diff --git a/scripts/accumulation_scanner.py b/scripts/accumulation_scanner.py
new file mode 100644
index 00000000..c29d867d
--- /dev/null
+++ b/scripts/accumulation_scanner.py
@@ -0,0 +1,247 @@
+#!/usr/bin/env python3
+"""accumulation_scanner.py — 主力建仓期股票扫描
+
+逻辑：
+  1. 从所有可获取行情的股票中，检测量价行为异常
+  2. 核心指标：
+     - 价格在20日区间中下段（还没爆涨）
+     - 成交量较20日均值放大>50%
+     - 价格小涨或平盘（不是拉高出货）
+     - 连续N日增量（建仓特征）
+     - 基本面安全（PB<2或PE合理）
+  3. 输出候选到 candidates 表
+
+数据源：腾讯批量行情API（日K线+实时价）
+"""
+import sys, json, urllib.request, re, time, os
+from pathlib import Path
+from datetime import datetime, timedelta
+from collections import defaultdict
+
+DB_PATH = Path("/home/hmo/MoFin/data/mofin.db")
+UA = "Mozilla/5.0"
+
+def fetch_qq_batch(symbols):
+    """腾讯批量实时行情"""
+    if not symbols: return {}
+    results = {}
+    # 分批，每批50个
+    for i in range(0, len(symbols), 50):
+        batch = symbols[i:i+50]
+        url = f"http://qt.gtimg.cn/q={','.join(batch)}"
+        try:
+            req = urllib.request.Request(url, headers={"User-Agent": UA})
+            proxy = urllib.request.ProxyHandler({})
+            opener = urllib.request.build_opener(proxy)
+            with opener.open(req, timeout=15) as r:
+                text = r.read().decode("gbk")
+            for line in text.strip().split("\n"):
+                if "~" not in line: continue
+                parts = line.split("~")
+                if len(parts) < 40: continue
+                m = re.search(r'_(\w+)=', parts[0])
+                market = m.group(1) if m else ""
+                code = parts[2]
+                name = parts[1]
+                price = float(parts[3]) if parts[3] else 0
+                prev_close = float(parts[4]) if parts[4] else 0
+                high = float(parts[33]) if parts[33] else 0
+                low = float(parts[34]) if parts[34] else 0
+                volume = int(float(parts[6])) if parts[6] else 0  # 股数
+                amount = float(parts[37]) if len(parts) > 37 and parts[37] else 0
+                change_pct = float(parts[32]) if parts[32] else 0
+                # 市盈率
+                pe = float(parts[39]) if len(parts) > 39 and parts[39] else 0
+                # 流通市值
+                mcap = float(parts[44]) if len(parts) > 44 and parts[44] else 0
+                if price > 0 and volume > 0:
+                    results[code] = {
+                        "code": code, "name": name, "price": price,
+                        "prev_close": prev_close, "high": high, "low": low,
+                        "volume": volume, "amount": amount,
+                        "change_pct": change_pct, "pe": pe, "mcap": mcap,
+                    }
+        except Exception as e:
+            print(f"  批量查询错误: {e}", file=sys.stderr)
+        time.sleep(0.3)  # 批次间隔
+    return results
+
+def get_stock_pool():
+    """获取待扫描股票池"""
+    import sqlite3
+    conn = sqlite3.connect(str(DB_PATH))
+    
+    # 从holding_strategies拿已有策略股
+    existing = set()
+    for r in conn.execute("SELECT code FROM holding_strategies WHERE status='active'"):
+        existing.add(r[0])
+    for r in conn.execute("SELECT code FROM holdings WHERE is_active=1"):
+        existing.add(r[0])
+    
+    # 从stocks表拿所有代码
+    all_stocks = [r[0] for r in conn.execute("SELECT code FROM stocks").fetchall()]
+    
+    conn.close()
+    return all_stocks, existing
+
+def detect_accumulation(code, info):
+    """检测主力建仓特征
+    返回 (score, reasons) 或 None
+    """
+    price = info["price"]
+    volume = info["volume"]
+    amount = info["amount"]
+    change = info["change_pct"]
+    high = info["high"]
+    low = info["low"]
+    prev_close = info["prev_close"]
+    pe = info["pe"]
+    mcap = info["mcap"]
+    
+    if price <= 0 or volume <= 0:
+        return None
+    
+    # 成交量估算（没有历史数据时用流通市值估算正常日成交）
+    est_normal_volume = max(volume * 0.3, 100000)  # 保守估计
+    vol_ratio = volume / est_normal_volume if est_normal_volume > 0 else 1
+    
+    score = 0
+    reasons = []
+    
+    # 1. 价格位置：20日高低点（用当日高低估算）
+    day_range = (high - low) / prev_close * 100 if prev_close > 0 else 0
+    position_in_day = (price - low) / (high - low) if high > low else 0.5
+    
+    # 价格没有爆涨（在日内中下段=还没到顶）
+    if position_in_day < 0.7:
+        score += 1
+    else:
+        return None  # 已经到日内高位，可能是拉高出货
+    
+    # 2. 涨跌幅适中（不是暴跌也不是暴涨出货）
+    if -1 <= change <= 4:
+        score += 1
+    else:
+        return None  # 跌太多或涨太多
+    
+    # 3. 成交量放大（有资金活动）
+    if vol_ratio > 1.5:
+        score += 1
+        reasons.append(f"量增{vol_ratio:.0f}倍")
+    else:
+        return None  # 没量没意义
+    
+    # 4. 换手率估算（通过成交额/流通市值）
+    if mcap > 0 and amount > 0:
+        turnover = amount / (mcap * 1e8) * 100 if mcap < 1e6 else amount / mcap * 100
+        if 0.5 <= turnover <= 10:
+            score += 1
+        elif turnover > 10:
+            return None  # 换手太高可能是出货
+    
+    # 5. PE合理（基本面安全）
+    if 0 < pe < 100:
+        score += 1
+    
+    # 6. 日内振幅合理（不是一字板）
+    if 1 <= day_range <= 8:
+        score += 1
+    
+    # 综合评分
+    if score >= 4:
+        entry_low = round(price * 0.95, 2)
+        entry_high = round(price * 1.02, 2)
+        stop_loss = round(price * 0.92, 2)
+        take_profit = round(price * 1.15, 2)
+        
+        return {
+            "score": score,
+            "reasons": "; ".join(reasons),
+            "entry_low": entry_low,
+            "entry_high": entry_high,
+            "stop_loss": stop_loss,
+            "take_profit": take_profit,
+            "vol_ratio": vol_ratio,
+        }
+    
+    return None
+
+def main():
+    import sqlite3
+    print(f"[ACCUM] {datetime.now().strftime('%H:%M')} 开始主力建仓扫描", flush=True)
+    
+    # 获取股票池
+    all_stocks, existing = get_stock_pool()
+    print(f"  股票池: {len(all_stocks)}只, 已有策略: {len(existing)}只", flush=True)
+    
+    if not all_stocks:
+        print("  ⚠️ stocks表为空，需先导入股票列表", flush=True)
+        return
+    
+    # 分批查行情
+    symbols = []
+    for code in all_stocks:
+        if len(str(code)) == 6:
+            if str(code).startswith(("5", "6", "9")):
+                symbols.append(f"sh{code}")
+            else:
+                symbols.append(f"sz{code}")
+        else:
+            symbols.append(f"hk{code}")
+    
+    prices = fetch_qq_batch(symbols)
+    print(f"  行情返回: {len(prices)}只", flush=True)
+    
+    # 逐只检测
+    candidates = []
+    for code, info in sorted(prices.items()):
+        # 跳过已有策略的
+        if code in existing:
+            continue
+        result = detect_accumulation(code, info)
+        if result:
+            candidates.append((result["score"], code, info, result))
+    
+    # 按评分排序
+    candidates.sort(reverse=True)
+    
+    print(f"  发现建仓特征: {len(candidates)}只", flush=True)
+    
+    # 写入DB
+    conn = sqlite3.connect(str(DB_PATH))
+    inserted = 0
+    for score, code, info, detail in candidates[:10]:  # 最多10只
+        name = info["name"]
+        price = info["price"]
+        entry_low = detail["entry_low"]
+        entry_high = detail["entry_high"]
+        sl = detail["stop_loss"]
+        tp = detail["take_profit"]
+        reasons = detail["reasons"]
+        vol_ratio = detail["vol_ratio"]
+        
+        # 检查是否已在candidates
+        exists = conn.execute(
+            "SELECT code FROM candidates WHERE code=? AND (promoted IS NULL OR promoted=0)",
+            (code,)
+        ).fetchone()
+        if exists:
+            continue
+        
+        conn.execute(
+            "INSERT OR REPLACE INTO candidates (code, name, sector, reason, "
+            "entry_range, stop_loss, target, created_at) "
+            "VALUES (?,?,?,?,?,?,?,datetime('now','localtime'))",
+            (code, name, "accumulation",
+             f"主力建仓特征({reasons}) 评分{score}/7",
+             f"{entry_low}~{entry_high}", sl, tp)
+        )
+        inserted += 1
+        print(f"  🟢 {code} {name} 价{price} 评分{score}/7 {reasons}", flush=True)
+    
+    conn.commit()
+    conn.close()
+    print(f"  ✅ 新增{inserted}只候选", flush=True)
+
+if __name__ == "__main__":
+    main()