XauBot/docs/arsitektur-ai/15-Dynamic-Confidence.md

Dynamic Confidence — Penyesuaian Threshold Otomatis

File: src/dynamic_confidence.py Class: DynamicConfidenceManager Digunakan di: main_live.py, backtest_live_sync.py

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Apa Itu Dynamic Confidence?

Dynamic Confidence adalah sistem yang menyesuaikan confidence threshold ML secara otomatis berdasarkan kondisi pasar saat ini. Saat kondisi ideal, threshold diturunkan agar lebih banyak peluang. Saat kondisi buruk, threshold dinaikkan untuk lebih selektif.

Analogi: Dynamic Confidence seperti termometer yang mengatur AC otomatis — saat cuaca panas (pasar bagus), AC diset dingin (threshold rendah, lebih banyak trade). Saat cuaca dingin (pasar buruk), AC dimatikan (threshold tinggi, kurangi trade).

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Prinsip Dasar

Market BAGUS (trending, session bagus)  → Threshold RENDAH (60%)  → Lebih banyak trade
Market BIASA (normal)                   → Threshold SEDANG (70%)  → Trade normal
Market JELEK (choppy, low liquidity)    → Threshold TINGGI (80%)  → Sangat selektif
Market BERBAHAYA (crisis, weekend)      → Threshold MAXIMUM (85%) → Hindari trading

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Konfigurasi

DynamicConfidenceManager(
    base_threshold=0.70,   # Default threshold 70%
    min_threshold=0.60,    # Minimum (kondisi terbaik): 60%
    max_threshold=0.85,    # Maximum (kondisi terburuk): 85%
)

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6 Faktor Penilaian

Score dimulai dari 50 (tengah), lalu disesuaikan oleh 6 faktor:

Faktor 1: Session (±20 poin)

Session	Poin	Alasan
London-NY Overlap / Golden	+20	Likuiditas tertinggi, spread rendah
London	+15	Volume tinggi
New York	+10	Volume tinggi
Asia/Tokyo	+0	Volatilitas rendah
Market Closed/Weekend	-30	Tidak ada likuiditas
Lainnya	+5	Default

Faktor 2: Regime (±15 poin)

Regime	Poin	Alasan
Medium Volatility	+15	Kondisi ideal untuk trading
Low Volatility	+5	Hati-hati ranging
High Volatility	-5	Perlu lot kecil
Crisis	-25	Hindari trading

Faktor 3: Volatility (±10 poin)

Volatility	Poin	Alasan
Medium	+10	Pergerakan cukup, bisa diprediksi
Low	+0	Pergerakan terlalu kecil
High	-5	Sulit diprediksi
Extreme	-10	Sangat berbahaya

Faktor 4: Trend Clarity (±10 poin)

Trend	Poin	Alasan
Uptrend / Downtrend	+10	Arah jelas, sinyal lebih akurat
Neutral / Ranging	-5	Sinyal sering whipsaw

Faktor 5: SMC Confluence (±10 poin)

Kondisi	Poin	Alasan
Ada sinyal SMC (OB/FVG/BOS)	+10	Konfirmasi tambahan
Tidak ada sinyal	+0	Tanpa konfirmasi

Faktor 6: ML Alignment (±5 poin)

ML Confidence	Poin	Alasan
>= 70%	+5	ML sangat yakin
>= 60%	+2	ML cukup yakin
< 60%	+0	ML kurang yakin

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Pemetaan Score ke Quality

Score dihitung (0–100), lalu dipetakan ke 5 level kualitas:

Score:  0    10    20    30    35    50    65    80    100
        |-----|-----|-----|-----|-----|-----|-----|-----|
        |     AVOID      |POOR |  MODERATE  |GOOD | EXCELLENT
        |    (< 35)      |     | (50-64)    |     | (80+)
        |  thresh: 85%   |80%  |   70%      |65%  |  60%

Score	Quality	Threshold	Aksi
80+	EXCELLENT	60%	Trade dengan percaya diri
65-79	GOOD	65%	Trade normal
50-64	MODERATE	70%	Trade hati-hati
35-49	POOR	80%	Sangat selektif
< 35	AVOID	85%	Jangan trade

---

Contoh Perhitungan

Contoh 1: Kondisi Ideal (Score: 95)

Base score:                        50

[+20] Session: London-NY Overlap   → 70
[+15] Regime: Medium Volatility    → 85
[+10] Volatility: Medium           → 95
[+10] Trend: UPTREND               → 105 → cap 100
[+10] SMC: Ada FVG + BOS           → 100
[+5]  ML: 72% confidence           → 100

Score: 100 → EXCELLENT → Threshold: 60%

Artinya: ML cukup confidence 60% saja untuk entry. Lebih banyak trade opportunity.

Contoh 2: Kondisi Jelek (Score: 40)

Base score:                        50

[+0]  Session: Asia                → 50
[+5]  Regime: Low Volatility       → 55
[+0]  Volatility: Low              → 55
[-5]  Trend: RANGING               → 50
[+0]  SMC: Tidak ada signal        → 50
[+0]  ML: 58% confidence           → 50

Score: 50 → MODERATE → Threshold: 70%

Artinya: ML harus confidence 70% untuk entry. Lebih selektif.

Contoh 3: Kondisi Berbahaya (Score: 15)

Base score:                        50

[-30] Session: Weekend             → 20
[-25] Regime: Crisis               → -5 → cap 0
[-10] Volatility: Extreme          → 0
[-5]  Trend: Ranging               → 0
[+0]  SMC: Tidak ada               → 0
[+0]  ML: 55%                      → 0

Score: 0 → AVOID → Threshold: 85% (praktis tidak trade)

---

Integrasi di Entry Flow

# main_live.py — Step 6 dari 11 filter entry

# 1. Analisis kondisi market
market_analysis = dynamic_confidence.analyze_market(
    session=session_name,           # "London-NY Overlap"
    regime=regime_name,             # "medium_volatility"
    volatility=volatility_level,    # "medium"
    trend_direction=trend,          # "UPTREND"
    has_smc_signal=True,            # Ada SMC signal
    ml_signal=ml_pred.signal,       # "BUY"
    ml_confidence=ml_pred.confidence, # 0.68
)

# 2. Cek quality
if market_analysis.quality == MarketQuality.AVOID:
    return  # SKIP — market tidak layak

# 3. Cek apakah ML confidence memenuhi threshold dinamis
can_entry, reason = dynamic_confidence.get_entry_decision(
    ml_confidence=0.68,
    analysis=market_analysis,
)

# can_entry = True (0.68 >= 0.60 threshold untuk EXCELLENT)
# reason = "Entry OK: ML 68% >= threshold 60% (score=95)"

---

Integrasi di Backtest

# backtest_live_sync.py — identik dengan live

market_analysis = self.dynamic_confidence.analyze_market(
    session=session_name,
    regime=regime,
    volatility="medium",
    trend_direction=regime,
    has_smc_signal=True,
    ml_signal=ml_pred.signal,
    ml_confidence=ml_pred.confidence,
)

if market_analysis.quality == MarketQuality.AVOID:
    continue  # Skip bar ini

---

Method get_entry_decision()

def get_entry_decision(ml_confidence, analysis) -> (bool, str):
    """
    Keputusan final entry berdasarkan analisis.

    1. Quality == AVOID? → False (jangan trade)
    2. ML confidence >= threshold? → True (entry OK)
    3. ML confidence < threshold? → False (tunggu)
    """

    # Contoh output:
    # True,  "Entry OK: ML 68% >= threshold 60% (score=95)"
    # False, "Wait: ML 55% < threshold 70% (need +15%)"
    # False, "Market quality: AVOID (score=20)"

---

Logging

def get_threshold_summary(analysis) -> str:
    """
    Output: "Market: EXCELLENT (score=95) → Threshold: 60%"
    """

Contoh log di main_live.py:

[14:30] Market: EXCELLENT (score=95) → Threshold: 60%
[14:35] Entry OK: ML 68% >= threshold 60% (score=95)
[15:00] Market: MODERATE (score=55) → Threshold: 70%
[15:05] Wait: ML 62% < threshold 70% (need +8%)
[04:00] Market: AVOID (score=15) → Threshold: 85%

---

Ringkasan Visual

Kondisi Market Saat Ini
    |
    v
6 Faktor Dianalisis:
├── Session     ±20 poin
├── Regime      ±15 poin
├── Volatility  ±10 poin
├── Trend       ±10 poin
├── SMC         ±10 poin
└── ML          ±5 poin
    |
    v
Score (0-100)
    |
    v
Quality Level:
├── EXCELLENT (80+) → Threshold 60%
├── GOOD (65-79)    → Threshold 65%
├── MODERATE (50-64)→ Threshold 70%
├── POOR (35-49)    → Threshold 80%
└── AVOID (<35)     → Threshold 85% / SKIP
    |
    v
ML Confidence >= Threshold?
├── YES → ENTRY diizinkan
└── NO  → TUNGGU