368 lines
8.8 KiB
Markdown
368 lines
8.8 KiB
Markdown
|
# Backtest — Engine Simulasi Live-Sync
|
|||
|
|
|
|||
|
|
> **File:** `backtests/backtest_live_sync.py`
|
|||
|
|
> **Class:** `LiveSyncBacktest`
|
|||
|
|
> **Prinsip:** 100% identik dengan `main_live.py`
|
|||
|
|
|
|||
|
|
---
|
|||
|
|
|
|||
|
|
## Apa Itu Backtest?
|
|||
|
|
|
|||
|
|
Backtest adalah sistem **simulasi trading pada data historis** yang logikanya 100% disinkronkan dengan trading live. Tujuannya menguji strategi sebelum dipakai uang sungguhan dan memvalidasi perubahan kode.
|
|||
|
|
|
|||
|
|
**Analogi:** Backtest seperti **simulator penerbangan** — pilot (bot) berlatih di kondisi realistis tanpa risiko jatuh. Setiap instrumen, prosedur, dan respons sama persis dengan pesawat asli.
|
|||
|
|
|
|||
|
|
---
|
|||
|
|
|
|||
|
|
## Prinsip Sinkronisasi
|
|||
|
|
|
|||
|
|
```
|
|||
|
|
ATURAN UTAMA: Backtest HARUS identik dengan live.
|
|||
|
|
|
|||
|
|
Setiap perubahan di main_live.py → HARUS di-mirror di backtest_live_sync.py
|
|||
|
|
|
|||
|
|
Yang disinkronkan:
|
|||
|
|
├── ML Model: XGBoost dengan fitur yang sama
|
|||
|
|
├── SMC Analyzer: Swing length & OB lookback sama
|
|||
|
|
├── Regime Detection: HMM MarketRegimeDetector
|
|||
|
|
├── Session Filter: Golden Time 19:00-23:00 WIB
|
|||
|
|
├── Signal Logic: Semua filter entry
|
|||
|
|
├── Position Sizing: Berdasarkan ML confidence tier
|
|||
|
|
├── Trade Cooldown: 300 detik (5 menit)
|
|||
|
|
└── Exit Logic: TP, ML reversal, max loss, time-based
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
---
|
|||
|
|
|
|||
|
|
## Komponen yang Dimuat
|
|||
|
|
|
|||
|
|
```python
|
|||
|
|
# Sama persis dengan main_live.py
|
|||
|
|
self.smc = SMCAnalyzer(swing_length=config.smc.swing_length, ob_lookback=config.smc.ob_lookback)
|
|||
|
|
self.features = FeatureEngineer()
|
|||
|
|
self.regime_detector = MarketRegimeDetector(model_path="models/hmm_regime.pkl")
|
|||
|
|
self.ml_model = TradingModel(model_path="models/xgboost_model.pkl")
|
|||
|
|
self.dynamic_confidence = create_dynamic_confidence()
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
---
|
|||
|
|
|
|||
|
|
## Entry Logic (Sama dengan Live)
|
|||
|
|
|
|||
|
|
Semua filter entry di-replikasi:
|
|||
|
|
|
|||
|
|
```
|
|||
|
|
Untuk setiap bar dalam data historis:
|
|||
|
|
|
|
|||
|
|
v
|
|||
|
|
[1] COOLDOWN: Jarak >= 20 bar dari trade terakhir? (~5 menit M15)
|
|||
|
|
|YES
|
|||
|
|
[2] SESSION: Bukan Off Hours (04:00-06:00 WIB)?
|
|||
|
|
|YES
|
|||
|
|
[3] GOLDEN TIME: (opsional) Hanya 19:00-23:00 WIB?
|
|||
|
|
|YES
|
|||
|
|
[4] REGIME: Bukan CRISIS?
|
|||
|
|
|YES
|
|||
|
|
[5] SMC SIGNAL: Ada signal dari SMCAnalyzer?
|
|||
|
|
|YES
|
|||
|
|
[6] DYNAMIC CONFIDENCE: Market quality bukan AVOID?
|
|||
|
|
|YES
|
|||
|
|
[7] ML THRESHOLD: Confidence >= threshold (50%-65%)?
|
|||
|
|
|YES
|
|||
|
|
[8] ML AGREEMENT: ML tidak strongly disagree (>65% berlawanan)?
|
|||
|
|
|YES
|
|||
|
|
[9] SIGNAL CONFIRMATION: Signal muncul 2x berturut?
|
|||
|
|
|YES
|
|||
|
|
[10] PULLBACK FILTER: Momentum tidak berlawanan?
|
|||
|
|
|YES
|
|||
|
|
v
|
|||
|
|
EXECUTE SIMULATED TRADE
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
---
|
|||
|
|
|
|||
|
|
## Session Mapping
|
|||
|
|
|
|||
|
|
```python
|
|||
|
|
# Sama dengan session_filter.py
|
|||
|
|
if 6 <= hour < 15: # Sydney-Tokyo → lot 0.5x
|
|||
|
|
if 15 <= hour < 16: # Tokyo-London Overlap → lot 0.75x
|
|||
|
|
if 16 <= hour < 19: # London Early → lot 0.8x
|
|||
|
|
if 19 <= hour < 24: # London-NY (Golden) → lot 1.0x ← TERBAIK
|
|||
|
|
if 0 <= hour < 4: # NY Session → lot 0.9x
|
|||
|
|
if 4 <= hour < 6: # Off Hours → SKIP
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
---
|
|||
|
|
|
|||
|
|
## Exit Logic (5 Kondisi)
|
|||
|
|
|
|||
|
|
Untuk setiap bar setelah entry (max 100 bar):
|
|||
|
|
|
|||
|
|
### EXIT 1: Take Profit
|
|||
|
|
|
|||
|
|
```
|
|||
|
|
IF harga hit TP level:
|
|||
|
|
BUY: high >= take_profit
|
|||
|
|
SELL: low <= take_profit
|
|||
|
|
-> EXIT dengan profit penuh
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
### EXIT 2: Maximum Loss
|
|||
|
|
|
|||
|
|
```
|
|||
|
|
IF current_profit < -$50 (max_loss_per_trade):
|
|||
|
|
-> EXIT, potong kerugian
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
### EXIT 3: Time-Based (Synced dengan Live v3)
|
|||
|
|
|
|||
|
|
```
|
|||
|
|
IF 16+ bar (4 jam) DAN profit < $5:
|
|||
|
|
a) profit >= $0 → EXIT (breakeven setelah 4 jam)
|
|||
|
|
b) profit > -$15 → EXIT (loss kecil, daripada stuck)
|
|||
|
|
|
|||
|
|
IF 24+ bar (6 jam):
|
|||
|
|
-> FORCE EXIT (apapun profitnya)
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
**Visualisasi:**
|
|||
|
|
|
|||
|
|
```
|
|||
|
|
Bar: 0 5 10 15 16 20 24
|
|||
|
|
|-----|-----|-----|-----|-----|-----|
|
|||
|
|
entry | |
|
|||
|
|
| |
|
|||
|
|
4h check: 6h FORCE EXIT
|
|||
|
|
profit<$5?
|
|||
|
|
Ya -> exit
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
### EXIT 4: ML Reversal
|
|||
|
|
|
|||
|
|
```
|
|||
|
|
Setiap 5 bar, cek prediksi ML:
|
|||
|
|
|
|||
|
|
IF direction BUY DAN ML bilang SELL dengan confidence > 65%:
|
|||
|
|
-> EXIT (ML mendeteksi reversal)
|
|||
|
|
|
|||
|
|
IF direction SELL DAN ML bilang BUY dengan confidence > 65%:
|
|||
|
|
-> EXIT (ML mendeteksi reversal)
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
### EXIT 5: Trend Reversal (Momentum)
|
|||
|
|
|
|||
|
|
```
|
|||
|
|
Setelah 10+ bar, cek momentum 5 bar terakhir:
|
|||
|
|
|
|||
|
|
IF BUY DAN momentum < -$5 DAN current_profit < -$10:
|
|||
|
|
-> EXIT (tren berbalik + sudah rugi)
|
|||
|
|
|
|||
|
|
IF SELL DAN momentum > +$5 DAN current_profit < -$10:
|
|||
|
|
-> EXIT (tren berbalik + sudah rugi)
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
---
|
|||
|
|
|
|||
|
|
## Lot Sizing
|
|||
|
|
|
|||
|
|
```python
|
|||
|
|
# Berdasarkan ML confidence tier (sama dengan live)
|
|||
|
|
if ml_confidence >= 0.65:
|
|||
|
|
lot_size = 0.02 # High confidence → lot lebih besar
|
|||
|
|
elif ml_confidence >= 0.55:
|
|||
|
|
lot_size = 0.01 # Medium confidence → lot standar
|
|||
|
|
else:
|
|||
|
|
lot_size = 0.01 # Low confidence → lot minimum
|
|||
|
|
|
|||
|
|
# Apply session multiplier
|
|||
|
|
lot_size = max(0.01, lot_size * session_lot_multiplier)
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
---
|
|||
|
|
|
|||
|
|
## Pullback Filter
|
|||
|
|
|
|||
|
|
```
|
|||
|
|
Sama persis dengan main_live.py:
|
|||
|
|
|
|||
|
|
Untuk signal SELL, block jika:
|
|||
|
|
- Harga naik > $2 dalam 3 candle terakhir
|
|||
|
|
- MACD histogram rising + harga naik
|
|||
|
|
- Harga di atas EMA9 dan masih naik
|
|||
|
|
|
|||
|
|
Untuk signal BUY, block jika:
|
|||
|
|
- Harga turun > $2 dalam 3 candle terakhir
|
|||
|
|
- MACD histogram falling + harga turun
|
|||
|
|
- Harga di bawah EMA9 dan masih turun
|
|||
|
|
|
|||
|
|
Exception (tetap boleh entry):
|
|||
|
|
- Konsolidasi (pergerakan < $1.50)
|
|||
|
|
- Momentum searah signal
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
---
|
|||
|
|
|
|||
|
|
## Metrik Performa
|
|||
|
|
|
|||
|
|
| Metrik | Rumus | Keterangan |
|
|||
|
|
|--------|-------|------------|
|
|||
|
|
| **Win Rate** | Wins / Total × 100% | Persentase trade profit |
|
|||
|
|
| **Profit Factor** | Gross Profit / Gross Loss | > 1.0 = profitable |
|
|||
|
|
| **Expectancy** | (WR × Avg Win) - (LR × Avg Loss) | Rata-rata per trade |
|
|||
|
|
| **Max Drawdown** | (Peak - Trough) / Peak × 100% | Penurunan terbesar |
|
|||
|
|
| **Sharpe Ratio** | (Avg Return / Std Dev) × √252 | Risk-adjusted return |
|
|||
|
|
| **Net P/L** | Total Profit - Total Loss | Keuntungan bersih |
|
|||
|
|
|
|||
|
|
---
|
|||
|
|
|
|||
|
|
## Threshold Tuning
|
|||
|
|
|
|||
|
|
Mode `--tune` menguji beberapa ML threshold secara otomatis:
|
|||
|
|
|
|||
|
|
```python
|
|||
|
|
ml_thresholds = [0.50, 0.52, 0.55, 0.58, 0.60, 0.65]
|
|||
|
|
|
|||
|
|
# Untuk setiap threshold:
|
|||
|
|
# 1. Jalankan full backtest
|
|||
|
|
# 2. Catat: trades, win rate, net P/L, profit factor, drawdown
|
|||
|
|
# 3. Ranking berdasarkan net P/L
|
|||
|
|
|
|||
|
|
# Output:
|
|||
|
|
# ML Thresh Trades Win Rate Net P/L PF DD
|
|||
|
|
# --------------------------------------------------------
|
|||
|
|
# 55% 145 64.8% $1,250.00 1.85 3.2%
|
|||
|
|
# 52% 178 62.1% $1,100.00 1.72 4.1%
|
|||
|
|
# 60% 112 67.0% $ 980.00 1.95 2.8%
|
|||
|
|
# ...
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
---
|
|||
|
|
|
|||
|
|
## Cara Penggunaan
|
|||
|
|
|
|||
|
|
```bash
|
|||
|
|
# Backtest standar dengan threshold default (55%)
|
|||
|
|
python backtests/backtest_live_sync.py
|
|||
|
|
|
|||
|
|
# Backtest dengan threshold custom
|
|||
|
|
python backtests/backtest_live_sync.py --threshold 0.60
|
|||
|
|
|
|||
|
|
# Hanya golden time
|
|||
|
|
python backtests/backtest_live_sync.py --golden-only
|
|||
|
|
|
|||
|
|
# Threshold tuning (cari optimal)
|
|||
|
|
python backtests/backtest_live_sync.py --tune
|
|||
|
|
|
|||
|
|
# Simpan hasil ke CSV
|
|||
|
|
python backtests/backtest_live_sync.py --save
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
---
|
|||
|
|
|
|||
|
|
## Output Backtest
|
|||
|
|
|
|||
|
|
### Laporan Performa
|
|||
|
|
|
|||
|
|
```
|
|||
|
|
==================================================================
|
|||
|
|
BACKTEST RESULTS
|
|||
|
|
==================================================================
|
|||
|
|
|
|||
|
|
Configuration:
|
|||
|
|
ML Threshold: 55%
|
|||
|
|
Signal Confirmation: 2 consecutive
|
|||
|
|
Pullback Filter: Enabled
|
|||
|
|
Golden Time Only: False
|
|||
|
|
|
|||
|
|
Performance:
|
|||
|
|
Total Trades: 145
|
|||
|
|
Wins: 94
|
|||
|
|
Losses: 51
|
|||
|
|
Win Rate: 64.8%
|
|||
|
|
|
|||
|
|
Profit/Loss:
|
|||
|
|
Total Profit: $2,850.00
|
|||
|
|
Total Loss: $1,600.00
|
|||
|
|
Net P/L: $1,250.00
|
|||
|
|
Profit Factor: 1.78
|
|||
|
|
|
|||
|
|
Risk Metrics:
|
|||
|
|
Max Drawdown: 3.2% ($160.00)
|
|||
|
|
Avg Win: $30.32
|
|||
|
|
Avg Loss: $31.37
|
|||
|
|
Expectancy: $8.62
|
|||
|
|
Sharpe Ratio: 1.45
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
### Breakdown Exit Reason
|
|||
|
|
|
|||
|
|
```
|
|||
|
|
Exit Reasons:
|
|||
|
|
take_profit: 72 (49.7%)
|
|||
|
|
timeout: 35 (24.1%)
|
|||
|
|
ml_reversal: 18 (12.4%)
|
|||
|
|
max_loss: 12 (8.3%)
|
|||
|
|
trend_reversal: 8 (5.5%)
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
### Breakdown Session
|
|||
|
|
|
|||
|
|
```
|
|||
|
|
Session Performance:
|
|||
|
|
London-NY Overlap (Golden): 65 trades, 69.2% WR, $820.00
|
|||
|
|
NY Session: 32 trades, 62.5% WR, $280.00
|
|||
|
|
London Early: 28 trades, 60.7% WR, $120.00
|
|||
|
|
Sydney-Tokyo: 20 trades, 55.0% WR, $30.00
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
---
|
|||
|
|
|
|||
|
|
## File Output
|
|||
|
|
|
|||
|
|
```
|
|||
|
|
backtests/results/
|
|||
|
|
├── backtest_20250206_143000.csv # Detail semua trade
|
|||
|
|
│ ├── ticket, entry_time, exit_time
|
|||
|
|
│ ├── direction, entry_price, exit_price
|
|||
|
|
│ ├── stop_loss, take_profit, lot_size
|
|||
|
|
│ ├── profit_usd, profit_pips, result
|
|||
|
|
│ ├── exit_reason, ml_confidence, smc_confidence
|
|||
|
|
│ └── regime, session, signal_reason
|
|||
|
|
│
|
|||
|
|
└── backtest_20250206_143000_summary.csv # Ringkasan metrik
|
|||
|
|
├── total_trades, wins, losses, win_rate
|
|||
|
|
├── total_profit, total_loss, net_pnl
|
|||
|
|
├── profit_factor, avg_win, avg_loss
|
|||
|
|
└── max_drawdown, expectancy, sharpe_ratio
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
---
|
|||
|
|
|
|||
|
|
## Data Flow
|
|||
|
|
|
|||
|
|
```
|
|||
|
|
MT5 Connected
|
|||
|
|
|
|
|||
|
|
v
|
|||
|
|
Fetch 50.000 bar M15 XAUUSD
|
|||
|
|
|
|
|||
|
|
v
|
|||
|
|
FeatureEngineer.calculate_all() → 40+ fitur
|
|||
|
|
SMCAnalyzer.calculate_all() → Struktur pasar
|
|||
|
|
RegimeDetector.predict() → Regime label
|
|||
|
|
|
|
|||
|
|
v
|
|||
|
|
Filter: Jan 2025 - Now
|
|||
|
|
|
|
|||
|
|
v
|
|||
|
|
Loop setiap bar:
|
|||
|
|
├── Entry check (10 filter)
|
|||
|
|
├── Simulate exit (5 kondisi)
|
|||
|
|
├── Record trade result
|
|||
|
|
└── Update statistics
|
|||
|
|
|
|
|||
|
|
v
|
|||
|
|
Print laporan + Save CSV
|
|||
|
|
```
|