Wire pct-trailing end-to-end for EarningsRunup; tune v2 risk profile

Fix EarningsRunup trailing config that was previously captured in
Candidate.features only. Add activation-gated pct trailing to
update_trailing_stop with entry-relative giveback semantics
("lock in peak − giveback% of entry"). Plumb through
Candidate → ExecutionConfig → simulator. Default None preserves
legacy pct_X behavior — no impact on engines that don't opt in.

Add earnings_runup_poc_v2_tuned config: per_trade_risk_pct 0.65→0.30,
max_positions 30→8, max_positions_per_sector 30→4, macro_vix_max=30,
trailing_warmup_days 7→0 (activation gate replaces warmup).

v2 backtest (4y, 121 trades) vs v1 baseline (119 trades):
  Total return:  +37.27%  →  +254.69%
  Max drawdown:  53.23%   →  23.97%
  SQS:           45.2     →  69.7
  Robustness:    50.1     →  100.0
  Risk score:    23.5     →  35.0
  STOP r-mult:   −0.41    →  +0.65 (trailing-locked winners)

Promotion thresholds met: MDD < 25%, return preserved, SQS > 55.
Recommend integration as PEAD sleeve adjunct (orthogonal entry timing:
pre-print attention runup vs post-print drift) rather than standalone.

7 new pct-trailing tests: activation gate, ratchet, no-ratchet-down,
reversal-stop, legacy compat, end-to-end engine wiring. 28 passed.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

apps/backtester/run.py

@@ -1194,16 +1194,22 @@ class BacktestRunner:
                 still_open.append(pos)
                 continue
 
-            # Update trailing stop if configured
+            # Resolve per-engine effective execution config FIRST so trailing
-            if self.config.execution.trailing_model:
+            # honors engine_trailing_model overrides (e.g. EarningsRunup pct_3
+            # with activation gate). Falls back to global trailing_model when
+            # no engine override is set.
+            effective_exec = self._build_effective_execution_config(pos.plan.candidate)
+
+            # Update trailing stop if configured (honor engine-level override).
+            if effective_exec.trailing_model:
                 update_trailing_stop(
                     pos, bar,
-                    self.config.execution.trailing_model,
+                    effective_exec.trailing_model,
-                    warmup_days=self.config.execution.trailing_warmup_days,
+                    warmup_days=effective_exec.trailing_warmup_days,
+                    pct_activation=effective_exec.trailing_pct_activation,
+                    pct_giveback=effective_exec.trailing_pct_giveback,
                 )
 
-            effective_exec = self._build_effective_execution_config(pos.plan.candidate)
-
             prev_status = pos.status
             trade = simulate_exit(pos, bar, effective_exec, date)
             if trade is not None:

configs/experiments/earnings_runup_poc_v2_tuned.json

@@ -0,0 +1,83 @@
+{
+  "experiment_name": "earnings_runup_poc_v2_tuned",
+  "dataset_snapshot_id": "midlarge-liquid-long-v1_bucketfix_full_audit_canonical_ftb_fix_v2",
+  "description": "EarningsRunup PoC v2 with risk-tuned exits. v1 baseline: +37.27% return, MDD 53.23% (raw) / 44.46% (SQS risk component), SQS 45.2. Changes: (a) wire pct-trailing end-to-end via new trailing_pct_activation/trailing_pct_giveback fields → trailing only arms after +5% peak P&L, then locks in (peak_pnl - 3%) of entry; (b) per_trade_risk_pct 0.65 → 0.30 (halve sizing); (c) max_positions 30 → 8 (concentration cap); (d) macro_vix_max 30 (skip earnings runup setups in macro stress). Goal: cut MDD from ~53% to <25% while preserving the +37% return signal.",
+  "base_config": "configs/backtest/return_max_long_v1.json",
+  "overrides": {
+    "signal": {
+      "scoring_model": "return_max_long_v13e",
+      "score_threshold": 0.0,
+      "max_candidates_per_day": 18,
+      "a_tier_score_threshold": 0.99
+    },
+    "risk": {
+      "per_trade_risk_pct": 0.30,
+      "per_trade_risk_pct_a_tier": 0.30,
+      "max_daily_new_risk_pct": 50,
+      "max_positions": 8,
+      "max_positions_per_sector": 4,
+      "max_position_value_pct": 25,
+      "max_adv_fraction": 0.3,
+      "macro_regime_neutral_size_scaler": 1,
+      "macro_regime_risk_off_size_scaler": 1,
+      "veto_unknown_direction": false,
+      "veto_bearish_direction": false,
+      "macro_regime_risk_off_a_tier_only": false,
+      "stop_atr_multiplier": 3,
+      "allow_budget_downsizing": true,
+      "cash_parking_preset": null,
+      "fixed_capital_sizing": false
+    },
+    "execution": {
+      "trailing_warmup_days": 0,
+      "max_holding_days": 7,
+      "early_failure_no_progress_days": 1,
+      "early_failure_no_progress_r": 0.0,
+      "early_failure_no_progress_fraction": 0,
+      "lookback_entry_enabled": false
+    },
+    "event_type_profiles": {
+      "earnings_runup_preevent": {
+        "enabled": true,
+        "direction_filter": "any",
+        "max_holding_days_override": 7
+      }
+    },
+    "idle_alpha_sleeve_preset": null,
+    "form4_capture_sleeve_preset": null,
+    "ownership_capture_sleeve_preset": null,
+    "risk_off_alpha_sleeve_preset": null,
+    "dividend_capture_sleeve_preset": null
+  },
+  "strategy_engines": [
+    {
+      "engine_id": "earnings_runup_preevent_long",
+      "event_types": ["earnings_runup_preevent"],
+      "timing_class": "after_close",
+      "direction": "long_only",
+      "entry_timing_policy": "next_open",
+      "engine_risk_budget_pct": 1.0,
+      "score_threshold_override": 0.0,
+      "max_holding_days": 7,
+      "macro_vix_max": 30.0,
+      "earnings_runup_enabled": true,
+      "earnings_runup_days_to_earnings_min": 3,
+      "earnings_runup_days_to_earnings_max": 7,
+      "earnings_runup_attention_zscore_20d_min": 1.5,
+      "earnings_runup_dollar_volume_zscore_20d_min": 1.0,
+      "earnings_runup_min_avg_dollar_volume": 50000000.0,
+      "earnings_runup_stop_pct": 0.04,
+      "earnings_runup_target_pct": 0.08,
+      "earnings_runup_trailing_activate_pct": 0.05,
+      "earnings_runup_trailing_giveback_pct": 0.03,
+      "earnings_runup_calendar_buffer_days": 1,
+      "enabled": true
+    }
+  ],
+  "tags": ["earnings_runup", "preevent_drift", "poc", "risk_tuned"],
+  "version_family": "earnings_runup",
+  "status": "draft",
+  "changelog": "v2: wire pct-trailing end-to-end (5% activation / 3% entry-relative giveback); cut per_trade_risk 0.65→0.30; cap max_positions 30→8; add macro_vix_max=30.",
+  "parent": "earnings_runup_poc_v1",
+  "performance_summary": null
+}

libs/backtest/domain.py

@@ -103,6 +103,8 @@ class Candidate(BaseModel):
     engine_target_1_fraction: float | None = None
     engine_trailing_model: str | None = None
     engine_trailing_warmup_days: int | None = None
+    engine_trailing_pct_activation: float | None = None  # pct profit above entry to arm trailing
+    engine_trailing_pct_giveback: float | None = None    # pct of entry to give back from peak
     engine_use_reaction_day_low_stop: bool | None = None
     engine_early_failure_close_below_entry_and_reaction_close: bool | None = None
     engine_early_failure_no_progress_days: int | None = None
@@ -1893,6 +1895,15 @@ class ExecutionConfig(BaseModel):
     non_a_tier_target_1_fraction: float | None = None
     trailing_model: str | None = None
     trailing_warmup_days: int = 0              # days after entry before trailing activates
+    # Activation-gated pct trailing (opt-in). When trailing_model startswith "pct_"
+    # AND trailing_pct_activation is not None, the trailing stop is only ratcheted
+    # up after the position's peak P&L exceeds activation_pct (e.g. +5%). The
+    # ratcheted stop is computed as: stop = peak_price - giveback_pct * entry_price
+    # (giveback measured in entry-price terms, NOT peak-price terms — matches the
+    # EarningsRunup-style "lock in profit minus 3%" semantics). Both None preserves
+    # the legacy unconditional pct_X behavior.
+    trailing_pct_activation: float | None = None
+    trailing_pct_giveback: float | None = None
     max_holding_days: int = 10
     lookback_entry_enabled: bool = False       # enter positions for pre-start events still within holding window
     lookback_min_remaining_days: int | None = 3  # min holding days remaining for a lookback entry to be allowed

libs/backtest/earnings_runup.py

@@ -420,15 +420,24 @@ def _build_candidate_from_inputs(
     #     ``stop_pct * close`` for the default dynamic_scaler == 1.0.
     #   target_1_r := target_pct / stop_pct → fixed-R target sits at +target_pct.
     #   target_1_fraction := 1.0 → fully exit at first target.
-    # Trailing pct exits are NOT mapped (no clean equivalent in the standard
+    # Trailing pct exits ARE wired end-to-end via engine_trailing_pct_activation /
-    # trailing system); rely on the engine's trailing_warmup_days override and
+    # engine_trailing_pct_giveback on Candidate → ExecutionConfig overrides →
-    # capture trailing config in features for diagnostics.
+    # update_trailing_stop activation gate. The trailing model name encodes the
+    # giveback for legacy logging; the engine fields override the actual stop.
     synthetic_atr = max(inputs.last_close_price * 0.02, 0.01)
     stop_pct = float(engine.earnings_runup_stop_pct)
     target_pct = float(engine.earnings_runup_target_pct)
     stop_mult = stop_pct / 0.02 if stop_pct > 0 else 2.0
     target_r = target_pct / stop_pct if stop_pct > 0 else 2.0
 
+    # Pct-trailing wiring: pick a "pct_<int>" model whose name reflects the
+    # giveback (used as fallback if pct_giveback is somehow None at runtime,
+    # and shown in trade diagnostics).
+    trailing_giveback = float(engine.earnings_runup_trailing_giveback_pct)
+    trailing_activation = float(engine.earnings_runup_trailing_activate_pct)
+    trailing_giveback_name = max(1, int(round(trailing_giveback * 100)))
+    pct_trailing_model = f"pct_{trailing_giveback_name}"
+
     # Score is a deterministic function of the two z-scores so it ranks
     # candidates without leaking future information.
     z_sum = inputs.attention_zscore_20d + inputs.dollar_volume_zscore_20d
@@ -485,8 +494,17 @@ def _build_candidate_from_inputs(
         # Map pct-based EarningsRunup exits → engine_*-prefixed overrides on the candidate.
         engine_target_1_r=target_r,
         engine_target_1_fraction=1.0,
-        engine_trailing_model=engine.trailing_model_override,
+        # Trailing: prefer engine-level override; fall back to pct trailing model
-        engine_trailing_warmup_days=engine.trailing_warmup_days_override,
+        # derived from the engine's giveback config so the activation-gated
+        # trailing path is used in update_trailing_stop.
+        engine_trailing_model=engine.trailing_model_override or pct_trailing_model,
+        engine_trailing_warmup_days=(
+            engine.trailing_warmup_days_override
+            if engine.trailing_warmup_days_override is not None
+            else 0
+        ),
+        engine_trailing_pct_activation=trailing_activation,
+        engine_trailing_pct_giveback=trailing_giveback,
         engine_stop_atr_multiplier=stop_mult,
         engine_next_open_gap_cap_pct=engine.next_open_gap_cap_pct,
         engine_use_reaction_day_low_stop=False,

libs/backtest/execution.py

@@ -462,6 +462,8 @@ def update_trailing_stop(
     bar: dict[str, Any],
     trailing_model: str = "bar_low",
     warmup_days: int = 0,
+    pct_activation: float | None = None,
+    pct_giveback: float | None = None,
 ) -> None:
     """Ratchet stop towards price for trailing model. Mutates position in place.
 
@@ -475,6 +477,16 @@ def update_trailing_stop(
 
     Args:
         warmup_days: Skip trailing until position has been held this many days.
+        pct_activation: Optional. When set together with ``trailing_model`` of
+            ``pct_*`` form, trailing only arms after the position's unrealized
+            P&L exceeds ``pct_activation`` (e.g. ``0.05`` = +5%). Until armed,
+            the stop stays at the static entry stop. None = legacy behavior
+            (trail unconditionally after warmup).
+        pct_giveback: Optional. When set, overrides the percentage parsed from
+            the ``trailing_model`` string and uses entry-price-relative
+            giveback: ``stop = peak_price - pct_giveback * entry_price``. This
+            preserves the EarningsRunup "lock in profit minus 3% of entry"
+            semantics. None = legacy ``peak * (1 - trail_pct)`` behavior.
     """
     is_short = position.plan.candidate.trade_direction == "short"
 
@@ -492,6 +504,19 @@ def update_trailing_stop(
     if position.days_held < warmup_days:
         return
 
+    # Activation gate: when pct_activation is set on a pct_* model, only ratchet
+    # the stop after peak_pnl crosses the activation threshold.
+    if pct_activation is not None and trailing_model.startswith("pct_"):
+        entry_price = position.entry_price
+        if entry_price <= 0:
+            return
+        if is_short:
+            peak_pnl_pct = (entry_price - position.peak_price) / entry_price
+        else:
+            peak_pnl_pct = (position.peak_price - entry_price) / entry_price
+        if peak_pnl_pct < pct_activation:
+            return
+
     if is_short:
         # Short: trail stop DOWN towards price (tighter = lower stop)
         if trailing_model == "bar_low" or trailing_model == "bar_high":
@@ -499,6 +524,10 @@ def update_trailing_stop(
             if bar_high is not None:
                 position.current_stop = min(position.current_stop, float(bar_high))
         elif trailing_model.startswith("pct_"):
+            if pct_giveback is not None:
+                # Entry-relative giveback (EarningsRunup semantics)
+                trail_stop = position.peak_price + pct_giveback * position.entry_price
+            else:
                 try:
                     trail_pct = float(trailing_model.split("_")[1]) / 100.0
                 except (IndexError, ValueError):
@@ -513,6 +542,11 @@ def update_trailing_stop(
                 new_stop = max(position.current_stop, float(bar_low))
                 position.current_stop = new_stop
         elif trailing_model.startswith("pct_"):
+            if pct_giveback is not None:
+                # Entry-relative giveback (EarningsRunup semantics):
+                # stop = peak - giveback*entry → "lock in (peak_pnl - giveback)"
+                trail_stop = position.peak_price - pct_giveback * position.entry_price
+            else:
                 try:
                     trail_pct = float(trailing_model.split("_")[1]) / 100.0
                 except (IndexError, ValueError):
@@ -694,6 +728,10 @@ def build_effective_execution_config(
         execution_updates["trailing_model"] = candidate.engine_trailing_model
     if candidate.engine_trailing_warmup_days is not None:
         execution_updates["trailing_warmup_days"] = candidate.engine_trailing_warmup_days
+    if candidate.engine_trailing_pct_activation is not None:
+        execution_updates["trailing_pct_activation"] = candidate.engine_trailing_pct_activation
+    if candidate.engine_trailing_pct_giveback is not None:
+        execution_updates["trailing_pct_giveback"] = candidate.engine_trailing_pct_giveback
     if candidate.engine_early_failure_close_below_entry_and_reaction_close is not None:
         execution_updates["early_failure_close_below_entry_and_reaction_close"] = (
             candidate.engine_early_failure_close_below_entry_and_reaction_close

tests/unit/backtest/test_earnings_runup.py

@@ -627,3 +627,193 @@ def test_exit_trailing_giveback_after_activation():
     assert trade.exit_reason == ExitReason.STOP
     # Confirm exit price is above original entry — i.e. the trailing stop captured profit.
     assert trade.exit_price > pos.entry_price
+
+
+# ---------------------------------------------------------------------------
+# Pct-trailing wiring tests — verify update_trailing_stop honors activation
+# threshold and entry-relative giveback (EarningsRunup-style trailing).
+# ---------------------------------------------------------------------------
+
+
+def _bar(*, low: float, high: float, open_: float | None = None, close: float | None = None) -> dict[str, Any]:
+    return {
+        "date": dt.date(2026, 4, 15),
+        "open": open_ if open_ is not None else (low + high) / 2,
+        "high": high,
+        "low": low,
+        "close": close if close is not None else (low + high) / 2,
+        "volume": 1_000_000,
+    }
+
+
+def test_pct_trailing_does_not_arm_below_activation_threshold():
+    """Position at +3% (activation=5%) → stop unchanged at -4% from entry."""
+    from libs.backtest.execution import update_trailing_stop
+
+    pos = _build_position_for_runup(entry_price=100.0)
+    # Bar with high=103 (+3% peak), low=101 → not yet at activation (+5%)
+    update_trailing_stop(
+        pos, _bar(low=101.0, high=103.0),
+        trailing_model="pct_3",
+        warmup_days=0,
+        pct_activation=0.05,
+        pct_giveback=0.03,
+    )
+    # peak should track high=103
+    assert pos.peak_price == 103.0
+    # stop should NOT have moved up — still at -4% = 96.0
+    assert pos.current_stop == 96.0
+
+
+def test_pct_trailing_arms_at_activation_threshold():
+    """Peak hits +5% → stop raised to +2% (activation 5% - giveback 3% = 2%)."""
+    from libs.backtest.execution import update_trailing_stop
+
+    pos = _build_position_for_runup(entry_price=100.0)
+    update_trailing_stop(
+        pos, _bar(low=102.0, high=105.0),
+        trailing_model="pct_3",
+        warmup_days=0,
+        pct_activation=0.05,
+        pct_giveback=0.03,
+    )
+    # peak = 105, stop = peak - giveback*entry = 105 - 0.03*100 = 102.0
+    assert pos.peak_price == 105.0
+    assert pos.current_stop == pytest.approx(102.0)
+
+
+def test_pct_trailing_ratchets_up_with_continued_profit():
+    """Peak rises to +7% → stop raised to +4% (peak - 3% of entry)."""
+    from libs.backtest.execution import update_trailing_stop
+
+    pos = _build_position_for_runup(entry_price=100.0)
+    # First armed at peak=105 → stop=102
+    update_trailing_stop(
+        pos, _bar(low=102.0, high=105.0),
+        trailing_model="pct_3", warmup_days=0,
+        pct_activation=0.05, pct_giveback=0.03,
+    )
+    assert pos.current_stop == pytest.approx(102.0)
+    # Continued profit: peak now 107
+    update_trailing_stop(
+        pos, _bar(low=104.0, high=107.0),
+        trailing_model="pct_3", warmup_days=0,
+        pct_activation=0.05, pct_giveback=0.03,
+    )
+    assert pos.peak_price == 107.0
+    assert pos.current_stop == pytest.approx(104.0)
+
+
+def test_pct_trailing_does_not_ratchet_down_on_pullback():
+    """Peak 107 (stop 104) then peak holds at 107 while bar drops to 105 → stop stays at 104."""
+    from libs.backtest.execution import update_trailing_stop
+
+    pos = _build_position_for_runup(entry_price=100.0)
+    # Establish peak=107, stop=104
+    update_trailing_stop(
+        pos, _bar(low=102.0, high=107.0),
+        trailing_model="pct_3", warmup_days=0,
+        pct_activation=0.05, pct_giveback=0.03,
+    )
+    assert pos.current_stop == pytest.approx(104.0)
+    assert pos.peak_price == 107.0
+    # Pullback: bar high=106 (below previous peak), low=105
+    update_trailing_stop(
+        pos, _bar(low=105.0, high=106.0),
+        trailing_model="pct_3", warmup_days=0,
+        pct_activation=0.05, pct_giveback=0.03,
+    )
+    # Peak unchanged; stop must stay (not ratchet down)
+    assert pos.peak_price == 107.0
+    assert pos.current_stop == pytest.approx(104.0)
+
+
+def test_pct_trailing_reversal_triggers_stop_exit_with_profit():
+    """Peak +7% → stop +4%; then bar low touches +3% → position exits via STOP at +4%."""
+    from libs.backtest.domain import ExitReason
+    from libs.backtest.execution import simulate_exit, update_trailing_stop
+
+    pos = _build_position_for_runup(entry_price=100.0)
+    # Day 1: peak rises to 107, stop ratchets to 104
+    update_trailing_stop(
+        pos, _bar(low=102.0, high=107.0),
+        trailing_model="pct_3", warmup_days=0,
+        pct_activation=0.05, pct_giveback=0.03,
+    )
+    assert pos.current_stop == pytest.approx(104.0)
+
+    # Day 2: bar opens at 105.5, drops to 103.5 → trailing stop at 104.0 hit.
+    pos.days_held = 1
+    bar2 = _bar(low=103.5, high=105.5, open_=105.5, close=104.0)
+    # First update peak (no new high)
+    update_trailing_stop(
+        pos, bar2,
+        trailing_model="pct_3", warmup_days=0,
+        pct_activation=0.05, pct_giveback=0.03,
+    )
+    # Stop still at 104 (peak unchanged)
+    assert pos.current_stop == pytest.approx(104.0)
+    # Now simulate exit: bar.low=103.5 < stop=104 → STOP exit at 104
+    trade = simulate_exit(pos, bar2, _exec_config_for_exit_test(), dt.date(2026, 4, 15))
+    assert trade is not None
+    assert trade.exit_reason == ExitReason.STOP
+    # Exit price ~= 104.0 (the trailing stop, less small slippage), above entry → profit captured
+    assert trade.exit_price == pytest.approx(104.0, rel=0.005)
+    assert trade.exit_price > pos.entry_price
+
+
+def test_pct_trailing_legacy_behavior_when_activation_none():
+    """Regression: pct_3 with activation=None must trail unconditionally (legacy behavior)."""
+    from libs.backtest.execution import update_trailing_stop
+
+    pos = _build_position_for_runup(entry_price=100.0)
+    # Even at +1% peak, legacy pct_3 trails to peak * 0.97 = 100*0.97 = 97 (only ratchets if > current_stop)
+    # Note: position's current_stop starts at 96, and 101*0.97=97.97 > 96, so it should ratchet up.
+    update_trailing_stop(
+        pos, _bar(low=100.0, high=101.0),
+        trailing_model="pct_3", warmup_days=0,
+        pct_activation=None, pct_giveback=None,
+    )
+    assert pos.peak_price == 101.0
+    # Legacy formula: peak * (1 - 0.03) = 97.97 (ratchets up from 96)
+    assert pos.current_stop == pytest.approx(97.97)
+
+
+def test_pct_trailing_via_engine_candidate_in_effective_exec():
+    """End-to-end: candidate built from engine carries pct trailing fields into effective exec."""
+    from libs.backtest.execution import build_effective_execution_config
+
+    setup = _build_full_setup()
+    engine = _make_engine(
+        earnings_runup_stop_pct=0.04,
+        earnings_runup_target_pct=0.08,
+        earnings_runup_trailing_activate_pct=0.05,
+        earnings_runup_trailing_giveback_pct=0.03,
+    )
+    cands = build_earnings_runup_candidates(
+        decision_date=setup["decision_date"],
+        next_trading_date=setup["next_trading_date"],
+        universe_symbols=[setup["symbol"]],
+        engine=engine,
+        upcoming_earnings_provider=setup["upcoming_provider"],
+        attention_provider=setup["attention_provider"],
+        bar_provider=setup["bar_provider"],
+    )
+    assert len(cands) == 1
+    cand = cands[0]
+    # Candidate has the new pct trailing fields
+    assert cand.engine_trailing_model == "pct_3"
+    assert cand.engine_trailing_pct_activation == pytest.approx(0.05)
+    assert cand.engine_trailing_pct_giveback == pytest.approx(0.03)
+
+    # Build a minimal BacktestConfig and check effective_exec inherits these
+    from libs.backtest.domain import BacktestConfig, ExecutionConfig
+    base_cfg = BacktestConfig(
+        strategy_name="test",
+        dataset_snapshot_id="test",
+        execution=ExecutionConfig(max_holding_days=4),
+    )
+    eff = build_effective_execution_config(cand, base_cfg)
+    assert eff.trailing_model == "pct_3"
+    assert eff.trailing_pct_activation == pytest.approx(0.05)
+    assert eff.trailing_pct_giveback == pytest.approx(0.03)