update

AGENTS.md

@@ -180,6 +180,8 @@ AlphaX 是一个以 `Python + FastAPI + PostgreSQL + Docker + 静态 HTML` 组
   - 市场环境识别中心，第一版基于市场快照、BTC/ETH 涨跌、山寨涨跌广度、强势/大跌数量和 funding 热度识别 `risk_off`、`btc_main_uptrend`、`altcoin_rotation`、`sideways_chop`、`meme_frenzy`、`unknown`。
 - `app/core/global_risk.py`
   - paper trading 全局风控门禁。单币机会进入开仓或挂单成交前，需要先检查市场环境和账户风险；critical 禁止新开仓，high 只允许高质量机会。
+- `app/core/trade_math.py`
+  - 多空通用交易数学中心。负责 side 归一、开仓/平仓滑点价、PnL、止损/止盈/移动止盈触发、保护价收紧比较。paper/live 不应各自实现一套多空收益和触发判断。
 - `app/core/order_lifecycle.py`
   - 挂单生命周期决策中心。负责限价单是否触价、是否过期、是否远离入场、RR 与入场距离计算；不写 DB、不取消订单、不调用交易所。paper/live 适配层只能消费它的 `OrderLifecycleDecision`。
 - `app/core/trailing_stop.py`
@@ -187,7 +189,8 @@ AlphaX 是一个以 `Python + FastAPI + PostgreSQL + Docker + 静态 HTML` 组
 - `app/core/position_health.py`
   - 已开仓仓位的健康检查中心。它不是入场规则，而是持仓后判断“机会是否仍按原计划运行”：超时未启动会收紧保护价或提前退出，浮盈大幅回吐且未触发移动止盈会提前退出，市场进入 critical 时未受保护的微盈利/弱势仓位可提前退出。
 - 交易执行能力必须按“决策核心 -> 执行适配 -> 账本记录”分层：移动止盈、仓位失效保护、动态杠杆、仓位 sizing、订单触发、账户风控都应有可被 paper trading 和 live trading 复用的核心模块。不要把这些规则直接写死在 `app/db/paper_trading.py`、`routes_live_trading.py` 或页面 JS 中。
-- 多策略基础设施当前内置 `main_composite_v1`、`box_retest_4h_v1`、`box_retest_1h_v1`、`volume_ignition_1h_v1`、`compression_breakout_4h_v1`、`intraday_momentum_15m_v1`。`box_breakout_pullback_4h` / `box_breakout_pullback_1h`、`vp_fly_1h_current`、`short_tf_15m_ignition` 等只是因子，只有和入场确认、风控、失效条件组成完整剧本后，才作为对应策略信号写入 `strategy_signals`。
+- 交易执行层已支持 `side=long/short`：paper trading 开仓、平仓、PnL、TP/SL、移动止盈、持仓健康和挂单触价都按 side 处理。当前已注册第一版独立空头策略 `breakdown_retest_short_1h_v1`，但这不代表发现/确认层已经全量接入空头扫描；新增做空必须继续使用独立 `strategy_code`、触发条件、失效条件和复盘口径，不能把多头策略简单反向。
+- 多策略基础设施当前内置 `main_composite_v1`、`box_retest_4h_v1`、`box_retest_1h_v1`、`volume_ignition_1h_v1`、`compression_breakout_4h_v1`、`intraday_momentum_15m_v1`、`breakdown_retest_short_1h_v1`。`box_breakout_pullback_4h` / `box_breakout_pullback_1h`、`vp_fly_1h_current`、`short_tf_15m_ignition`、`breakdown_retest_1h_short` 等只是因子，只有和入场确认、风控、失效条件组成完整剧本后，才作为对应策略信号写入 `strategy_signals`。
   - 确认层也会应用同一市场风控语义：`risk_level=critical` 且 `position_multiplier=0` 时，强势发现仍可记录为观察，但不能输出 `buy_now` 或新挂单动作；已有活跃可交易推荐会被降级为观察并写入 `market_risk_gate`。
 
 ## 5. 数据与状态中心

app/core/factor_roles.py

@@ -31,6 +31,9 @@ VALID_FACTOR_ROLES = {
 DEFAULT_FACTOR_ROLES: dict[str, str] = {
     "box_breakout_pullback_4h": TRIGGER,
     "box_breakout_pullback_1h": TRIGGER,
+    "breakdown_retest_1h_short": TRIGGER,
+    "retest_reject_15m_short": ENTRY,
+    "market_risk_off_short": CONFIRMATION,
     "vp_fly_1h_current": TRIGGER,
     "volume_consecutive_1h": CONFIRMATION,
     "volume_divergence_1h": RISK,

app/core/signal_taxonomy.py

@@ -24,6 +24,9 @@ SIGNAL_CODE_LABELS = {
     "compression_surge_4h": "4H压缩放量",
     "box_breakout_pullback_1h": "1H箱体突破回踩",
     "box_breakout_pullback_4h": "4H箱体突破回踩",
+    "breakdown_retest_1h_short": "1H破位反抽做空",
+    "retest_reject_15m_short": "15min反抽失败",
+    "market_risk_off_short": "弱势环境空头确认",
     "ignition_1h_current": "1H当前起爆点",
     "ignition_4h_current": "4H当前起爆点",
     "ignition_d1_current": "日线当前起爆点",
@@ -67,6 +70,9 @@ _PATTERNS = [
     ("static_accum_4h", ("静K蓄力", "静K旁路")),
     ("box_breakout_pullback_1h", ("1H", "箱体", "突破", "回踩")),
     ("box_breakout_pullback_4h", ("4H", "箱体", "突破", "回踩")),
+    ("breakdown_retest_1h_short", ("1H", "破位", "反抽", "做空")),
+    ("retest_reject_15m_short", ("15min", "反抽失败")),
+    ("market_risk_off_short", ("risk_off", "空头")),
     ("higher_lows_4h", ("底部抬高",)),
     ("compression_surge_4h", ("压缩放量",)),
     ("ignition_stale", ("历史起爆点", "起爆点已过期", "旧起爆")),

app/core/strategy_registry.py

@@ -11,6 +11,7 @@ BOX_RETEST_4H_STRATEGY = "box_retest_4h_v1"
 VOLUME_IGNITION_1H_STRATEGY = "volume_ignition_1h_v1"
 COMPRESSION_BREAKOUT_4H_STRATEGY = "compression_breakout_4h_v1"
 INTRADAY_MOMENTUM_15M_STRATEGY = "intraday_momentum_15m_v1"
+BREAKDOWN_RETEST_SHORT_1H_STRATEGY = "breakdown_retest_short_1h_v1"
 
 
 @dataclass(frozen=True)
@@ -139,6 +140,28 @@ STRATEGY_DEFINITIONS: dict[str, StrategyDefinition] = {
             "dynamic_leverage_min": 3,
         },
     ),
+    BREAKDOWN_RETEST_SHORT_1H_STRATEGY: StrategyDefinition(
+        strategy_code=BREAKDOWN_RETEST_SHORT_1H_STRATEGY,
+        strategy_name="1H破位反抽做空",
+        description="箱体或关键均线破位后反抽失败的空头策略；只用于独立空头样本，不与多头突破策略共享入场门槛。",
+        mode="paper_only",
+        entry_gate_config={
+            "direction": "short",
+            "min_entry_score_buy_now": 2,
+            "min_entry_score_wait_pullback": 1,
+            "min_rr_buy_now": 1.5,
+            "breakdown_distance_wait_pct": 10,
+            "max_retest_deviation_pct": 8,
+        },
+        paper_config={
+            "entry_min_rr": 1.8,
+            "order_min_rr": 1.8,
+            "order_min_distance_to_entry_pct": 0,
+            "order_require_current_trigger": True,
+            "dynamic_leverage_enabled": True,
+            "dynamic_leverage_min": 2,
+        },
+    ),
 }
 
 

app/core/trade_math.py

@@ -0,0 +1,112 @@
+"""Side-aware execution math shared by paper and live trading adapters."""
+
+from __future__ import annotations
+
+
+def safe_float(value, default: float = 0.0) -> float:
+    try:
+        if value is None or value == "":
+            return default
+        return float(value)
+    except Exception:
+        return default
+
+
+def normalize_side(side: str | None) -> str:
+    return "short" if str(side or "").strip().lower() == "short" else "long"
+
+
+def open_price(side: str, current_price: float, slippage_pct: float = 0.0) -> float:
+    price = safe_float(current_price)
+    slip = max(0.0, safe_float(slippage_pct))
+    if price <= 0:
+        return 0.0
+    if normalize_side(side) == "short":
+        return round(price * (1 - slip / 100), 12)
+    return round(price * (1 + slip / 100), 12)
+
+
+def close_price(side: str, current_price: float, slippage_pct: float = 0.0) -> float:
+    price = safe_float(current_price)
+    slip = max(0.0, safe_float(slippage_pct))
+    if price <= 0:
+        return 0.0
+    if normalize_side(side) == "short":
+        return round(price * (1 + slip / 100), 12)
+    return round(price * (1 - slip / 100), 12)
+
+
+def pnl_pct(side: str, entry_price: float, current_price: float) -> float:
+    entry = safe_float(entry_price)
+    price = safe_float(current_price)
+    if entry <= 0 or price <= 0:
+        return 0.0
+    if normalize_side(side) == "short":
+        return round((entry / price - 1) * 100, 4)
+    return round((price / entry - 1) * 100, 4)
+
+
+def stop_loss_distance_pct(side: str, entry_price: float, stop_loss: float) -> float:
+    entry = safe_float(entry_price)
+    stop = safe_float(stop_loss)
+    if entry <= 0 or stop <= 0:
+        return 0.0
+    if normalize_side(side) == "short":
+        return max(0.0, (stop / entry - 1) * 100)
+    return max(0.0, (1 - stop / entry) * 100)
+
+
+def should_stop_loss(side: str, current_price: float, stop_loss: float) -> bool:
+    price = safe_float(current_price)
+    stop = safe_float(stop_loss)
+    if price <= 0 or stop <= 0:
+        return False
+    if normalize_side(side) == "short":
+        return price >= stop
+    return price <= stop
+
+
+def should_take_profit(side: str, current_price: float, target: float) -> bool:
+    price = safe_float(current_price)
+    tp = safe_float(target)
+    if price <= 0 or tp <= 0:
+        return False
+    if normalize_side(side) == "short":
+        return price <= tp
+    return price >= tp
+
+
+def should_hit_trailing_stop(side: str, current_price: float, trailing_stop: float) -> bool:
+    price = safe_float(current_price)
+    stop = safe_float(trailing_stop)
+    if price <= 0 or stop <= 0:
+        return False
+    if normalize_side(side) == "short":
+        return price >= stop
+    return price <= stop
+
+
+def tighter_stop(side: str, current_stop: float, candidate_stop: float) -> float:
+    current = safe_float(current_stop)
+    candidate = safe_float(candidate_stop)
+    if candidate <= 0:
+        return current
+    if current <= 0:
+        return candidate
+    if normalize_side(side) == "short":
+        return min(current, candidate)
+    return max(current, candidate)
+
+
+__all__ = [
+    "close_price",
+    "normalize_side",
+    "open_price",
+    "pnl_pct",
+    "safe_float",
+    "should_hit_trailing_stop",
+    "should_stop_loss",
+    "should_take_profit",
+    "stop_loss_distance_pct",
+    "tighter_stop",
+]

app/core/trailing_stop.py

@@ -9,6 +9,8 @@ from __future__ import annotations
 
 from dataclasses import dataclass, field
 
+from app.core.trade_math import normalize_side, tighter_stop
+
 
 def _safe_float(value, default: float = 0.0) -> float:
     try:
@@ -158,12 +160,20 @@ def evaluate_trailing_stop(
             detail={"reason": "below_activation"},
         )
 
+    side = normalize_side(position.get("side"))
     distance_pct = _safe_float(profile.get("distance_pct"), cfg.get("distance_pct"))
-    protection_floor = entry_price * (1 + _safe_float(cfg.get("min_lock_profit_pct")) / 100)
+    if side == "short":
-    candidate = current_price * (1 - distance_pct / 100)
+        protection_floor = entry_price * (1 - _safe_float(cfg.get("min_lock_profit_pct")) / 100)
-    new_trail = round(max(current_trail, protection_floor, candidate), 12)
+        candidate = current_price * (1 + distance_pct / 100)
+        new_trail = round(tighter_stop(side, current_trail, min(protection_floor, candidate)), 12)
+    else:
+        protection_floor = entry_price * (1 + _safe_float(cfg.get("min_lock_profit_pct")) / 100)
+        candidate = current_price * (1 - distance_pct / 100)
+        new_trail = round(tighter_stop(side, current_trail, max(protection_floor, candidate)), 12)
     activated = current_trail <= 0 and new_trail > 0
-    moved = current_trail > 0 and new_trail > current_trail + 1e-12
+    moved = current_trail > 0 and (
+        new_trail < current_trail - 1e-12 if side == "short" else new_trail > current_trail + 1e-12
+    )
     if not activated and not moved:
         return TrailingStopDecision(
             action="hold",

app/db/paper_trading.py

@@ -16,6 +16,17 @@ from app.core.order_lifecycle import (
 )
 from app.core.position_health import evaluate_position_health
 from app.core.trailing_stop import evaluate_trailing_stop, normalize_trailing_config
+from app.core.trade_math import (
+    close_price as side_close_price,
+    normalize_side,
+    open_price as side_open_price,
+    pnl_pct as side_pnl_pct,
+    should_hit_trailing_stop,
+    should_stop_loss,
+    should_take_profit,
+    stop_loss_distance_pct as side_stop_loss_distance_pct,
+    tighter_stop,
+)
 from app.core.strategy_registry import normalize_strategy_code, strategy_label, strategy_paper_config
 from app.db.schema import get_conn
 from app.db.system_logs import record_system_error
@@ -317,26 +328,20 @@ def _parse_time(value: str):
         return None
 
 
-def _open_price(current_price: float, config: dict | None = None) -> float:
+def _open_price(current_price: float, config: dict | None = None, side: str = "long") -> float:
-    return round(current_price * (1 + default_slippage_pct(config) / 100), 12)
+    return side_open_price(side, current_price, default_slippage_pct(config))
 
 
-def _close_price(current_price: float, config: dict | None = None) -> float:
+def _close_price(current_price: float, config: dict | None = None, side: str = "long") -> float:
-    return round(current_price * (1 - default_slippage_pct(config) / 100), 12)
+    return side_close_price(side, current_price, default_slippage_pct(config))
 
 
-def _trade_pnl_pct(entry_price: float, current_price: float) -> float:
+def _trade_pnl_pct(entry_price: float, current_price: float, side: str = "long") -> float:
-    if entry_price <= 0 or current_price <= 0:
+    return side_pnl_pct(side, entry_price, current_price)
-        return 0.0
-    return round((current_price / entry_price - 1) * 100, 4)
 
 
 def _stop_loss_distance_pct(side: str, entry_price: float, stop_loss: float) -> float:
-    if entry_price <= 0 or stop_loss <= 0:
+    return side_stop_loss_distance_pct(side, entry_price, stop_loss)
-        return 0.0
-    if str(side or "long").lower() == "short":
-        return max(0.0, (stop_loss / entry_price - 1) * 100)
-    return max(0.0, (1 - stop_loss / entry_price) * 100)
 
 
 def _stop_loss_leverage_risk_pct(side: str, entry_price: float, stop_loss: float, leverage: float) -> float:
@@ -637,9 +642,9 @@ def _open_trade(conn, rec: dict, current_price: float, event_time: str, config:
     rec_id = _safe_int(rec.get("id"))
     symbol = str(rec.get("symbol") or "").strip().upper()
     plan = _entry_plan(rec)
-    entry_price = _open_price(current_price, cfg)
+    side = normalize_side(plan.get("side") or rec.get("side"))
+    entry_price = _open_price(current_price, cfg, side)
     notional = default_notional_usdt(cfg)
-    side = str(plan.get("side") or rec.get("side") or "long").strip().lower() or "long"
     leverage = default_leverage(cfg)
     stop_loss = _safe_float(plan.get("stop_loss") or rec.get("stop_loss"))
     tp1 = _safe_float(plan.get("tp1") or plan.get("take_profit_1") or rec.get("tp1"))
@@ -735,13 +740,14 @@ def _open_trade(conn, rec: dict, current_price: float, event_time: str, config:
             max_price, min_price, current_price, pnl_pct, fee_usdt,
             source_status, source_action, strategy_version, strategy_code, strategy_signal_id,
             strategy_snapshot_json, factor_roles_json, created_at, updated_at
-        ) VALUES (%s,%s,'long','open',%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,0,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)
+        ) VALUES (%s,%s,%s,'open',%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,0,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)
         ON CONFLICT(recommendation_id) DO NOTHING
         RETURNING id
         """,
         (
             rec_id,
             symbol,
+            side,
             now,
             entry_price,
             qty,
@@ -1062,7 +1068,8 @@ def _fill_paper_order(conn, order: dict, rec: dict, current_price: float, event_
         result["paper_order"] = {"filled": True, "order_id": order["id"], "fill_price": fill_price}
         _push_order_filled_card(order, result, event_time)
         stop_loss = _safe_float(rec.get("stop_loss") or _entry_plan(rec).get("stop_loss") or order.get("stop_loss"))
-        if stop_loss > 0 and current_price <= stop_loss:
+        side = normalize_side(order.get("side") or _entry_plan(rec).get("side") or rec.get("side"))
+        if should_stop_loss(side, current_price, stop_loss):
             trade = conn.execute("SELECT * FROM paper_trades WHERE id=%s", (result["trade_id"],)).fetchone()
             if trade:
                 close_result = _close_trade(conn, dict(trade), current_price, "stop_loss_same_tick", event_time)
@@ -1199,8 +1206,9 @@ def _sync_wait_pullback_order(conn, rec: dict, current_price: float, event_time:
 
 def _close_trade(conn, trade: dict, current_price: float, reason: str, event_time: str, detail: dict | None = None) -> dict:
     entry_price = _safe_float(trade.get("entry_price"))
-    exit_price = _close_price(current_price)
+    side = normalize_side(trade.get("side"))
-    pnl_pct = _trade_pnl_pct(entry_price, exit_price)
+    exit_price = _close_price(current_price, side=side)
+    pnl_pct = _trade_pnl_pct(entry_price, exit_price, side)
     notional = _safe_float(trade.get("notional_usdt"))
     open_fee = _safe_float(trade.get("fee_usdt"))
     close_fee = round(notional * default_fee_rate(), 8)
@@ -1284,7 +1292,9 @@ def _apply_position_health_guard(
     if action == "tighten_stop":
         guard_stop = _safe_float(decision.get("guard_stop"))
         current_trail = _safe_float(trade.get("trailing_stop"))
-        if guard_stop > 0 and guard_stop > current_trail + 1e-12:
+        side = normalize_side(trade.get("side"))
+        next_stop = tighter_stop(side, current_trail, guard_stop)
+        if guard_stop > 0 and abs(next_stop - current_trail) > 1e-12:
             _record_event(
                 conn,
                 trade["id"],
@@ -1297,7 +1307,7 @@ def _apply_position_health_guard(
                 {"position_health": decision},
                 event_time,
             )
-            return {"updated": True, "tightened": True, "trailing_stop": guard_stop, "position_health": decision}
+            return {"updated": True, "tightened": True, "trailing_stop": next_stop, "position_health": decision}
     return {"updated": True, "tightened": False, "position_health": decision}
 
 
@@ -1366,23 +1376,24 @@ def _update_trailing_stop(conn, trade: dict, current_price: float, pnl_pct: floa
 
 def _update_open_trade(conn, trade: dict, current_price: float, event_time: str) -> dict:
     entry_price = _safe_float(trade.get("entry_price"))
+    side = normalize_side(trade.get("side"))
     old_max = _safe_float(trade.get("max_price")) or entry_price
     old_min = _safe_float(trade.get("min_price")) or entry_price
     new_max = max(old_max, current_price)
     new_min = min(old_min, current_price)
-    pnl_pct = _trade_pnl_pct(entry_price, current_price)
+    pnl_pct = _trade_pnl_pct(entry_price, current_price, side)
     stop_loss = _safe_float(trade.get("stop_loss"))
     trailing_stop = _safe_float(trade.get("trailing_stop"))
     tp2 = _safe_float(trade.get("tp2"))
     tp1 = _safe_float(trade.get("tp1"))
     reason = ""
-    if stop_loss > 0 and current_price <= stop_loss:
+    if should_stop_loss(side, current_price, stop_loss):
         reason = "stop_loss"
-    elif trailing_stop > 0 and current_price <= trailing_stop:
+    elif should_hit_trailing_stop(side, current_price, trailing_stop):
         reason = "trailing_stop"
-    elif tp2 > 0 and current_price >= tp2:
+    elif should_take_profit(side, current_price, tp2):
         reason = "tp2"
-    elif tp1 > 0 and current_price >= tp1:
+    elif should_take_profit(side, current_price, tp1):
         reason = "tp1"
 
     if reason:
@@ -1394,7 +1405,7 @@ def _update_open_trade(conn, trade: dict, current_price: float, event_time: str)
     if guard_result.get("closed"):
         return guard_result
     if guard_result.get("tightened"):
-        trailing_stop = max(trailing_stop, _safe_float(guard_result.get("trailing_stop")))
+        trailing_stop = tighter_stop(side, trailing_stop, _safe_float(guard_result.get("trailing_stop")))
 
     conn.execute(
         """
@@ -1797,7 +1808,7 @@ def get_paper_trading_performance(days: int = 30) -> dict:
     }
 
 
-def list_paper_trades(limit: int = 50, offset: int = 0, status: str = "", strategy_code: str = "") -> dict:
+def list_paper_trades(limit: int = 50, offset: int = 0, status: str = "", strategy_code: str = "", side: str = "") -> dict:
     limit = max(1, min(_safe_int(limit, 50), 200))
     offset = max(0, _safe_int(offset, 0))
     status = str(status or "").strip()
@@ -1811,6 +1822,10 @@ def list_paper_trades(limit: int = 50, offset: int = 0, status: str = "", strate
     if strategy_code:
         clauses.append("strategy_code=%s")
         params.append(normalize_strategy_code(strategy_code))
+    side = str(side or "").strip().lower()
+    if side in {"long", "short"}:
+        clauses.append("LOWER(COALESCE(side, 'long'))=%s")
+        params.append(side)
     where = "WHERE " + " AND ".join(clauses) if clauses else ""
     conn = get_conn()
     try:
@@ -1838,7 +1853,7 @@ def list_paper_trades(limit: int = 50, offset: int = 0, status: str = "", strate
     }
 
 
-def list_paper_orders(limit: int = 50, offset: int = 0, status: str = "", strategy_code: str = "") -> dict:
+def list_paper_orders(limit: int = 50, offset: int = 0, status: str = "", strategy_code: str = "", side: str = "") -> dict:
     limit = max(1, min(_safe_int(limit, 50), 200))
     offset = max(0, _safe_int(offset, 0))
     status = str(status or "").strip()
@@ -1852,6 +1867,10 @@ def list_paper_orders(limit: int = 50, offset: int = 0, status: str = "", strate
     if strategy_code:
         clauses.append("strategy_code=%s")
         params.append(normalize_strategy_code(strategy_code))
+    side = str(side or "").strip().lower()
+    if side in {"long", "short"}:
+        clauses.append("LOWER(COALESCE(side, 'long'))=%s")
+        params.append(side)
     where = "WHERE " + " AND ".join(clauses) if clauses else ""
     conn = get_conn()
     try:
@@ -1890,7 +1909,7 @@ def list_paper_orders(limit: int = 50, offset: int = 0, status: str = "", strate
     }
 
 
-def list_paper_trade_events(limit: int = 80, offset: int = 0, symbol: str = "", event_type: str = "", strategy_code: str = "") -> dict:
+def list_paper_trade_events(limit: int = 80, offset: int = 0, symbol: str = "", event_type: str = "", strategy_code: str = "", side: str = "") -> dict:
     limit = max(1, min(_safe_int(limit, 80), 200))
     offset = max(0, _safe_int(offset, 0))
     symbol = str(symbol or "").strip().upper()
@@ -1907,6 +1926,10 @@ def list_paper_trade_events(limit: int = 80, offset: int = 0, symbol: str = "",
     if strategy_code:
         where.append("COALESCE(NULLIF(e.strategy_code, ''), t.strategy_code)=%s")
         params.append(normalize_strategy_code(strategy_code))
+    side = str(side or "").strip().lower()
+    if side in {"long", "short"}:
+        where.append("LOWER(COALESCE(t.side, 'long'))=%s")
+        params.append(side)
     where_sql = "WHERE " + " AND ".join(where) if where else ""
     conn = get_conn()
     try:
@@ -1930,6 +1953,7 @@ def list_paper_trade_events(limit: int = 80, offset: int = 0, symbol: str = "",
                 t.margin_usdt,
                 t.leverage,
                 t.exit_reason,
+                t.side AS trade_side,
                 t.opened_at,
                 t.closed_at,
                 t.strategy_code AS trade_strategy_code,
@@ -1951,6 +1975,7 @@ def list_paper_trade_events(limit: int = 80, offset: int = 0, symbol: str = "",
         item["strategy_code"] = normalize_strategy_code(item.get("strategy_code") or item.get("trade_strategy_code"))
         item["strategy_name"] = strategy_label(item["strategy_code"])
         item["strategy_signal_id"] = _safe_int(item.get("strategy_signal_id") or item.get("trade_strategy_signal_id"))
+        item["side"] = normalize_side(item.get("trade_side"))
         items.append(item)
     return {
         "items": items,

app/db/strategy_insights.py

@@ -54,6 +54,15 @@ def _pct(part, total):
     return round(float(part or 0) / float(total or 0) * 100, 2) if total else 0.0
 
 
+def _strategy_direction(definition) -> str:
+    direction = str((definition.entry_gate_config or {}).get("direction") or "long").strip().lower()
+    return "short" if direction == "short" else "long"
+
+
+def _direction_label(direction: str) -> str:
+    return "空" if str(direction or "").lower() == "short" else "多"
+
+
 def evaluate_strategy_decision(metrics: dict) -> dict:
     """Turn strategy metrics into an explicit lifecycle recommendation.
 
@@ -145,6 +154,8 @@ def get_strategy_evaluation(days: int = 30) -> dict:
             "description": definition.description,
             "mode": definition.mode,
             "status": definition.status,
+            "direction": _strategy_direction(definition),
+            "direction_label": _direction_label(_strategy_direction(definition)),
             "signal_count": 0,
             "candidate_signal_count": 0,
             "observe_signal_count": 0,
@@ -158,6 +169,8 @@ def get_strategy_evaluation(days: int = 30) -> dict:
             "filled_order_count": 0,
             "canceled_order_count": 0,
             "trade_count": 0,
+            "long_trade_count": 0,
+            "short_trade_count": 0,
             "open_trade_count": 0,
             "closed_trade_count": 0,
             "win_count": 0,
@@ -172,12 +185,15 @@ def get_strategy_evaluation(days: int = 30) -> dict:
         normalized = normalize_strategy_code(code)
         if normalized not in metrics:
             definition = strategy_definition(normalized)
+            direction = _strategy_direction(definition)
             metrics[normalized] = {
                 "strategy_code": normalized,
                 "strategy_name": definition.strategy_name,
                 "description": definition.description,
                 "mode": definition.mode,
                 "status": definition.status,
+                "direction": direction,
+                "direction_label": _direction_label(direction),
                 "signal_count": 0,
                 "candidate_signal_count": 0,
                 "observe_signal_count": 0,
@@ -191,6 +207,8 @@ def get_strategy_evaluation(days: int = 30) -> dict:
                 "filled_order_count": 0,
                 "canceled_order_count": 0,
                 "trade_count": 0,
+                "long_trade_count": 0,
+                "short_trade_count": 0,
                 "open_trade_count": 0,
                 "closed_trade_count": 0,
                 "win_count": 0,
@@ -260,7 +278,7 @@ def get_strategy_evaluation(days: int = 30) -> dict:
 
         for row in conn.execute(
             """
-            SELECT strategy_code, status, realized_pnl_pct, realized_pnl_usdt, pnl_pct
+            SELECT strategy_code, side, status, realized_pnl_pct, realized_pnl_usdt, pnl_pct
             FROM paper_trades
             WHERE opened_at >= %s
             """,
@@ -268,7 +286,12 @@ def get_strategy_evaluation(days: int = 30) -> dict:
         ).fetchall():
             b = bucket(row.get("strategy_code"))
             status = row.get("status") or ""
+            side = str(row.get("side") or "long").strip().lower()
             b["trade_count"] += 1
+            if side == "short":
+                b["short_trade_count"] += 1
+            else:
+                b["long_trade_count"] += 1
             if status == "open":
                 b["open_trade_count"] += 1
             if status == "closed":

app/strategies/short_breakdown.py

@@ -0,0 +1,113 @@
+"""Independent short strategy builders.
+
+Short setups are not inverted long setups. They need their own trigger,
+confirmation, invalidation and review lineage.
+"""
+
+from __future__ import annotations
+
+from app.core.factor_roles import CONFIRMATION, ENTRY, RISK, TRIGGER
+from app.core.strategy_contract import StrategySignal, current_strategy_version
+from app.core.strategy_registry import BREAKDOWN_RETEST_SHORT_1H_STRATEGY
+
+
+def _safe_float(value, default=0.0) -> float:
+    try:
+        if value is None or value == "":
+            return default
+        return float(value)
+    except Exception:
+        return default
+
+
+def build_breakdown_retest_short_1h_signal(
+    *,
+    symbol: str,
+    current_price: float,
+    detection: dict,
+    entry_plan: dict | None = None,
+    market_regime: dict | None = None,
+    decision_log: dict | None = None,
+) -> StrategySignal | None:
+    """Build a short signal for breakdown -> failed retest setups.
+
+    Expected detection fields are intentionally simple so scanner/confirm
+    implementations can evolve without changing the strategy contract:
+    detected, breakdown_level, retest_zone, stop_level, target_1, quality,
+    retest_rejected, score.
+    """
+    if not (detection or {}).get("detected"):
+        return None
+    entry_plan = dict(entry_plan or {})
+    market_regime = market_regime or {}
+    quality = str(detection.get("quality") or "")
+    retest_rejected = bool(detection.get("retest_rejected"))
+    current_price = _safe_float(current_price)
+    retest_zone = _safe_float(detection.get("retest_zone") or detection.get("breakdown_level"))
+    distance_pct = abs(current_price / retest_zone - 1) * 100 if current_price > 0 and retest_zone > 0 else 0.0
+    risk_level = str(market_regime.get("risk_level") or "medium").lower()
+    reasons = []
+    status = "candidate"
+    if quality not in {"良好", "优质"}:
+        status = "observe"
+        reasons.append(f"反抽质量 {quality or '未知'}，不直接做空")
+    if not retest_rejected:
+        status = "observe"
+        reasons.append("尚未确认反抽失败")
+    if risk_level in {"low", "medium"} and not bool(detection.get("relative_weakness")):
+        status = "observe"
+        reasons.append("市场并非明显弱势，且缺少相对弱势确认")
+    if distance_pct > 8:
+        status = "observe"
+        reasons.append(f"当前价离反抽区 {distance_pct:.1f}%，不追空")
+
+    entry_plan.setdefault("side", "short")
+    entry_plan.setdefault("entry_action", "可即刻买入" if status == "candidate" else "观察")
+    entry_plan.setdefault("entry_price", current_price)
+    entry_plan.setdefault("stop_loss", detection.get("stop_level"))
+    entry_plan.setdefault("tp1", detection.get("target_1"))
+    entry_plan.setdefault("risk_reward_ok", True)
+
+    score = _safe_float(detection.get("score"))
+    confidence = min(100.0, max(0.0, score * 8 + (12 if retest_rejected else 0)))
+    return StrategySignal(
+        strategy_code=BREAKDOWN_RETEST_SHORT_1H_STRATEGY,
+        strategy_version=current_strategy_version(),
+        symbol=symbol,
+        direction="short",
+        status=status,
+        confidence=confidence,
+        score=score,
+        trigger={
+            "factor_code": "breakdown_retest_1h_short",
+            "factor_label": "1H破位反抽做空",
+            "breakdown_level": detection.get("breakdown_level"),
+            "retest_zone": retest_zone,
+            "stop_level": detection.get("stop_level"),
+            "target_1": detection.get("target_1"),
+            "quality": quality,
+            "retest_rejected": retest_rejected,
+            "distance_to_retest_zone_pct": round(distance_pct, 4),
+            "risk_level": risk_level,
+        },
+        factor_roles={
+            "breakdown_retest_1h_short": TRIGGER,
+            "retest_reject_15m_short": ENTRY,
+            "market_risk_off_short": CONFIRMATION,
+            "false_breakout": RISK,
+            "funding_extreme": RISK,
+        },
+        entry_plan=entry_plan,
+        risk_plan={
+            "invalid_if": ["重新站回破位区", "反抽放量突破", "BTC/ETH快速转强", "RR不足"],
+            "risk_reasons": reasons,
+        },
+        decision_log=decision_log or {
+            "module": BREAKDOWN_RETEST_SHORT_1H_STRATEGY,
+            "decision": status,
+            "reasons": reasons,
+        },
+    )
+
+
+__all__ = ["build_breakdown_retest_short_1h_signal"]

app/web/routes_paper_trading.py

@@ -42,10 +42,11 @@ async def api_paper_trading_trades(
     offset: int = 0,
     status: str = "",
     strategy_code: str = "",
+    side: str = "",
     altcoin_session: str = Cookie(default=""),
 ):
     require_admin(altcoin_session)
-    return list_paper_trades(limit=limit, offset=offset, status=status, strategy_code=strategy_code)
+    return list_paper_trades(limit=limit, offset=offset, status=status, strategy_code=strategy_code, side=side)
 
 
 @router.get("/api/paper-trading/orders")
@@ -54,10 +55,11 @@ async def api_paper_trading_orders(
     offset: int = 0,
     status: str = "",
     strategy_code: str = "",
+    side: str = "",
     altcoin_session: str = Cookie(default=""),
 ):
     require_admin(altcoin_session)
-    return list_paper_orders(limit=limit, offset=offset, status=status, strategy_code=strategy_code)
+    return list_paper_orders(limit=limit, offset=offset, status=status, strategy_code=strategy_code, side=side)
 
 
 @router.get("/api/paper-trading/events")
@@ -67,10 +69,11 @@ async def api_paper_trading_events(
     symbol: str = "",
     event_type: str = "",
     strategy_code: str = "",
+    side: str = "",
     altcoin_session: str = Cookie(default=""),
 ):
     require_admin(altcoin_session)
-    return list_paper_trade_events(limit=limit, offset=offset, symbol=symbol, event_type=event_type, strategy_code=strategy_code)
+    return list_paper_trade_events(limit=limit, offset=offset, symbol=symbol, event_type=event_type, strategy_code=strategy_code, side=side)
 
 
 @router.post("/api/paper-trading/report")

tests/test_multi_strategy_infra.py

@@ -4,6 +4,7 @@ from app.core.strategy_registry import (
     BOX_RETEST_1H_STRATEGY,
     BOX_RETEST_4H_STRATEGY,
     COMPRESSION_BREAKOUT_4H_STRATEGY,
+    BREAKDOWN_RETEST_SHORT_1H_STRATEGY,
     INTRADAY_MOMENTUM_15M_STRATEGY,
     MAIN_COMPOSITE_STRATEGY,
     VOLUME_IGNITION_1H_STRATEGY,
@@ -19,6 +20,7 @@ from app.strategies.altcoin_breakout import (
     build_volume_ignition_1h_signal,
 )
 from app.strategies.box_retest_4h import build_box_retest_1h_signal
+from app.strategies.short_breakdown import build_breakdown_retest_short_1h_signal
 
 
 def test_factor_roles_never_promote_unknown_to_trigger():
@@ -47,6 +49,7 @@ def test_default_main_composite_strategy_signal_is_stable():
     assert strategy_label(VOLUME_IGNITION_1H_STRATEGY) == "1H放量突破启动"
     assert strategy_label(COMPRESSION_BREAKOUT_4H_STRATEGY) == "4H压缩蓄力突破"
     assert strategy_label(INTRADAY_MOMENTUM_15M_STRATEGY) == "15m日内动量延续"
+    assert strategy_label(BREAKDOWN_RETEST_SHORT_1H_STRATEGY) == "1H破位反抽做空"
 
 
 def test_volume_ignition_strategy_builds_independent_signal():
@@ -108,6 +111,31 @@ def test_intraday_momentum_strategy_requires_current_trigger():
     assert fresh["status"] == "candidate"
 
 
+def test_breakdown_retest_short_strategy_is_independent_short_signal():
+    signal = build_breakdown_retest_short_1h_signal(
+        symbol="WEAK/USDT",
+        current_price=0.98,
+        detection={
+            "detected": True,
+            "score": 8,
+            "breakdown_level": 1.0,
+            "retest_zone": 1.0,
+            "stop_level": 1.04,
+            "target_1": 0.9,
+            "quality": "优质",
+            "retest_rejected": True,
+            "relative_weakness": True,
+        },
+        market_regime={"risk_level": "high", "regime": "risk_off"},
+    ).to_json_dict()
+
+    assert signal["strategy_code"] == BREAKDOWN_RETEST_SHORT_1H_STRATEGY
+    assert signal["direction"] == "short"
+    assert signal["entry_plan"]["side"] == "short"
+    assert signal["status"] == "candidate"
+    assert signal["factor_roles"]["breakdown_retest_1h_short"] == "trigger"
+
+
 def test_strategy_evaluation_recommends_promote_or_pause():
     strong = evaluate_strategy_decision({
         "signal_count": 24,

tests/test_paper_trading.py

@@ -1049,6 +1049,62 @@ def test_open_paper_trade_closes_on_tp1_and_summary_counts_win(buy_now_rec):
     assert summary["win_rate"] == pytest.approx(100.0)
 
 
+def test_short_paper_trade_opens_and_closes_on_take_profit(monkeypatch, buy_now_rec):
+    rec = dict(buy_now_rec)
+    rec["side"] = "short"
+    rec["stop_loss"] = 105
+    rec["tp1"] = 94
+    rec["tp2"] = 90
+    rec["entry_plan"] = {
+        "side": "short",
+        "entry_action": "可即刻买入",
+        "entry_price": 100,
+        "stop_loss": 105,
+        "tp1": 94,
+        "tp2": 90,
+        "risk_reward_ok": True,
+        "rr1": 1.2,
+        "entry_trigger_confirmed": True,
+    }
+
+    opened = sync_recommendation(rec, 100, event_time="2026-05-16T10:00:00")
+    closed = sync_recommendation(rec, 94, event_time="2026-05-16T10:10:00")
+
+    assert opened["opened"] is True
+    assert closed["closed"] is True
+    assert closed["exit_reason"] == "tp1"
+    assert closed["pnl_pct"] > 0
+    trade = list_paper_trades()["items"][0]
+    assert trade["side"] == "short"
+    assert trade["status"] == "closed"
+    assert list_paper_trades(side="short")["total"] == 1
+    assert list_paper_trades(side="long")["total"] == 0
+
+
+def test_short_paper_trade_closes_on_stop_loss(monkeypatch, buy_now_rec):
+    rec = dict(buy_now_rec)
+    rec["side"] = "short"
+    rec["stop_loss"] = 105
+    rec["tp1"] = 94
+    rec["entry_plan"] = {
+        "side": "short",
+        "entry_action": "可即刻买入",
+        "entry_price": 100,
+        "stop_loss": 105,
+        "tp1": 94,
+        "risk_reward_ok": True,
+        "rr1": 1.2,
+        "entry_trigger_confirmed": True,
+    }
+
+    sync_recommendation(rec, 100, event_time="2026-05-16T10:00:00")
+    result = sync_recommendation(rec, 106, event_time="2026-05-16T10:10:00")
+
+    assert result["closed"] is True
+    assert result["exit_reason"] == "stop_loss"
+    assert result["pnl_pct"] < 0
+
+
 def test_paper_trading_trailing_stop_activates_moves_and_closes(monkeypatch, buy_now_rec):
     pushed = []
     monkeypatch.setenv("ALPHAX_PAPER_TRAILING_STOP_ENABLED", "1")

tests/test_trade_math.py

@@ -0,0 +1,30 @@
+import pytest
+
+from app.core.trade_math import (
+    close_price,
+    open_price,
+    pnl_pct,
+    should_hit_trailing_stop,
+    should_stop_loss,
+    should_take_profit,
+    tighter_stop,
+)
+
+
+def test_trade_math_is_side_aware_for_short():
+    assert open_price("short", 100, 0.1) == pytest.approx(99.9)
+    assert close_price("short", 90, 0.1) == pytest.approx(90.09)
+    assert pnl_pct("short", 100, 90) == pytest.approx(11.1111)
+    assert should_stop_loss("short", 106, 105) is True
+    assert should_take_profit("short", 94, 95) is True
+    assert should_hit_trailing_stop("short", 98, 97.5) is True
+    assert tighter_stop("short", 99, 97.5) == pytest.approx(97.5)
+
+
+def test_trade_math_keeps_long_behavior():
+    assert open_price("long", 100, 0.1) == pytest.approx(100.1)
+    assert close_price("long", 110, 0.1) == pytest.approx(109.89)
+    assert pnl_pct("long", 100, 110) == pytest.approx(10)
+    assert should_stop_loss("long", 94, 95) is True
+    assert should_take_profit("long", 106, 105) is True
+    assert tighter_stop("long", 99, 101) == pytest.approx(101)

tests/test_trailing_stop.py

@@ -43,6 +43,38 @@ def test_trailing_stop_never_moves_down():
     assert decision["trailing_stop"] == pytest.approx(104)
 
 
+def test_short_trailing_stop_activates_and_moves_down():
+    activated = evaluate_trailing_stop(
+        position={"side": "short", "entry_price": 100, "max_price": 100, "min_price": 100, "trailing_stop": 0},
+        current_price=94,
+        pnl_pct=6,
+        config={
+            "trailing_stop_enabled": True,
+            "trailing_mode": "fixed",
+            "trailing_activate_pnl_pct": 3,
+            "trailing_min_lock_profit_pct": 0.5,
+            "trailing_distance_pct": 1.5,
+        },
+    ).as_dict()
+    moved = evaluate_trailing_stop(
+        position={"side": "short", "entry_price": 100, "max_price": 100, "min_price": 94, "trailing_stop": activated["trailing_stop"]},
+        current_price=92,
+        pnl_pct=8,
+        config={
+            "trailing_stop_enabled": True,
+            "trailing_mode": "fixed",
+            "trailing_activate_pnl_pct": 3,
+            "trailing_min_lock_profit_pct": 0.5,
+            "trailing_distance_pct": 1.5,
+        },
+    ).as_dict()
+
+    assert activated["action"] == "activate"
+    assert activated["trailing_stop"] == pytest.approx(95.41)
+    assert moved["action"] == "move"
+    assert moved["trailing_stop"] < activated["trailing_stop"]
+
+
 def test_volatility_profile_widens_activation_and_distance():
     profile = trailing_profile(
         {"entry_price": 100, "max_price": 100, "min_price": 98},