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AI가 evaluate() 메서드 내부에 또 다른 evaluate() 함수를 중첩 정의하는 실수로 생성된 IndentationError 수정. 각 파일별 수정 내용: - v20260220_210124_evolved.py: 중첩 def evaluate 제거, 상수/로직 8칸으로 정규화 - v20260220_210159_evolved.py: 중첩 def evaluate 제거, 16칸→8칸 들여쓰기 수정 - v20260220_210244_evolved.py: 12칸→8칸 들여쓰기 수정 Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
89 lines
4.1 KiB
Python
89 lines
4.1 KiB
Python
"""Auto-generated strategy: v20260220_210244
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Generated at: 2026-02-20T21:02:44.387355+00:00
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Rationale: Auto-evolved from 6 failures. Primary failure markets: ['US_AMEX', 'US_NYSE', 'US_NASDAQ']. Average loss: -194.69
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"""
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from __future__ import annotations
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from typing import Any
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from src.strategies.base import BaseStrategy
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class Strategy_v20260220_210244(BaseStrategy):
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"""Strategy: v20260220_210244"""
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def evaluate(self, market_data: dict[str, Any]) -> dict[str, Any]:
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from datetime import datetime
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# Extract required data points safely
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current_price = market_data.get("current_price")
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price_change_pct = market_data.get("price_change_pct")
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volume_ratio = market_data.get("volume_ratio")
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rsi = market_data.get("rsi")
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timestamp_str = market_data.get("timestamp")
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market_name = market_data.get("market")
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stock_code = market_data.get("stock_code", "UNKNOWN")
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# Default action is HOLD with conservative confidence and rationale
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action = "HOLD"
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confidence = 50
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rationale = f"No strong BUY signal for {stock_code} or awaiting more favorable conditions after avoiding known failure patterns."
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# --- 1. Failure Pattern Avoidance Filters ---
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# A. Avoid low-priced (penny) stocks
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if current_price is not None and current_price < 5.0:
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return {
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"action": "HOLD",
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"confidence": 50,
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"rationale": f"AVOID {stock_code}: Stock price (${current_price:.2f}) is below minimum threshold ($5.00) for BUY action. Identified past failures on highly volatile, low-priced stocks."
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}
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# B. Avoid initiating BUY trades during identified high-volatility hours
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if timestamp_str:
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try:
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trade_hour = datetime.fromisoformat(timestamp_str).hour
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if trade_hour in [14, 20]:
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return {
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"action": "HOLD",
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"confidence": 50,
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"rationale": f"AVOID {stock_code}: Trading during historically volatile hour ({trade_hour} UTC) where previous BUYs resulted in losses. Prefer to observe market stability."
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}
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except ValueError:
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pass
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# C. Be cautious with extreme momentum spikes
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if volume_ratio is not None and price_change_pct is not None:
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if volume_ratio >= 9.0 and price_change_pct >= 15.0:
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return {
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"action": "HOLD",
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"confidence": 50,
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"rationale": f"AVOID {stock_code}: Extreme short-term momentum detected (price change: +{price_change_pct:.2f}%, volume ratio: {volume_ratio:.1f}x). Historical failures indicate buying into such rapid spikes often leads to reversals."
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}
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# D. Be cautious with "oversold" signals without further confirmation
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if rsi is not None and rsi < 30:
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return {
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"action": "HOLD",
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"confidence": 50,
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"rationale": f"AVOID {stock_code}: Oversold signal (RSI={rsi:.1f}) detected. While often a BUY signal, historical failures on similar 'oversold' trades suggest waiting for stronger confirmation."
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}
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# --- 2. Improved BUY Signal Generation ---
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if volume_ratio is not None and 2.0 <= volume_ratio < 9.0 and \
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price_change_pct is not None and 2.0 <= price_change_pct < 15.0:
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action = "BUY"
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confidence = 70
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rationale = f"BUY {stock_code}: Moderate momentum detected (price change: +{price_change_pct:.2f}%, volume ratio: {volume_ratio:.1f}x). Passed filters for price and extreme momentum, avoiding past failure patterns."
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if market_name in ["US_AMEX", "US_NASDAQ"]:
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confidence = max(60, confidence - 5)
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rationale += f" Adjusted confidence for {market_name} market characteristics."
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elif market_name == "US_NYSE":
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confidence = max(65, confidence)
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confidence = max(50, min(85, confidence))
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return {"action": action, "confidence": confidence, "rationale": rationale}
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