7 Sprints 全部完成: Sprint 0: 基础设施 (DataManager + MariaDB) Sprint 1: 因子引擎 (34因子/12分类) Sprint 2: VectorBT 回测 (5策略+截面) Sprint 3: Optuna 优化 (+Walk-Forward) Sprint 4: ML 模型 (LightGBM+CatBoost) Sprint 5: Qwen 情绪因子 (三源新闻+日期对齐) Sprint 6: Agent 系统 (4Agent+日报.md/.html) 生产加固 (15项): Tushare双源fallback, SSH自动恢复, pool_pre_ping, save_daily先删后插, load_dotenv绝对路径, 日报5d/20d修复, RiskAgent改上证指数, 昨日对比+数据截止, mac_report utf8mb4, CLAUDE-*.md 9条已知Bug, demo全参数化, djapi数据源归一化, indexDatas API修正 Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
34 lines
934 B
Python
34 lines
934 B
Python
"""
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均线交叉策略。
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短期均线上穿长期均线 → 买入
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短期均线下穿长期均线 → 平仓
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"""
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import pandas as pd
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from backtest.base import BaseStrategy
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from backtest.signal import cross_signal
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class SMACrossStrategy(BaseStrategy):
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"""快慢均线交叉策略。"""
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category = "trend"
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def __init__(self, fast: int = 5, slow: int = 20):
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self.fast = fast
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self.slow = slow
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self.name = f"sma_cross_{fast}_{slow}"
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def generate_signals(self, factor_df: pd.DataFrame) -> pd.Series:
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if "close" not in factor_df.columns:
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raise ValueError("factor_df 缺少 'close' 列")
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close = factor_df["close"]
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min_p = min(self.fast, self.slow)
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ma_fast = close.rolling(window=self.fast, min_periods=self.fast).mean()
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ma_slow = close.rolling(window=self.slow, min_periods=self.slow).mean()
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return cross_signal(ma_fast, ma_slow)
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