QuantStrategyLab · Pigbibi · Jul 4, 2026 · Jul 4, 2026 · chatgpt-codex-connector · Jul 4, 2026
@@ -34,6 +34,7 @@ See the Chinese handbook for localized positioning text and default parameter ta
 | `tech_communication_pullback_enhancement` | research_only | Underperforms `russell_top50_leader_rotation` on return and drawdown. |
 | `QQQ` / `SPY` LEAPS growth overlay | research_only | Design: [`research/index_leaps_growth_overlay.md`](./research/index_leaps_growth_overlay.md). Proxy backtest module: `UsEquitySnapshotPipelines/docs/index-leaps-growth-overlay-research.md`. |
 | `us_equity_combo_leveraged_shadow_352045` | shadow_candidate | TQQQ 35% / SOXL 20% / BOXX 45% with `hard_defense_risk_exposure=0.0`. Backtest evidence: 22.21% CAGR, -33.88% max drawdown over 2010-01-05 to 2026-07-02 with 5 bps cost. Runtime config: `src/us_equity_strategies/configs/us_equity_combo_leveraged_shadow_352045.json`. |
+| `us_equity_combo_leveraged_shadow_402040` | shadow_candidate | TQQQ 40% / SOXL 20% / BOXX 40% with `hard_defense_risk_exposure=0.0`. Backtest evidence: 23.81% CAGR, -35.53% max drawdown over 2010-01-05 to 2026-07-02 with 5 bps cost. Runtime config: `src/us_equity_strategies/configs/us_equity_combo_leveraged_shadow_402040.json`. |
 | `crisis_response_shadow` plugin | shadow candidate | Defense-only observation; no allocation impact. |
 
 ## Promotion principles

@@ -65,6 +65,7 @@ _更新日期：2026-06-28_
 | `global_etf_confidence_vol_gate` production-like 研究 | 2015-01-05 至 2026-05-06 | 14.77% | -23.35% | 相比同口径 Top2/SMA250 的 13.60% CAGR、-23.35% 回撤，收益和 Sharpe 改善；仍未跑赢 QQQ 长期 CAGR，因此只作为 Global ETF 自身增强候选。 | [`docs/research/global_etf_confidence_vol_gate.md`](./research/global_etf_confidence_vol_gate.md) |
 | Crisis unified response historical research，含旧 5% 反弹袖子 | 1999-03-10 至 2026-04-16 | 23.89% | -56.04% | 相比合成 TQQQ 基线显著降低 2000/2008 级别灾难回撤；但该历史版本包含旧反弹袖子，不等于当前 defense-only shadow plugin。 | `UsEquitySnapshotPipelines/data/output/crisis_response_audit_trial/external_fragility10_severe10_fin_credit/summary.csv` |
 | `us_equity_combo_leveraged_shadow_352045`，5 bps 单边成本 | 2010-01-05 至 2026-07-02 | 22.21% | -33.88% | `TQQQ 35% / SOXL 20% / BOXX 45%`，`hard_defense_risk_exposure=0`；最大回撤进入 35%-40% 可接受区间，但收益/风险仍弱于单腿最强 proxy，因此只进入 shadow 观察，不替换 live。 | `/tmp/us_combo_core_sweep_20260704/ranking.csv`；运行配置见 `src/us_equity_strategies/configs/us_equity_combo_leveraged_shadow_352045.json` |
+| `us_equity_combo_leveraged_shadow_402040`，5 bps 单边成本 | 2010-01-05 至 2026-07-02 | 23.81% | -35.53% | `TQQQ 40% / SOXL 20% / BOXX 40%`，`hard_defense_risk_exposure=0`；在 35%-40% 回撤预算下收益、Sharpe、Calmar 均优于 35/20/45，适合作为下一轮 shadow 观察配置。 | `/tmp/us_combo_rule_compare_20260704/ranking_rule_compare.csv`；运行配置见 `src/us_equity_strategies/configs/us_equity_combo_leveraged_shadow_402040.json` |
 
 暂时没有写进正式表的内容：
 
@@ -76,6 +77,7 @@ _更新日期：2026-06-28_
 | --- | --- | --- |
 | `tecl_xlk_trend_income` | `research_enabled` | 重叠窗口未跑赢 live TQQQ / SOXL（2024+ CAGR 24.8%，最大回撤 -46.0%）；保留策略实现与回测入口，不进入 runtime。研究文档见 [`UsEquitySnapshotPipelines/docs/tecl-xlk-optimization-research.zh-CN.md`](../../UsEquitySnapshotPipelines/docs/tecl-xlk-optimization-research.zh-CN.md)。 |
 | `us_equity_combo_leveraged_shadow_352045` | shadow candidate | 组合型杠杆候选：`TQQQ 35% / SOXL 20% / BOXX 45%`，risk-off 归零风险腿转 `BOXX`。当前仅提供受控 runtime_config 与测试保护，不改变默认 live；需要平台 dry-run / shadow 周期证据后才可重新评估 live。 |
+| `us_equity_combo_leveraged_shadow_402040` | shadow candidate | 组合型杠杆候选：`TQQQ 40% / SOXL 20% / BOXX 40%`，risk-off 归零风险腿转 `BOXX`。这是 35%-40% 回撤预算下的下一轮 shadow 配置，不直接替换 live。 |
 | `crisis_response_shadow` 插件 | 可作为 `tqqq_growth_income` 的 `shadow` 插件候选，只写信号、日志和通知上下文。 | 现在是 defense-only 黑天鹅观察流，不下单、不改 allocation；需要稳定 shadow 日志后再做 evidence review。 |
 | 事件反弹 / MAGS 路线 | 保持 research-only，不作为运行策略 profile。 | 对 MAGS 的正贡献不稳定，且事件反弹预算不应该混进黑天鹅逃命插件。 |
 | `QQQ` / `SPY` LEAPS 增长增强层 | 已有 option overlay 意图框架；组合型 live profile 默认带 `option_*` 设置，但 `spy_leaps_growth_v1` / `qqq_leaps_growth_v1` 等 recipe 仍是 research candidate，当前会以 `research_only_recipe` 跳过，不产生真实订单意图，研究设计见 [`docs/research/index_leaps_growth_overlay.zh-CN.md`](./research/index_leaps_growth_overlay.zh-CN.md)（[English](./research/index_leaps_growth_overlay.md)）；代理回测见 [`UsEquitySnapshotPipelines/docs/index-leaps-growth-overlay-research.md`](../../UsEquitySnapshotPipelines/docs/index-leaps-growth-overlay-research.md)。 | 属于有限权利金预算的增长增强层，不是当前低回撤收入层的直接替代；需要真实期权链回测后才能把 recipe 晋级为 live。 |

@@ -184,8 +184,11 @@ def evaluate_us_equity_combo_leveraged(ctx: StrategyContext) -> StrategyDecision
     risk_flags: tuple[str, ...] = ()
     if has_cash:
         risk_flags += ("cash_parked",)
-    if not metadata.get("spy_above_ma200", True):
+    regime_state = str(metadata.get("regime_state") or "")
+    if regime_state == "hard_defense":
         risk_flags += ("ma200_risk_off",)
+    elif regime_state == "soft_defense":
+        risk_flags += ("soft_defense",)
     budgets = _build_budgets(diagnostics)
     return StrategyDecision(
         positions=_weights_to_positions(weights),

@@ -13,7 +13,12 @@
   },
   "required_market_data": {
     "market_data": {
-      "spy_above_ma200": "boolean"
+      "spy_above_ma200": "boolean",
+      "qqq_above_ma200": "boolean",
+      "soxx_above_ma200": "boolean",
+      "spy_ma20_slope_positive": "boolean",
+      "qqq_ma20_slope_positive": "boolean",
+      "soxx_ma20_slope_positive": "boolean"
     }
   },
   "backtest_evidence": {
@@ -32,6 +37,7 @@
   },
   "notes": [
     "This config does not change the strategy default or any live deployment.",
+    "Backtest dynamic mode uses SPY/QQQ/SOXX MA200 hard-defense inputs; runtime market_data must provide the same regime fields.",
     "Risk-off behavior requires hard_defense_risk_exposure=0.0; otherwise the strategy retains the default 50% risk-leg exposure.",
     "The backtest artifact is local research output and should be regenerated into a durable repo or CI artifact before live promotion."
   ]

@@ -0,0 +1,46 @@
+{
+  "role": "us_equity_combo_leveraged_shadow",
+  "status": "shadow_candidate",
+  "strategy_profile": "us_equity_combo_leveraged",
+  "name": "us_equity_combo_leveraged_shadow_402040",
+  "description": "TQQQ 40% + SOXL 20% + BOXX 40% dynamic shadow candidate with full BOXX hard defense.",
+  "runtime_config": {
+    "tqqq_weight": 0.4,
+    "soxl_weight": 0.2,
+    "boxx_weight": 0.4,
+    "dynamic": true,
+    "hard_defense_risk_exposure": 0.0
+  },
+  "required_market_data": {
+    "market_data": {
+      "spy_above_ma200": "boolean",
+      "qqq_above_ma200": "boolean",
+      "soxx_above_ma200": "boolean",
+      "spy_ma20_slope_positive": "boolean",
+      "qqq_ma20_slope_positive": "boolean",
+      "soxx_ma20_slope_positive": "boolean"
+    }
+  },
+  "backtest_evidence": {
+    "artifact": "/tmp/us_combo_rule_compare_20260704/ranking_rule_compare.csv",
+    "window": "2010-01-05 to 2026-07-02",
+    "turnover_cost_bps": 5,
+    "full_cagr": 0.238097,
+    "max_drawdown": -0.35531,
+    "sharpe": 0.911368,
+    "calmar": 0.67011,
+    "rolling_1y_worst_mdd": -0.35531,
+    "rolling_3y_worst_mdd": -0.35531
+  },
+  "promotion_state": {
+    "live_enable_candidate": false,
+    "shadow_ready": true,
+    "promotion_gate": "requires platform-level dry-run evidence before live"
+  },
+  "notes": [
+    "This config does not change the strategy default or any live deployment.",
+    "Backtest dynamic mode uses SPY/QQQ/SOXX MA200 hard-defense inputs; runtime market_data must provide the same regime fields.",
+    "Risk-off behavior requires hard_defense_risk_exposure=0.0; otherwise the strategy retains the default 50% risk-leg exposure.",
+    "Candidate assumes user accepts an approximate 35-40% historical max drawdown budget."
+  ]
+}
@@ -9,9 +9,10 @@
 
 Dynamic mode
 ------------
-SPY 200-day MA regime signal:
-- SPY above MA200 (bull): normal weights
-- SPY below MA200 (bear): risk legs retain 50% by default, BOXX receives the rest
+Multi-asset 200-day MA regime signal:
+- SPY/QQQ/SOXX all above MA200: normal weights
+- any of SPY/QQQ/SOXX below MA200: risk legs retain 50% by default, BOXX receives the rest
+- if only 20-day MA slope weakens, keep current weights and mark soft defense
 """
 
 from __future__ import annotations
@@ -33,6 +34,8 @@
 DEFAULT_BOXX_WEIGHT = 0.40
 DEFAULT_REBALANCE_THRESHOLD = 0.05  # 5% drift triggers rebalance
 DEFAULT_HARD_DEFENSE_RISK_EXPOSURE = 0.50
+DEFAULT_SOFT_DEFENSE_RISK_EXPOSURE = 1.00
+REGIME_SYMBOLS = ("SPY", "QQQ", "SOXX")
 
 
 def _noop_logger(_message: str) -> None:
@@ -80,7 +83,13 @@ def load_runtime_parameters(
         raise ValueError("Runtime strategy config runtime_config must be an object")
 
     runtime_config = dict(raw_runtime_config)
-    for key in ("tqqq_weight", "soxl_weight", "boxx_weight", "hard_defense_risk_exposure"):
+    for key in (
+        "tqqq_weight",
+        "soxl_weight",
+        "boxx_weight",
+        "hard_defense_risk_exposure",
+        "soft_defense_risk_exposure",
+    ):
         if key not in runtime_config:
             continue
         value = float(runtime_config[key])
@@ -91,6 +100,8 @@ def load_runtime_parameters(
         runtime_config[key] = value
     if "hard_defense_risk_exposure" in runtime_config and float(runtime_config["hard_defense_risk_exposure"]) > 1.0:
         raise ValueError("Runtime strategy config hard_defense_risk_exposure must be in [0, 1]")
+    if "soft_defense_risk_exposure" in runtime_config and float(runtime_config["soft_defense_risk_exposure"]) > 1.0:
+        raise ValueError("Runtime strategy config soft_defense_risk_exposure must be in [0, 1]")
     if all(key in runtime_config for key in ("tqqq_weight", "soxl_weight", "boxx_weight")):
         total = sum(float(runtime_config[key]) for key in ("tqqq_weight", "soxl_weight", "boxx_weight"))
         if total <= 0.0:
@@ -103,6 +114,37 @@ def load_runtime_parameters(
     return runtime_config
 
 
+def _market_bool(market_data: dict[str, Any], key: str, default: bool) -> bool:
+    value = market_data.get(key, default)
+    return bool(value)
+
+
+def _resolve_regime(market_data: dict[str, Any] | None) -> dict[str, object]:
+    raw = market_data if isinstance(market_data, dict) else {}
+    above_ma200 = {
+        symbol: _market_bool(raw, f"{symbol.lower()}_above_ma200", True)
+        for symbol in REGIME_SYMBOLS
+    }
+    ma20_slope_positive = {
+        symbol: _market_bool(raw, f"{symbol.lower()}_ma20_slope_positive", True)
+        for symbol in REGIME_SYMBOLS
+    }
+
+    if not all(above_ma200.values()):
+        regime_state = "hard_defense"
+    elif not all(ma20_slope_positive.values()):
+        regime_state = "soft_defense"
+    else:
+        regime_state = "risk_on"
+
+    return {
+        "regime_state": regime_state,
+        "above_ma200": above_ma200,
+        "ma20_slope_positive": ma20_slope_positive,
+        "spy_above_ma200": above_ma200["SPY"],
+    }
+
+
 def build_target_weights(
     market_data: dict[str, Any] | None = None,
     config: dict[str, Any] | None = None,
@@ -113,15 +155,19 @@ def build_target_weights(
     Parameters
     ----------
     market_data : dict or None
-        Contains price/regime info.  If it holds a 'spy_above_ma200' key,
-        dynamic mode uses it.
+        Contains price/regime info.  Dynamic mode uses SPY/QQQ/SOXX
+        '<symbol>_above_ma200' and '<symbol>_ma20_slope_positive' keys when
+        available. Missing non-SPY keys default to risk-on for backwards
+        compatibility.
     config : dict or None
         Override configuration.  Accepted keys:
         - tqqq_weight, soxl_weight, boxx_weight (overrides defaults)
         - dynamic (bool, default True)
         - hard_defense_risk_exposure (float, default 0.50): retained
           TQQQ/SOXL fraction when SPY is below MA200.  Use 0.0 for a
           full BOXX hard-defense shadow.
+        - soft_defense_risk_exposure (float, default 1.00): retained
+          TQQQ/SOXL fraction when MA20 slope weakens while MA200 stays intact.
 
     Returns
     -------
@@ -137,15 +183,23 @@ def build_target_weights(
         1.0,
         max(0.0, float(cfg.get("hard_defense_risk_exposure", DEFAULT_HARD_DEFENSE_RISK_EXPOSURE))),
     )
+    soft_defense_risk_exposure = min(
+        1.0,
+        max(0.0, float(cfg.get("soft_defense_risk_exposure", DEFAULT_SOFT_DEFENSE_RISK_EXPOSURE))),
+    )
 
-    # Dynamic mode: SPY MA200 risk-off
-    spy_above_ma200 = True
-    if isinstance(market_data, dict):
-        spy_above_ma200 = bool(market_data.get("spy_above_ma200", True))
+    regime = _resolve_regime(market_data)
+    regime_state = str(regime["regime_state"])
 
-    if dynamic and not spy_above_ma200:
-        tqqq_weight *= hard_defense_risk_exposure
-        soxl_weight *= hard_defense_risk_exposure
+    if dynamic and regime_state == "hard_defense":
+        risk_exposure = hard_defense_risk_exposure
+        tqqq_weight *= risk_exposure
+        soxl_weight *= risk_exposure
+        boxx_weight = 1.0 - tqqq_weight - soxl_weight
+    elif dynamic and regime_state == "soft_defense":
+        risk_exposure = soft_defense_risk_exposure
+        tqqq_weight *= risk_exposure
+        soxl_weight *= risk_exposure
         boxx_weight = 1.0 - tqqq_weight - soxl_weight
 
     # Normalize
@@ -165,14 +219,18 @@ def build_target_weights(
         "profile_name": PROFILE_NAME,
         "signal_source": SIGNAL_SOURCE,
         "status_icon": STATUS_ICON,
-        "spy_above_ma200": spy_above_ma200,
+        "regime_state": regime_state if dynamic else "risk_on",
+        "spy_above_ma200": regime["spy_above_ma200"],
+        "above_ma200": regime["above_ma200"],
+        "ma20_slope_positive": regime["ma20_slope_positive"],
         "effective_weights": {
             "TQQQ": tqqq_weight,
             "SOXL": soxl_weight,
             "BOXX": boxx_weight,
         },
         "dynamic": dynamic,
         "hard_defense_risk_exposure": hard_defense_risk_exposure,
+        "soft_defense_risk_exposure": soft_defense_risk_exposure,
         "rebalance": compute_portfolio_drift(
             weights,
             holdings=cfg.get("current_holdings_quantities", {}),
@@ -202,13 +260,14 @@ def compute_signals(
         **kwargs,
     )
     ew = metadata.get("effective_weights", {})
+    regime_state = str(metadata.get("regime_state") or "risk_on")
     spy_status = "MA200_up" if metadata.get("spy_above_ma200", True) else "MA200_down"
     signal_desc = (
-        f"leveraged combo {spy_status} "
+        f"leveraged combo {regime_state} {spy_status} "
         f"TQQQ={ew.get('TQQQ', 0):.0%} SOXL={ew.get('SOXL', 0):.0%} BOXX={ew.get('BOXX', 0):.0%}"
     )
     status_desc = (
-        f"{spy_status} | "
+        f"{regime_state} {spy_status} | "
         f"TQQQ={ew.get('TQQQ', 0):.0%} SOXL={ew.get('SOXL', 0):.0%} BOXX={ew.get('BOXX', 0):.0%}"
     )
     has_cash = ew.get("BOXX", 0) > 0.5

@@ -60,6 +60,49 @@ def test_us_equity_combo_leveraged_supports_zero_hard_defense_shadow() -> None:
     assert metadata["hard_defense_risk_exposure"] == 0.0
 
 
+def test_us_equity_combo_leveraged_uses_multi_asset_hard_defense() -> None:
+    weights, metadata = us_equity_combo_leveraged.build_target_weights(
+        market_data={
+            "spy_above_ma200": True,
+            "qqq_above_ma200": False,
+            "soxx_above_ma200": True,
+        },
+        config={
+            "tqqq_weight": 0.35,
+            "soxl_weight": 0.20,
+            "boxx_weight": 0.45,
+            "hard_defense_risk_exposure": 0.0,
+        },
+    )
+
+    assert weights == {"TQQQ": 0.0, "SOXL": 0.0, "BOXX": 1.0}
+    assert metadata["regime_state"] == "hard_defense"
+    assert metadata["above_ma200"]["QQQ"] is False
+
+
+def test_us_equity_combo_leveraged_marks_soft_defense_without_changing_shadow_weights() -> None:
+    weights, metadata = us_equity_combo_leveraged.build_target_weights(
+        market_data={
+            "spy_above_ma200": True,
+            "qqq_above_ma200": True,
+            "soxx_above_ma200": True,
+            "spy_ma20_slope_positive": True,
+            "qqq_ma20_slope_positive": False,
+            "soxx_ma20_slope_positive": True,
+        },
+        config={
+            "tqqq_weight": 0.35,
+            "soxl_weight": 0.20,
+            "boxx_weight": 0.45,
+            "hard_defense_risk_exposure": 0.0,
+        },
+    )
+
+    assert weights == {"TQQQ": 0.35, "SOXL": 0.20, "BOXX": 0.45}
+    assert metadata["regime_state"] == "soft_defense"
+    assert metadata["ma20_slope_positive"]["QQQ"] is False
+
+
 def test_us_equity_combo_leveraged_shadow_352045_config_matches_strategy_behavior() -> None:
     config_path = (
         Path(__file__).resolve().parents[1]
@@ -123,3 +166,34 @@ def test_us_equity_combo_leveraged_loads_package_runtime_config() -> None:
     assert runtime_config["runtime_config_path"].startswith("package://us_equity_strategies/")
     assert runtime_config["tqqq_weight"] == 0.35
     assert runtime_config["hard_defense_risk_exposure"] == 0.0
+
+
+def test_us_equity_combo_leveraged_loads_402040_shadow_config() -> None:
+    runtime_config = us_equity_combo_leveraged.load_runtime_parameters(
+        config_path=(
+            "package://us_equity_strategies/"
+            "configs/us_equity_combo_leveraged_shadow_402040.json"
+        ),
+        logger=lambda _message: None,
+    )
+    risk_on_weights, _risk_on_metadata = us_equity_combo_leveraged.build_target_weights(
+        market_data={
+            "spy_above_ma200": True,
+            "qqq_above_ma200": True,
+            "soxx_above_ma200": True,
+        },
+        config=runtime_config,
+    )
+    hard_weights, hard_metadata = us_equity_combo_leveraged.build_target_weights(
+        market_data={
+            "spy_above_ma200": True,
+            "qqq_above_ma200": False,
+            "soxx_above_ma200": True,
+        },
+        config=runtime_config,
+    )
+
+    assert runtime_config["runtime_config_name"] == "us_equity_combo_leveraged_shadow_402040"
+    assert risk_on_weights == {"TQQQ": 0.4, "SOXL": 0.2, "BOXX": 0.4}
+    assert hard_weights == {"TQQQ": 0.0, "SOXL": 0.0, "BOXX": 1.0}
+    assert hard_metadata["regime_state"] == "hard_defense"