GifariKemalandClaude Opus 4.6
757b499033
5 major issues reflected in documentation: 1. Confidence calibration (03-SMC, 00-ARSITEKTUR): - Base 55% + 10% each → base 40% + weighted scoring - Structure +15%, BOS/CHoCH +12%, FVG +8%, OB +10%, Trend +10% 2. ATR-based pullback filter (09-Entry, 00-ARSITEKTUR): - Hardcoded $2/$1.5 → bounce 15% ATR, consolidation 10% ATR 3. Smarter time-based exit (10-Exit, 05-Risk, 00-ARSITEKTUR): - 4h: check profit growth, not just profit<$5 - 6h: extend to 8h if profit>$10 and growing + ML agrees 4. Slippage validation (09-Entry, 23-Main, 00-ARSITEKTUR): - Check actual vs expected price, log if >0.15% 5. Partial fill handling (09-Entry, 23-Main, 00-ARSITEKTUR): - Check filled volume, use actual values for tracking Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
450 lines
15 KiB
Markdown
450 lines
15 KiB
Markdown
# SMC Analyzer (Smart Money Concepts)
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> **File:** `src/smc_polars.py`
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> **Framework:** Pure Polars (vectorized, tanpa loop)
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---
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## Apa Itu SMC?
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Smart Money Concepts adalah metode analisis berdasarkan **cara institusi besar (bank, hedge fund) trading**. SMC membaca **struktur pasar** dan **jejak uang besar** untuk menemukan zona entry yang presisi.
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**Analogi:** SMC adalah **peta jalan** — menunjukkan zona penting, rambu lalu lintas, dan rute terbaik.
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---
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## 6 Konsep yang Diimplementasikan
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| # | Konsep | Fungsi | Lines |
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|---|--------|--------|-------|
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| 1 | Swing Points | Puncak & lembah penting | 185-261 |
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| 2 | Fair Value Gap (FVG) | Imbalance/gap harga | 84-183 |
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| 3 | Order Block (OB) | Zona order institusi | 263-368 |
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| 4 | Break of Structure (BOS) | Kelanjutan tren | 370-457 |
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| 5 | Change of Character (CHoCH) | Pembalikan tren | 370-457 |
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| 6 | Liquidity Zones | Kumpulan stop loss | 459-551 |
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---
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## 1. Swing Points (Fractal High/Low)
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**Fungsi:** Mendeteksi puncak dan lembah penting di chart.
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### Algoritma
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```
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Window: 2 x swing_length + 1 = 11 candle (default swing_length=5)
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Deteksi TANPA LOOKAHEAD (no future data):
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- Rolling max/min menggunakan center=False (hanya data masa lalu)
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- Swing point dikonfirmasi swing_length bar SETELAH terjadi
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- Menggunakan shift(swing_length) untuk melihat "center" point
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Swing High: High di center point = Maximum dalam window 11 bar ke belakang
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Swing Low: Low di center point = Minimum dalam window 11 bar ke belakang
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Catatan: Deteksi terlambat swing_length bar (5 bar), tapi
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TIDAK menggunakan data masa depan (zero lookahead).
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```
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### Visualisasi
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```
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/\ <- Swing High (high = max 11 candle)
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/ \
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/ \
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/ \
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/ \/ <- Swing Low (low = min 11 candle)
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/
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```
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### Output
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| Kolom | Nilai | Keterangan |
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|-------|-------|-----------|
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| `swing_high` | 1 / 0 | 1 jika swing high |
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| `swing_low` | -1 / 0 | -1 jika swing low |
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| `swing_high_level` | float | Harga di swing high |
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| `swing_low_level` | float | Harga di swing low |
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| `last_swing_high` | float | Swing high terakhir (forward fill) |
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| `last_swing_low` | float | Swing low terakhir (forward fill) |
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---
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## 2. Fair Value Gap (FVG)
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**Fungsi:** Mendeteksi **imbalance/gap** di harga — zona yang belum "diisi" oleh pasar.
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### Algoritma
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```
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TANPA LOOKAHEAD — Deteksi pada candle KETIGA (setelah pola selesai):
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Bullish FVG: Bearish FVG:
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Candle T-2: ████ high Candle T-2: ████ low
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Candle T-1: (middle) Candle T-1: (middle)
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Candle T: ████ low (SAAT INI) Candle T: ████ high (SAAT INI)
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Syarat Bullish: high[T-2] < low[T] (gap antara candle pertama & ketiga)
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Syarat Bearish: low[T-2] > high[T] (gap antara candle pertama & ketiga)
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Catatan: TIDAK menggunakan shift(-1) / data masa depan.
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FVG dideteksi pada candle saat ini (T) setelah pola terkonfirmasi.
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```
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### Zona FVG
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```
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Bullish FVG Zone:
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Top = low[T] (low candle saat ini = batas atas gap)
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Bottom = high[T-2] (high candle pertama = batas bawah gap)
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Mid = (top + bottom) / 2 (50% retracement)
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```
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### Output
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| Kolom | Nilai | Keterangan |
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|-------|-------|-----------|
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| `fvg_signal` | 1 / -1 / 0 | Bullish / Bearish / Tidak ada |
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| `fvg_top` | float | Batas atas gap |
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| `fvg_bottom` | float | Batas bawah gap |
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| `fvg_mid` | float | Titik tengah (target retracement) |
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**Peran:** Zona entry ideal — harga cenderung **kembali mengisi gap** sebelum melanjutkan.
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---
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## 3. Order Block (OB)
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**Fungsi:** Mendeteksi candle terakhir sebelum pergerakan besar — zona dimana institusi menaruh order.
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### Algoritma
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```
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TANPA LOOKAHEAD — Validasi menggunakan candle SAAT INI:
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Bullish OB:
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1. Temukan swing low
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2. Lihat 10 candle ke belakang
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3. Cari candle bearish terakhir (close < open)
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4. Jika candle SAAT INI close di atas high candle tersebut:
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-> Candle itu = Bullish Order Block
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(validasi di bar saat ini, BUKAN bar berikutnya)
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Bearish OB:
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1. Temukan swing high
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2. Lihat 10 candle ke belakang
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3. Cari candle bullish terakhir (close > open)
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4. Jika candle SAAT INI close di bawah low candle tersebut:
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-> Candle itu = Bearish Order Block
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(validasi di bar saat ini, BUKAN bar berikutnya)
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```
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### Visualisasi
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```
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Bullish OB: Bearish OB:
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████ <- Bullish candle terakhir
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████ <- Bearish candle terakhir sebelum jatuh
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sebelum naik ═══════════════
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═══════════════ ||| turun
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||| naik
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```
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### Output
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| Kolom | Nilai | Keterangan |
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|-------|-------|-----------|
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| `ob` | 1 / -1 / 0 | Bullish / Bearish / Tidak ada |
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| `ob_top` | float | Batas atas zona OB |
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| `ob_bottom` | float | Batas bawah zona OB |
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| `ob_mitigated` | bool | True jika OB sudah dikunjungi ulang |
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**Peran:** Zona support/resistance berdasarkan aksi institusi besar.
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---
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## 4. Break of Structure (BOS)
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**Fungsi:** Mendeteksi **kelanjutan tren** — harga menembus swing point searah tren.
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### Algoritma
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```python
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# Tren sudah BULLISH, lalu:
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if close > last_swing_high:
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bos = 1 # Bullish BOS — tren naik BERLANJUT
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# Tren sudah BEARISH, lalu:
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if close < last_swing_low:
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bos = -1 # Bearish BOS — tren turun BERLANJUT
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```
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### Visualisasi
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```
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Bullish BOS:
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SH1 SH2 (baru ditembus!)
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/ \ / close >>>
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/ \ /
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/ SL1 -> BOS! Tren naik lanjut
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Bearish BOS:
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\ SH1
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\ / \
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\ / \ close <<<
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SL1 SL2 (baru ditembus!) -> BOS! Tren turun lanjut
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```
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### Output
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| Kolom | Nilai | Keterangan |
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|-------|-------|-----------|
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| `bos` | 1 / -1 / 0 | Bullish / Bearish / Tidak ada |
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**Peran:** Konfirmasi bahwa **tren masih kuat** dan lanjut.
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---
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## 5. Change of Character (CHoCH)
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**Fungsi:** Mendeteksi **pembalikan tren** — harga menembus swing point berlawanan tren.
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### Algoritma
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```python
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# Tren sedang BEARISH, lalu:
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if close > last_swing_high:
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choch = 1 # Bullish CHoCH — REVERSAL naik!
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# Tren sedang BULLISH, lalu:
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if close < last_swing_low:
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choch = -1 # Bearish CHoCH — REVERSAL turun!
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```
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### Visualisasi
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```
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Bearish CHoCH (tren naik -> balik turun):
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SH <- gagal naik
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/ \
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/ \
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/ close menembus SL >>> CHoCH! Reversal turun!
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SL
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Bullish CHoCH (tren turun -> balik naik):
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SH
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\ close menembus SH >>> CHoCH! Reversal naik!
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\ /
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\ /
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SL <- gagal turun
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```
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### Output
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| Kolom | Nilai | Keterangan |
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|-------|-------|-----------|
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| `choch` | 1 / -1 / 0 | Bullish / Bearish / Tidak ada |
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| `market_structure` | 1 / -1 / 0 | Bullish / Bearish / Netral |
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**Peran:** **Early warning** perubahan arah tren.
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---
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## 6. Liquidity Zones
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**Fungsi:** Mendeteksi kumpulan stop loss (equal highs/lows) yang bisa "disapu" oleh institusi.
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### Algoritma
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```
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1. Hitung rolling std & mean dari highs dan lows (window=20)
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2. Coefficient of Variation = std / mean
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3. Jika CV < 0.001 (0.1%):
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-> Harga sangat mirip = cluster likuiditas
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-> BSL (Buy Side Liquidity) = level high
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-> SSL (Sell Side Liquidity) = level low
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4. Deteksi sweep:
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-> BSL sweep: High > BSL lalu close < BSL
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-> SSL sweep: Low < SSL lalu close > SSL
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```
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### Visualisasi
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```
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Buy Side Liquidity (BSL): Sell Side Liquidity (SSL):
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═══════ equal highs ═══════
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████ ████ ████ ████ ████ ████ ████ ████
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═══════ equal lows ═══════
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^ Stop loss short sellers ^ Stop loss long traders
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^ Institusi sweep ke atas ^ Institusi sweep ke bawah
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```
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### Output
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| Kolom | Nilai | Keterangan |
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|-------|-------|-----------|
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| `bsl_level` | float | Level buy side liquidity |
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| `ssl_level` | float | Level sell side liquidity |
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| `liquidity_sweep` | "BSL" / "SSL" / None | Sweep terdeteksi |
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---
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## Signal Generation
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### ATR-Based Dynamic SL/TP (v4 Update)
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Sebelum menghitung SL dan TP, sistem mengambil nilai ATR untuk kalkulasi dinamis:
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```python
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atr = latest["atr"] # Dari Feature Engineering
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# Sanity check ATR (v4: validasi ketat)
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if atr is None or atr <= 0 or atr > current_close * 0.05:
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atr = 12.0 # Default realistis untuk XAUUSD (~$12-15 tipikal)
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min_sl_distance = 1.5 * atr # Minimum jarak SL = 1.5 ATR
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min_rr_ratio = 2.0 # ENFORCED: Minimum Risk:Reward 1:2
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```
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### Kondisi Bullish Signal
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```
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IF (market_structure == BULLISH ATAU ada BOS/CHoCH bullish)
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AND (ada FVG bullish ATAU Order Block bullish):
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Entry = current_close (v4: SELALU harga saat ini, bukan harga zone lama)
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SL (v4 - ATR-based, lebih protektif):
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swing_sl = last_swing_low (jika ada & di bawah entry)
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atr_sl = entry - 1.5 * ATR
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SL = MIN(swing_sl, atr_sl) <- pilih yang LEBIH JAUH
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IF entry - SL < min_sl_distance:
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SL = entry - min_sl_distance <- enforce jarak minimum
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TP (v4 - ENFORCED minimum 1:2 RR):
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risk = entry - SL
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tp = entry + (risk * 2.0) <- TEPAT 2:1 R:R
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IF actual_rr < 2.0:
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-> SKIP sinyal (tidak valid) <- sinyal ditolak jika RR terlalu kecil
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```
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### Kondisi Bearish Signal
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```
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IF (market_structure == BEARISH ATAU ada BOS/CHoCH bearish)
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AND (ada FVG bearish ATAU Order Block bearish):
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Entry = current_close (v4: SELALU harga saat ini, bukan harga zone lama)
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SL (v4 - ATR-based, lebih protektif):
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swing_sl = last_swing_high (jika ada & di atas entry)
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atr_sl = entry + 1.5 * ATR
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SL = MAX(swing_sl, atr_sl) <- pilih yang LEBIH JAUH
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IF SL - entry < min_sl_distance:
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SL = entry + min_sl_distance <- enforce jarak minimum
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TP (v4 - ENFORCED minimum 1:2 RR):
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risk = SL - entry
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tp = entry - (risk * 2.0) <- TEPAT 2:1 R:R
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IF actual_rr < 2.0:
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-> SKIP sinyal (tidak valid) <- sinyal ditolak jika RR terlalu kecil
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```
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### Perbandingan Evolusi SL/TP
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```
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┌────────────┬─────────────────────┬──────────────────────┬──────────────────────────┐
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│ Komponen │ v2 (lama) │ v3 │ v4 (sekarang) │
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├────────────┼─────────────────────┼──────────────────────┼──────────────────────────┤
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│ Entry │ Zone price (FVG/OB) │ Zone price (FVG/OB) │ SELALU current_close │
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├────────────┼─────────────────────┼──────────────────────┼──────────────────────────┤
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│ SL (BUY) │ entry * 0.995 │ MIN(swing, 1.5ATR) │ MIN(swing, 1.5ATR) │
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│ │ (bisa terlalu dekat)│ │ + enforce min distance │
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├────────────┼─────────────────────┼──────────────────────┼──────────────────────────┤
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│ TP │ risk * 2 │ MIN(risk*2, 4*ATR) │ risk * 2.0 (ENFORCED) │
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│ │ (tanpa batas) │ (dibatasi) │ SKIP jika RR < 2.0 │
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├────────────┼─────────────────────┼──────────────────────┼──────────────────────────┤
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│ ATR default│ close * 1% │ close * 1% │ $12 (realistis XAUUSD) │
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├────────────┼─────────────────────┼──────────────────────┼──────────────────────────┤
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│ Lookahead │ Ada (shift -1) │ Ada (shift -1) │ TIDAK ADA (zero future) │
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└────────────┴─────────────────────┴──────────────────────┴──────────────────────────┘
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```
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### Sistem Confidence (v5: Calibrated Weighted Scoring)
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```
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Sebelum (v4): Sesudah (v5):
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Base: 55% Base: 40%
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+ BOS/CHoCH: +10% + Structure aligned: +15%
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+ FVG: +10% + BOS/CHoCH: +12%
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+ OB: +10% + FVG: +8%
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Max: 85% + Order Block: +10%
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+ Trend strength: +10%
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+ Fresh level: +5%
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Max: 85%
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Kalkulasi confidence sekarang menggunakan metode calculate_confidence():
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1. Base = 40% (minimum, selalu ada)
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2. Structure aligned = +15% (market_structure searah sinyal)
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3. BOS/CHoCH = +12% (ada break of structure/character)
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4. FVG = +8% (ada Fair Value Gap)
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5. Order Block = +10% (ada Order Block)
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6. Trend strength = +10% (ada ≥2 BOS searah dalam 20 bar terakhir)
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7. Fresh level = +5% (first touch of key level)
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8. Cap di 85% (tidak pernah 100% yakin)
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Contoh:
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BUY signal, structure bullish, ada BOS + FVG + OB, trend kuat:
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= 40% + 15% + 12% + 8% + 10% + 10% = 95% → cap 85%
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BUY signal, structure bearish, ada CHoCH + FVG saja:
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= 40% + 0% + 12% + 8% + 0% + 0% = 60%
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```
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### Output Signal
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```python
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SMCSignal:
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signal_type: "BUY" / "SELL"
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entry_price: float
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stop_loss: float # ATR-based (min 1.5 ATR dari entry)
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take_profit: float # 2:1 RR, capped di 4 ATR
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confidence: 0.40 - 0.85 # v5: base diturunkan ke 40% (calibrated)
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reason: "Bullish BOS + FVG + OB"
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risk_reward: float # Minimum 2.0
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```
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---
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## Konfigurasi
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```python
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SMCConfig:
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swing_length: 5 # Window untuk deteksi swing (11 bar total)
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fvg_min_gap_pips: 2.0 # Minimum ukuran FVG
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ob_lookback: 10 # Berapa jauh cari OB ke belakang
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bos_close_break: True # Harus close (bukan wick) yang break
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```
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---
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## Integrasi dalam Pipeline
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```
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Data OHLCV
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v
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smc.calculate_all(df)
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|--- calculate_fair_value_gaps()
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|--- calculate_swing_points()
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|--- calculate_order_blocks() <- butuh swing points
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|--- calculate_structure_breaks() <- butuh swing points
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|--- calculate_liquidity_zones()
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v
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smc.generate_signal(df)
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v
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SMCSignal (entry, SL, TP, confidence)
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v
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Dikombinasikan dengan XGBoost + HMM
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```
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