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# FILE: mcp_server/tier_classifier.py
# PURPOSE: Tier Classifier - Opportunity Quality Classification
# VERSION: 3.0 INSTITUTIONAL
# ═══════════════════════════════════════════════════════════
"""
Tier Classifier - Opportunity Quality Classification
Implements 4-tier quality system instead of binary approve/reject
TIERS:
🟢 Elite (8.0-10.0 score, 75%+ prob, 2.5+ R:R)
• Win rate target: 75%+
• Position size: 100% (2% risk)
• Recommendation: TRADE IMMEDIATELY
🟡 Professional (6.5-7.9 score, 65%+ prob, 2.0+ R:R)
• Win rate target: 65-74%
• Position size: 75% (1.5% risk)
• Recommendation: TRADE WITH CAUTION
🟠 Speculative (5.0-6.4 score, 55%+ prob, 1.5+ R:R)
• Win rate target: 55-64%
• Position size: 50% (1% risk)
• Recommendation: EXPERIENCED TRADERS ONLY
🔴 High Risk (4.0-4.9 score)
• Win rate target: <55%
• Position size: 25% (0.5% risk)
• Recommendation: NOT RECOMMENDED, paper trade only
⛔ Not Recommended (<4.0 score)
• Win rate target: <50%
• Position size: 0%
• Recommendation: SKIP
"""
from typing import Literal
from loguru import logger
TierType = Literal["elite", "professional", "speculative", "high_risk", "not_recommended"]
class TierClassifier:
"""
Классификация торговых возможностей по уровням качества
Заменяет бинарный approve/reject на 5-уровневую систему
для более гранулярного управления риском
"""
@staticmethod
def classify(
score: float,
probability: float,
risk_reward: float
) -> TierType:
"""
Classify opportunity into quality tier
Args:
score: Confluence score (0-10, normalized)
probability: Win probability (0-1)
risk_reward: Risk/reward ratio
Returns:
Tier classification
"""
# 🟢 Elite Tier
if score >= 8.0 and probability >= 0.75 and risk_reward >= 2.5:
logger.debug(f"Classified as ELITE: score={score:.1f}, prob={probability:.2f}, rr={risk_reward:.1f}")
return "elite"
# 🟡 Professional Tier
elif score >= 6.5 and probability >= 0.65 and risk_reward >= 2.0:
logger.debug(f"Classified as PROFESSIONAL: score={score:.1f}, prob={probability:.2f}, rr={risk_reward:.1f}")
return "professional"
# 🟠 Speculative Tier
elif score >= 5.0 and probability >= 0.55 and risk_reward >= 1.5:
logger.debug(f"Classified as SPECULATIVE: score={score:.1f}, prob={probability:.2f}, rr={risk_reward:.1f}")
return "speculative"
# 🔴 High Risk
elif score >= 4.0:
logger.debug(f"Classified as HIGH_RISK: score={score:.1f}")
return "high_risk"
# ⛔ Not Recommended
else:
logger.debug(f"Classified as NOT_RECOMMENDED: score={score:.1f}")
return "not_recommended"
@staticmethod
def get_recommendation(tier: TierType) -> str:
"""Get recommendation text for tier"""
recommendations = {
"elite": "✅ ОТКРЫВАТЬ - Отличный setup с высокой вероятностью успеха (75%+)",
"professional": "⚠️ ОСТОРОЖНО - Хороший setup, уменьшите размер позиции (65-74% вероятность)",
"speculative": "⚠️⚠️ ВЫСОКИЙ РИСК - Только для опытных, минимальный размер (55-64% вероятность)",
"high_risk": "🔴 НЕ РЕКОМЕНДУЕТСЯ - Низкая confluence (<55%), paper trade only",
"not_recommended": "⛔ ПРОПУСТИТЬ - Setup слишком слабый (<50% вероятность)"
}
return recommendations.get(tier, "Unknown tier")
@staticmethod
def get_position_size_multiplier(tier: TierType) -> float:
"""
Get position size multiplier based on tier
Returns:
Multiplier for base position size
Base = 2% risk, multiplier scales it down for lower tiers
"""
multipliers = {
"elite": 1.0, # 100% = 2% risk
"professional": 0.75, # 75% = 1.5% risk
"speculative": 0.5, # 50% = 1% risk
"high_risk": 0.25, # 25% = 0.5% risk
"not_recommended": 0.0 # 0% = don't trade
}
return multipliers.get(tier, 0.0)
@staticmethod
def get_tier_color(tier: TierType) -> str:
"""Get color emoji for tier"""
colors = {
"elite": "🟢",
"professional": "🟡",
"speculative": "🟠",
"high_risk": "🔴",
"not_recommended": "⛔"
}
return colors.get(tier, "⚪")
@staticmethod
def get_tier_name(tier: TierType) -> str:
"""Get display name for tier"""
names = {
"elite": "Elite",
"professional": "Professional",
"speculative": "Speculative",
"high_risk": "High Risk",
"not_recommended": "Not Recommended"
}
return names.get(tier, "Unknown")
@staticmethod
def get_expected_win_rate(tier: TierType) -> float:
"""
Get expected win rate for tier
Returns:
Expected win rate (0-1)
"""
win_rates = {
"elite": 0.75,
"professional": 0.68,
"speculative": 0.58,
"high_risk": 0.48,
"not_recommended": 0.35
}
return win_rates.get(tier, 0.50)
@staticmethod
def should_trade(tier: TierType) -> bool:
"""
Should this tier be traded?
Returns:
True if tier is tradeable (elite/professional/speculative)
"""
return tier in ["elite", "professional", "speculative"]
