# main_live.py Lines 537-542
risk_rec = self.smart_risk.get_trading_recommendation()
if not risk_rec["can_trade"]:
return # STOPPED mode — daily/total limit tercapai
```
**Bisa block:** Mode STOPPED (daily loss >= $250, total loss >= $500).
---
### Step 3: SMC Signal Generation
```python
# main_live.py Lines 498-499
smc_signal = self.smc.generate_signal(df)
if smc_signal is None:
return # Tidak ada setup SMC yang valid
```
**SMC membutuhkan:**
- Market structure (bullish/bearish) ATAU BOS/CHoCH
- DAN (FVG ATAU Order Block)
- Minimum 2:1 risk/reward
**Output:** Entry price, SL, TP, confidence (55-85%), reason.
---
### Step 4: ML Confidence Check
```python
# main_live.py Lines 419-425
ml_prediction = self.ml_model.predict(df, feature_cols)
# Lines 664-669
if ml_prediction.confidence < 0.50:
return # ML terlalu tidak yakin
```
---
### Step 5: ML Agreement Check
```python
# main_live.py Lines 676-684
# Jika SMC bilang BUY tapi ML bilang SELL dengan confidence > 65%:
if smc_signal.signal_type == "BUY":
if ml_prediction.signal == "SELL" and ml_prediction.confidence > 0.65:
return # ML strongly disagrees — VETO
if smc_signal.signal_type == "SELL":
if ml_prediction.signal == "BUY" and ml_prediction.confidence > 0.65:
return # ML strongly disagrees — VETO
```
---
### Step 6: Dynamic Market Quality
```python
# main_live.py Lines 618-657
# Analisis kualitas pasar berdasarkan:
# - Session (London/NY = tinggi, Sydney = rendah)
# - Regime (low vol = bagus, crisis = block)
# - Volatility (medium = ideal)
# - Trend strength
# - SMC confluence
# - ML signal alignment
quality_score = analyze_market_quality(...)
# EXCELLENT (80+), GOOD (60+), MODERATE (40+), POOR (20+), AVOID (<20), CRISIS
if quality == "AVOID" or quality == "CRISIS":
return # Pasar tidak layak untuk trading
```
---
### Step 7: Signal Confirmation (2 Bar Berturut)
```python
# main_live.py Lines 686-709
signal_key = f"{smc_signal.signal_type}_{smc_signal.entry_price:.0f}"
if signal_key in self._signal_persistence:
self._signal_persistence[signal_key] += 1
else:
self._signal_persistence[signal_key] = 1
if self._signal_persistence[signal_key] < 2:
return # Belum dikonfirmasi — tunggu 1 loop lagi
# Signal sudah muncul 2x berturut -> CONFIRMED
```
**Tujuan:** Mencegah whipsaw — signal yang hanya muncul 1 detik kemungkinan noise.
---
### Step 8: Pullback Filter
```python
# main_live.py Lines 742-871
can_enter, pullback_reason = self._check_pullback_filter(df, signal.signal_type)
if not can_enter:
return # Sedang pullback, tunggu momentum selaras
```
**v5: Threshold sekarang ATR-based (bukan hardcoded)**
```
ATR diambil dari data (default $12 untuk XAUUSD)
bounce_threshold = ATR × 0.15 # ~$1.80 (sebelumnya: $2.00 fixed)
consolidation_threshold = ATR × 0.10 # ~$1.20 (sebelumnya: $1.50 fixed)
Kenapa ATR-based?
- Threshold menyesuaikan volatilitas pasar saat ini
- Saat volatilitas tinggi (ATR=$20): bounce=$3, consolidation=$2
- Saat volatilitas rendah (ATR=$8): bounce=$1.2, consolidation=$0.8
- Lebih akurat daripada threshold tetap
```
**Untuk signal BUY, block jika:**
- Harga turun > bounce_threshold (15% ATR) dalam 3 candle terakhir
- MACD bearish + harga turun
- Harga jauh di bawah EMA9 + terus turun
**Untuk signal SELL, block jika:**
- Harga naik > bounce_threshold (15% ATR) dalam 3 candle terakhir
- MACD bullish + harga naik
- Harga jauh di atas EMA9 + terus naik
**Komponen yang dicek:**
```
1. Short-term Momentum (3 candle terakhir)
-> Arah pergerakan harga terkini
-> Block jika bounce > 15% ATR (v5: dinamis)
2. MACD Histogram
-> Rising = bullish momentum
-> Falling = bearish momentum
3. Harga vs EMA9
-> Di atas = bullish bias
-> Di bawah = bearish bias
4. RSI Extreme
-> RSI > 80 = overbought (block BUY)
-> RSI < 20 = oversold (block SELL)
5. Consolidation Check
-> Jika movement < 10% ATR = consolidation → ALLOW
-> v5: dinamis, bukan fixed $1.5
```
---
### Step 9: Trade Cooldown
```python
# main_live.py Lines 520-524
trade_cooldown = 300 # 5 menit
if last_trade_time:
elapsed = (now - last_trade_time).total_seconds()
if elapsed < trade_cooldown:
return # Tunggu cooldown selesai
```
**Tujuan:** Mencegah overtrading — minimal 5 menit antar trade.
---
### Step 10: Position Limit
```python
# main_live.py Lines 588-592
can_open, limit_reason = self.smart_risk.can_open_position()
if not can_open:
return # Sudah 2 posisi terbuka (max)
```
---
### Step 11: Lot Size Calculation
```python
# main_live.py Lines 544-560
safe_lot = self.smart_risk.calculate_lot_size(
entry_price=signal.entry_price,
confidence=signal.confidence, # SMC confidence
regime=regime_name, # HMM regime
ml_confidence=ml_prediction.confidence, # ML confidence
)
# Apply session multiplier
safe_lot = max(0.01, safe_lot * session_multiplier)
if safe_lot <= 0:
return # Lot 0 = tidak boleh trade
```
---
## Eksekusi Order
Setelah semua 11 filter lolos:
```python
# main_live.py Lines 985-1008
# Step A: Ambil harga real-time
tick = mt5.get_tick(symbol)
current_price = tick.ask if BUY else tick.bid
# Step B: Validasi broker SL (min 10 pips)
broker_sl = signal.stop_loss
if jarak_terlalu_dekat:
broker_sl = paksa_lebih_lebar
# Step C: Kirim order
result = mt5.send_order(
symbol="XAUUSD",
order_type="BUY" / "SELL",
volume=0.01 - 0.02, # Lot dari risk calculation
sl=broker_sl, # ATR-based SL (v3)
tp=signal.take_profit, # SMC TP (ATR-capped)
magic=123456, # ID bot
comment="AI Safe v3",
)
# Step D: Fallback jika broker reject SL
if gagal dan error 10016:
result = mt5.send_order(sl=0, ...) # Tanpa broker SL
# Step E: Slippage Validation (v5 BARU)
if result.success:
actual_price = result.price
slippage = abs(actual_price - signal.entry_price)
max_slippage = signal.entry_price * 0.0015 # 0.15% dari harga
if slippage > max_slippage:
log WARNING "HIGH SLIPPAGE" # Catat slippage tinggi
# Gunakan harga AKTUAL untuk tracking, bukan harga expected
# Step F: Partial Fill Check (v5 BARU)
filled_volume = result.volume
if filled_volume < requested_volume:
log WARNING "PARTIAL FILL"
# Update lot_size ke volume yang sebenarnya terisi
position.lot_size = filled_volume
# Step G: Register posisi (gunakan nilai AKTUAL)
smart_risk.register_position(
ticket=result.order_id,
entry_price=actual_price, # v5: harga aktual (bukan expected)
lot_size=filled_volume, # v5: volume aktual (bukan requested)
direction=signal.signal_type,
)
```
### Slippage & Partial Fill (v5 Detail)
```
SLIPPAGE VALIDATION:
expected_price = signal.entry_price
actual_price = result.price (dari broker)
slippage = |actual - expected|
max_acceptable = 0.15% dari harga (~$4 untuk XAUUSD @$2650)
Jika slippage > max_acceptable:
-> LOG WARNING (untuk monitoring & analisis)
-> Tetap pakai harga aktual untuk position tracking
PARTIAL FILL HANDLING:
requested_volume = lot dari risk calculation
filled_volume = result.volume (dari broker)
Jika filled < requested:
-> LOG WARNING dengan fill ratio (%)
-> Update position.lot_size ke filled_volume
-> Risk calculation tetap akurat (berdasarkan volume sebenarnya)
```
---
## Post-Entry
```python
# Step H: Log trade detail
trade_logger.log_trade_open(
signal, ml_prediction, regime, market_quality, ...
)
# Step G: Kirim notifikasi Telegram
await telegram.send_trade_open(trade_info)
# Step H: Update cooldown timer
last_trade_time = now
```
---
## Diagram Flow Lengkap
```
Loop setiap 1 detik
|
v
Fetch 200 bar M15 -> Feature Eng -> SMC -> HMM -> XGBoost
|
v
[1] Session OK? ----NO----> Skip
|YES
[2] Risk OK? -------NO----> Skip (STOPPED)
|YES
[3] SMC Signal? ----NO----> Skip (tidak ada setup)
|YES
[4] ML >= 50%? -----NO----> Skip (terlalu uncertain)
|YES
[5] ML Agree? ------NO----> Skip (ML veto)
|YES
[6] Quality OK? ----NO----> Skip (AVOID/CRISIS)
|YES
[7] Confirmed 2x? --NO----> Skip (tunggu konfirmasi)
|YES
[8] No Pullback? ---NO----> Skip (retrace)
|YES
[9] Cooldown OK? ---NO----> Skip (< 5 menit)
|YES
[10] Pos < 2? ------NO----> Skip (full)
|YES
[11] Lot > 0? ------NO----> Skip
|YES
v
EXECUTE TRADE -> Register -> Log -> Telegram
```
---
## Statistik Filter
Dalam kondisi normal, dari ratusan loop per jam:
- **~95%** diblokir oleh "tidak ada SMC signal" (pasar sideways)
- **~3%** diblokir oleh ML disagreement atau low confidence
- **~1%** diblokir oleh pullback filter atau session
- **<1%** lolos semua filter dan menghasilkan trade
**Rata-rata:** 3-8 trade per hari (sangat selektif).