Initial commit: cc-cursor 全链路量化研究平台

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>

finance/backtest/strategies/momentum_breakout.py

@@ -0,0 +1,52 @@
+"""
+动量突破策略。
+
+价格突破 N 日新高 → 买入
+价格跌破 N 日均线 → 平仓
+"""
+
+import pandas as pd
+
+from backtest.base import BaseStrategy
+from backtest.signal import factor_to_threshold_signal
+
+
+class MomentumBreakoutStrategy(BaseStrategy):
+    """动量突破策略。"""
+
+    category = "trend"
+
+    def __init__(self, lookback: int = 20, exit_period: int = 10):
+        self.lookback = lookback
+        self.exit_period = exit_period
+        self.name = f"mom_breakout_{lookback}"
+
+    def generate_signals(self, factor_df: pd.DataFrame) -> pd.Series:
+        if "close" not in factor_df.columns:
+            raise ValueError("factor_df 缺少 'close' 列")
+
+        close = factor_df["close"]
+        # 买入信号：突破 N 日新高
+        rolling_high = close.rolling(window=self.lookback, min_periods=self.lookback).max()
+        breakout = close >= rolling_high.shift(1)
+
+        # 平仓信号：跌破 exit 日均线
+        exit_ma = close.rolling(window=self.exit_period, min_periods=self.exit_period).mean()
+
+        signals = pd.Series(0, index=close.index)
+        signals[breakout] = 1
+        signals[close < exit_ma] = 0
+
+        return self._dedup(signals)
+
+    @staticmethod
+    def _dedup(signals: pd.Series) -> pd.Series:
+        """只保留第一个买入和第一个卖出信号。"""
+        result = signals.copy()
+        prev = -1
+        for i in range(len(result)):
+            if result.iloc[i] == prev:
+                result.iloc[i] = -1
+            else:
+                prev = result.iloc[i]
+        return result[result != -1].reindex(signals.index).fillna(-1)