redesign activation gate to expected value + make pipelines cron-configurable

Diagnosing "no qualified signals for 5 days": setups were generated but none
qualified. The gate required BOTH a high min_rr (2.0) AND a high
min_target_probability (60), which became contradictory after the Jun-15
probability recalibration — probability already embeds R:R via the 1/(rr+1) ruin
term, so high-R:R targets are inherently low-probability and nothing cleared both.

Gate is now expected value (R): p*rr - (1-p) from the primary target's
probability. R:R and confidence stay as floors; high-conviction / exclude-conflicts
/ min-target-probability become optional tighteners (default off). Defaults:
min_expected_value=0.15, min_rr=1.2, min_confidence=55. EV is only enforced when
computable. Migration 009 clears stored activation_* rows so the new defaults
apply. Backtest sweeps min_expected_value instead of target probability.

Scheduling: pipelines are now cron-configurable in Admin -> Jobs. daily_pipeline
(full, default 0 7 * * *) plus a new light intraday_pipeline (OHLCV + outcome eval,
default hourly US session) that keeps prices/live-R:R current without setup churn.
Fundamentals on its own early weekly cron. Timezone configurable (default
Europe/Berlin). Moving interval->CronTrigger also fixes the restart-deferral bug
where an interval job's countdown resets on every process restart.

319 backend unit tests pass; frontend tsc clean.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

alembic/versions/009_reset_activation_gate.py

@@ -0,0 +1,40 @@
+"""reset activation gate settings for the EV-based redesign
+
+The activation gate was redesigned around expected value (R): the core test is
+now ``min_expected_value`` instead of the old, self-contradicting pair of a high
+``min_rr`` AND a high ``min_target_probability`` (with the post-recalibration
+probability model the two could not be satisfied together, so nothing qualified).
+The conviction / conflict toggles are now optional tighteners that default off.
+
+Stored ``activation_*`` rows from the old gate no longer map cleanly onto the new
+one, so they are cleared here and the redesigned code defaults take effect. Re-tune
+in Admin → Activation (validated against the Track Record's backtest EV sweep).
+
+Revision ID: 009
+Revises: 008
+Create Date: 2026-06-23 00:00:00.000000
+
+"""
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision: str = "009"
+down_revision: Union[str, None] = "008"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    op.execute(
+        sa.text("DELETE FROM system_settings WHERE key LIKE 'activation\\_%' ESCAPE '\\'")
+    )
+
+
+def downgrade() -> None:
+    # One-way data reset — the old per-key values aren't recoverable. Code defaults
+    # apply until re-tuned, so there is nothing to restore.
+    pass

app/main.py

@@ -68,7 +68,7 @@ from app.config import settings
 from app.database import async_session_factory, engine
 from app.middleware import register_exception_handlers
 from app.models.user import User
-from app.scheduler import configure_scheduler, scheduler
+from app.scheduler import configure_scheduler, load_schedule_config, scheduler
 from app.routers.admin import router as admin_router
 from app.routers.auth import router as auth_router
 from app.routers.health import router as health_router
@@ -128,8 +128,9 @@ async def lifespan(_app: FastAPI) -> AsyncGenerator[None, None]:
 
     async with async_session_factory() as session:
         await _create_default_admin(session)
+        schedule_config = await load_schedule_config(session)
 
-    configure_scheduler()
+    configure_scheduler(schedule_config)
     scheduler.start()
     logger.info("Scheduler started")
 

app/routers/admin.py

@@ -15,6 +15,7 @@ from app.schemas.admin import (
     DataCleanupRequest,
     JobToggle,
     RecommendationConfigUpdate,
+    ScheduleConfigUpdate,
     SentimentConfigUpdate,
     SentimentTestRequest,
     PasswordReset,
@@ -176,6 +177,28 @@ async def update_activation_settings(
     return APIEnvelope(status="success", data=updated)
 
 
+@router.get("/admin/settings/schedule", response_model=APIEnvelope)
+async def get_schedule_settings(
+    _admin: User = Depends(require_admin),
+    db: AsyncSession = Depends(get_db),
+):
+    config = await admin_service.get_schedule_config(db)
+    return APIEnvelope(status="success", data=config)
+
+
+@router.put("/admin/settings/schedule", response_model=APIEnvelope)
+async def update_schedule_settings(
+    body: ScheduleConfigUpdate,
+    _admin: User = Depends(require_admin),
+    db: AsyncSession = Depends(get_db),
+):
+    updated = await admin_service.update_schedule_config(
+        db,
+        body.model_dump(exclude_unset=True, exclude_none=True),
+    )
+    return APIEnvelope(status="success", data=updated)
+
+
 @router.get("/admin/settings/sentiment", response_model=APIEnvelope)
 async def get_sentiment_settings(
     _admin: User = Depends(require_admin),

app/scheduler.py

@@ -19,6 +19,7 @@ import asyncio
 from datetime import date, datetime, timedelta, timezone
 
 from apscheduler.schedulers.asyncio import AsyncIOScheduler
+from apscheduler.triggers.cron import CronTrigger
 from sqlalchemy import case, func, or_, select
 from sqlalchemy.ext.asyncio import AsyncSession
 
@@ -168,6 +169,17 @@ _job_runtime: dict[str, dict[str, object]] = {
         "finished_at": None,
         "message": None,
     },
+    "intraday_pipeline": {
+        "running": False,
+        "status": "idle",
+        "processed": 0,
+        "total": None,
+        "progress_pct": None,
+        "current_ticker": None,
+        "started_at": None,
+        "finished_at": None,
+        "message": None,
+    },
 }
 
 
@@ -1000,7 +1012,9 @@ async def sync_ticker_universe() -> None:
 # Steps run in dependency order: each uses fresh output from the previous one.
 # (name, coroutine) — the names match the individual jobs so each step still
 # updates its own runtime status while the pipeline runs.
-_PIPELINE_STEPS = [
+#
+# Daily (full): the complete data→signal refresh, once a day.
+_DAILY_PIPELINE_STEPS = [
     ("data_collector", "collect_ohlcv"),
     ("sentiment_collector", "collect_sentiment"),
     ("rr_scanner", "scan_rr"),
@@ -1008,28 +1022,41 @@ _PIPELINE_STEPS = [
     ("market_regime", "compute_market_regime"),
 ]
 
+# Intraday (light): keep prices current and resolve outcomes through the day,
+# without the expensive scan/sentiment. The dashboard recomputes live R:R from
+# the latest price, so refreshing OHLCV is enough to stop prices lagging; the
+# outcome step also closes paper trades that hit their stop/target intraday.
+_INTRADAY_PIPELINE_STEPS = [
+    ("data_collector", "collect_ohlcv"),
+    ("outcome_evaluator", "evaluate_outcomes"),
+]
 
-async def run_daily_pipeline() -> None:
-    """Run the daily data→signal flow in dependency order.
 
-    OHLCV → fundamentals → sentiment → R:R scan → outcome eval (+paper close) →
+async def _run_pipeline(job_name: str, steps: list[tuple[str, str]]) -> None:
-    market regime. Each step respects its own enable flag and manages its own
+    """Run an ordered list of (step_name, coroutine_name) steps.
-    runtime status; a failing step is logged and the pipeline continues.
+
+    Each step respects its own enable flag and manages its own runtime status; a
+    failing step is logged and the pipeline continues with the next one.
     """
-    job_name = "daily_pipeline"
     logger.info(json.dumps({"event": "job_start", "job": job_name}))
-    total = len(_PIPELINE_STEPS)
+    async with async_session_factory() as db:
+        if not await _is_job_enabled(db, job_name):
+            logger.info(json.dumps({"event": "job_skipped", "job": job_name, "reason": "disabled"}))
+            _runtime_finish(job_name, "skipped", processed=0, total=0, message="Disabled")
+            return
+
+    total = len(steps)
     _runtime_start(job_name, total=total)
 
     funcs = globals()
     done = 0
     try:
-        for step_name, func_name in _PIPELINE_STEPS:
+        for step_name, func_name in steps:
             _runtime_progress(job_name, processed=done, total=total, current_ticker=step_name)
             try:
                 await funcs[func_name]()
             except Exception:
-                logger.exception("Daily pipeline step %s failed", step_name)
+                logger.exception("%s step %s failed", job_name, step_name)
             done += 1
         _runtime_finish(job_name, "completed", processed=done, total=total, message="Pipeline complete")
         logger.info(json.dumps({"event": "job_complete", "job": job_name}))
@@ -1041,6 +1068,17 @@ async def run_daily_pipeline() -> None:
         }))
 
 
+async def run_daily_pipeline() -> None:
+    """Full daily flow: OHLCV → sentiment → R:R scan → outcome eval (+paper
+    close) → market regime."""
+    await _run_pipeline("daily_pipeline", _DAILY_PIPELINE_STEPS)
+
+
+async def run_intraday_pipeline() -> None:
+    """Light intraday flow: refresh OHLCV → evaluate outcomes (+paper close)."""
+    await _run_pipeline("intraday_pipeline", _INTRADAY_PIPELINE_STEPS)
+
+
 # ---------------------------------------------------------------------------
 # Frequency helpers
 # ---------------------------------------------------------------------------
@@ -1057,22 +1095,91 @@ def _parse_frequency(freq: str) -> dict[str, int]:
     return _FREQUENCY_MAP.get(freq.lower(), {"hours": 24})
 
 
+# ---------------------------------------------------------------------------
+# Schedule config (cron, admin-configurable)
+# ---------------------------------------------------------------------------
+#
+# The cron-driven jobs read their schedule from SystemSettings so it can be
+# tuned from Admin → Jobs without a redeploy. A wall-clock CronTrigger also fixes
+# the interval-trigger pitfall: an interval job resets its countdown to now+N on
+# every process restart, so on a box that's redeployed often it can keep being
+# deferred and never fire. Cron fires at a fixed local time regardless.
+
+SCHEDULE_DEFAULTS: dict[str, str] = {
+    "schedule_timezone": "Europe/Berlin",
+    "schedule_daily_pipeline_cron": "0 7 * * *",        # full refresh, ready by ~8am
+    "schedule_intraday_pipeline_cron": "0 14-22 * * 1-5",  # hourly across the US session
+    "schedule_fundamentals_cron": "0 4 * * 1",          # weekly, early Monday (slow job)
+}
+
+# job id -> schedule setting key
+_CRON_JOBS: dict[str, str] = {
+    "daily_pipeline": "schedule_daily_pipeline_cron",
+    "intraday_pipeline": "schedule_intraday_pipeline_cron",
+    "fundamental_collector": "schedule_fundamentals_cron",
+}
+
+
+def validate_cron(expr: str, timezone: str) -> None:
+    """Raise ValueError if the cron expression or timezone is invalid."""
+    CronTrigger.from_crontab((expr or "").strip(), timezone=(timezone or "").strip())
+
+
+def _cron_trigger(expr: str, timezone: str, fallback_key: str) -> CronTrigger:
+    """Build a CronTrigger, falling back to the default (UTC) on a bad value."""
+    try:
+        return CronTrigger.from_crontab(expr.strip(), timezone=timezone.strip())
+    except Exception:
+        logger.warning(json.dumps({
+            "event": "invalid_cron", "expr": expr, "timezone": timezone,
+            "fallback": SCHEDULE_DEFAULTS[fallback_key],
+        }))
+        return CronTrigger.from_crontab(SCHEDULE_DEFAULTS[fallback_key], timezone="UTC")
+
+
+async def load_schedule_config(db: AsyncSession) -> dict[str, str]:
+    """Read the cron schedule config from SystemSettings, defaults for any unset."""
+    result = await db.execute(
+        select(SystemSetting).where(SystemSetting.key.in_(list(SCHEDULE_DEFAULTS)))
+    )
+    stored = {s.key: s.value for s in result.scalars().all()}
+    return {key: (stored.get(key) or default) for key, default in SCHEDULE_DEFAULTS.items()}
+
+
+def reschedule_jobs(schedule_config: dict[str, str]) -> dict[str, str]:
+    """Re-apply cron triggers to the running scheduler after a settings change."""
+    tz = schedule_config.get("schedule_timezone") or SCHEDULE_DEFAULTS["schedule_timezone"]
+    applied: dict[str, str] = {}
+    for job_id, key in _CRON_JOBS.items():
+        if scheduler.get_job(job_id) is None:
+            continue
+        expr = schedule_config.get(key) or SCHEDULE_DEFAULTS[key]
+        scheduler.reschedule_job(job_id, trigger=_cron_trigger(expr, tz, key))
+        applied[job_id] = expr
+    logger.info(json.dumps({"event": "jobs_rescheduled", "applied": applied, "timezone": tz}))
+    return applied
+
+
 # ---------------------------------------------------------------------------
 # Scheduler setup
 # ---------------------------------------------------------------------------
 
 
-def configure_scheduler() -> None:
+def configure_scheduler(schedule_config: dict[str, str] | None = None) -> None:
-    """Add all jobs to the scheduler with configured intervals.
+    """Add all jobs to the scheduler.
 
-    Call this once before scheduler.start(). Removes any existing jobs first
+    Call this once before scheduler.start(). Removes any existing jobs first to
-    to ensure idempotency.
+    ensure idempotency. ``schedule_config`` supplies the cron strings + timezone
+    for the cron-driven jobs (daily/intraday pipelines, fundamentals); defaults
+    are used for anything missing.
     """
+    cfg = {**SCHEDULE_DEFAULTS, **(schedule_config or {})}
+    tz = cfg["schedule_timezone"]
     scheduler.remove_all_jobs()
 
     # Pipeline members: registered but PAUSED (next_run_time=None) so they never
-    # auto-fire on their own timer — the daily_pipeline drives them in order. The
+    # auto-fire on their own timer — the pipelines drive them in order. The long
-    # long interval is just a backstop after a manual trigger (which re-arms an
+    # interval is just a backstop after a manual trigger (which re-arms an
     # interval job). They stay manually triggerable from Admin → Jobs.
     _members = [
         (collect_ohlcv, "data_collector", "Data Collector (OHLCV)"),
@@ -1087,23 +1194,30 @@ def configure_scheduler() -> None:
             replace_existing=True, next_run_time=None,
         )
 
-    # Daily Pipeline — the single ordered daily flow
+    # Cron-driven jobs (admin-configurable times)
     scheduler.add_job(
-        run_daily_pipeline, "interval", hours=24,
+        run_daily_pipeline,
+        _cron_trigger(cfg["schedule_daily_pipeline_cron"], tz, "schedule_daily_pipeline_cron"),
         id="daily_pipeline", name="Daily Pipeline", replace_existing=True,
     )
+    scheduler.add_job(
+        run_intraday_pipeline,
+        _cron_trigger(cfg["schedule_intraday_pipeline_cron"], tz, "schedule_intraday_pipeline_cron"),
+        id="intraday_pipeline", name="Intraday Pipeline", replace_existing=True,
+    )
+    # Fundamentals — quarterly-ish data; weekly by default (conserves API quota).
+    # Its own early cron so the slow, rate-limited fetch finishes before the day.
+    scheduler.add_job(
+        collect_fundamentals,
+        _cron_trigger(cfg["schedule_fundamentals_cron"], tz, "schedule_fundamentals_cron"),
+        id="fundamental_collector", name="Fundamental Collector", replace_existing=True,
+    )
 
-    # Independent jobs (own cadence, no ordering dependency)
+    # Independent interval jobs (own cadence, no ordering dependency)
     scheduler.add_job(
         sync_ticker_universe, "interval", hours=24,
         id="ticker_universe_sync", name="Ticker Universe Sync", replace_existing=True,
     )
-    # Fundamentals — quarterly-ish data; weekly by default (conserves API quota)
-    fund_interval = _parse_frequency(settings.fundamental_fetch_frequency)
-    scheduler.add_job(
-        collect_fundamentals, "interval", **fund_interval,
-        id="fundamental_collector", name="Fundamental Collector", replace_existing=True,
-    )
     alerts_interval = _parse_frequency(settings.alerts_frequency)
     scheduler.add_job(
         dispatch_alerts_job, "interval", **alerts_interval,
@@ -1117,7 +1231,16 @@ def configure_scheduler() -> None:
     logger.info(
         json.dumps({
             "event": "scheduler_configured",
-            "daily_pipeline": [name for name, _ in _PIPELINE_STEPS],
+            "timezone": tz,
+            "daily_pipeline": {
+                "cron": cfg["schedule_daily_pipeline_cron"],
+                "steps": [name for name, _ in _DAILY_PIPELINE_STEPS],
+            },
+            "intraday_pipeline": {
+                "cron": cfg["schedule_intraday_pipeline_cron"],
+                "steps": [name for name, _ in _INTRADAY_PIPELINE_STEPS],
+            },
+            "fundamental_collector": {"cron": cfg["schedule_fundamentals_cron"]},
             "independent": ["ticker_universe_sync", "alerts", "backtest"],
         })
     )

app/schemas/admin.py

@@ -59,6 +59,7 @@ class TickerUniverseUpdate(BaseModel):
 
 class ActivationConfigUpdate(BaseModel):
     """Activation gate: what counts as an actionable signal."""
+    min_expected_value: float | None = Field(default=None, ge=-1, le=10)
     min_rr: float | None = Field(default=None, ge=0)
     min_confidence: float | None = Field(default=None, ge=0, le=100)
     min_target_probability: float | None = Field(default=None, ge=0, le=100)
@@ -66,6 +67,15 @@ class ActivationConfigUpdate(BaseModel):
     exclude_conflicts: bool | None = None
 
 
+class ScheduleConfigUpdate(BaseModel):
+    """Cron schedule for the pipelines + fundamentals. Crons are 5-field
+    (min hour dom month dow); timezone is an IANA name (e.g. Europe/Berlin)."""
+    schedule_timezone: str | None = Field(default=None, max_length=64)
+    schedule_daily_pipeline_cron: str | None = Field(default=None, max_length=120)
+    schedule_intraday_pipeline_cron: str | None = Field(default=None, max_length=120)
+    schedule_fundamentals_cron: str | None = Field(default=None, max_length=120)
+
+
 class SentimentConfigUpdate(BaseModel):
     """Runtime sentiment LLM config. api_key is write-only; omit/empty to keep
     the stored key."""

app/services/admin_service.py

@@ -1,5 +1,6 @@
 """Admin service: user management, system settings, data cleanup, job control."""
 
+import logging
 from datetime import datetime, timedelta, timezone
 
 from passlib.hash import bcrypt
@@ -17,6 +18,8 @@ from app.models.ticker import Ticker
 from app.models.trade_setup import TradeSetup
 from app.models.user import User
 
+logger = logging.getLogger(__name__)
+
 RECOMMENDATION_CONFIG_DEFAULTS: dict[str, float] = {
     "recommendation_high_confidence_threshold": 70.0,
     "recommendation_moderate_confidence_threshold": 50.0,
@@ -35,10 +38,12 @@ SUPPORTED_TICKER_UNIVERSES = {"sp500", "nasdaq100", "nasdaq_all"}
 # Track Record's qualified stats. The outcome evaluator deliberately ignores
 # these — every setup is evaluated so the gate itself can be validated.
 #
-# Beyond raw R:R and confidence, the gate demands conviction: a high-conviction
+# The core test is expected value (in R): probability-weighted asymmetry, so a
-# action (LONG_HIGH / SHORT_HIGH), a clean read (risk Low / no conflicts), and a
+# fat-but-improbable target and a likely-but-thin one are both rejected. R:R and
-# probable primary target.
+# confidence are floors; high-conviction / clean-read / target-probability are
+# optional tighteners (off by default — turn on to be more selective).
 _ACTIVATION_FLOAT_KEYS: dict[str, str] = {
+    "min_expected_value": "activation_min_expected_value",
     "min_rr": "activation_min_rr",
     "min_confidence": "activation_min_confidence",
     "min_target_probability": "activation_min_target_probability",
@@ -48,11 +53,12 @@ _ACTIVATION_BOOL_KEYS: dict[str, str] = {
     "exclude_conflicts": "activation_exclude_conflicts",
 }
 ACTIVATION_DEFAULTS: dict[str, float | bool] = {
-    "min_rr": 2.0,
+    "min_expected_value": 0.15,
-    "min_confidence": 70.0,
+    "min_rr": 1.2,
-    "min_target_probability": 60.0,
+    "min_confidence": 55.0,
-    "require_high_conviction": True,
+    "min_target_probability": 0.0,
-    "exclude_conflicts": True,
+    "require_high_conviction": False,
+    "exclude_conflicts": False,
 }
 
 
@@ -195,6 +201,8 @@ async def update_activation_config(
     db: AsyncSession, updates: dict[str, float | bool]
 ) -> dict[str, float | bool]:
     """Update the activation gate. Accepts public keys; only supplied keys change."""
+    if "min_expected_value" in updates and not -1.0 <= updates["min_expected_value"] <= 10.0:
+        raise ValidationError("min_expected_value must be between -1 and 10 (R units)")
     if "min_rr" in updates and updates["min_rr"] < 0:
         raise ValidationError("min_rr must be >= 0")
     if "min_confidence" in updates and not 0 <= updates["min_confidence"] <= 100:
@@ -212,6 +220,59 @@ async def update_activation_config(
     return await get_activation_config(db)
 
 
+# ---------------------------------------------------------------------------
+# Pipeline schedule (cron)
+# ---------------------------------------------------------------------------
+
+async def get_schedule_config(db: AsyncSession) -> dict[str, str]:
+    """Cron schedule for the daily/intraday pipelines and fundamentals."""
+    from app.scheduler import load_schedule_config
+
+    return await load_schedule_config(db)
+
+
+async def update_schedule_config(
+    db: AsyncSession, updates: dict[str, str]
+) -> dict[str, str]:
+    """Validate, persist, and apply cron schedule changes to the running scheduler."""
+    from app.scheduler import (
+        SCHEDULE_DEFAULTS,
+        load_schedule_config,
+        reschedule_jobs,
+        validate_cron,
+    )
+
+    current = await load_schedule_config(db)
+    tz = (updates.get("schedule_timezone") or current["schedule_timezone"]).strip()
+
+    for key, value in updates.items():
+        if key not in SCHEDULE_DEFAULTS:
+            raise ValidationError(f"Unknown schedule key: {key}")
+        if key == "schedule_timezone":
+            # Validate the timezone against an existing cron expression.
+            try:
+                validate_cron(current["schedule_daily_pipeline_cron"], value)
+            except Exception as exc:
+                raise ValidationError(f"Invalid timezone: {value}") from exc
+        else:
+            try:
+                validate_cron(value, tz)
+            except Exception as exc:
+                raise ValidationError(f"Invalid cron for {key}: {value!r}") from exc
+
+    for key, value in updates.items():
+        await update_setting(db, key, str(value).strip())
+
+    new_config = await load_schedule_config(db)
+    try:
+        reschedule_jobs(new_config)
+    except Exception:
+        # Scheduler may not be running (e.g. unit tests) — the config is saved
+        # regardless and applied on next startup.
+        logger.warning("Could not reschedule jobs after config update", exc_info=True)
+    return new_config
+
+
 def _recommendation_public_to_storage_key(key: str) -> str:
     return f"recommendation_{key}"
 
@@ -486,6 +547,7 @@ VALID_JOB_NAMES = {
     "market_regime",
     "backtest",
     "daily_pipeline",
+    "intraday_pipeline",
 }
 
 JOB_LABELS = {
@@ -499,6 +561,7 @@ JOB_LABELS = {
     "market_regime": "Market Regime",
     "backtest": "Backtest",
     "daily_pipeline": "Daily Pipeline",
+    "intraday_pipeline": "Intraday Pipeline",
 }
 
 # Jobs driven by the daily_pipeline (in order) rather than their own timer.

app/services/backtest_service.py

@@ -36,7 +36,11 @@ from app.services.outcome_service import (
     evaluate_setup_against_bars,
 )
 from app.services.price_service import query_ohlcv
-from app.services.qualification import best_target_probability, setup_qualifies
+from app.services.qualification import (
+    best_target_probability,
+    expected_value_r,
+    setup_qualifies,
+)
 from app.services.recommendation_service import (
     _choose_recommended_action,
     _classify_by_probability,
@@ -131,6 +135,10 @@ def _window_setups(
         primary = _select_primary_target(targets)
         if primary is None:
             continue
+        # Flag the primary so qualification's EV uses the primary target's
+        # probability (matching production's enhance_trade_setup).
+        for t in targets:
+            t["is_primary"] = t is primary
         per_dir[direction] = {"stop": stop, "targets": targets, "primary": primary}
 
     available = set(per_dir.keys())
@@ -160,12 +168,13 @@ def _window_setups(
             stop_loss=stop,
             entry_price=entry,
         )
-        # meets_core = clears every gate EXCEPT target probability, so the report
+        # meets_core = clears every gate EXCEPT the expected-value floor, so the
-        # can sweep the min_target_probability threshold without re-replaying.
+        # report can sweep the min_expected_value threshold without re-replaying.
-        core_config = {**activation, "min_target_probability": 0.0}
+        core_config = {**activation, "min_expected_value": float("-inf")}
         meets_core = setup_qualifies(setup_ns, core_config)
+        ev = expected_value_r(setup_ns)
         best_prob = best_target_probability(setup_ns)
-        min_tp = float(activation.get("min_target_probability", 0.0))
+        min_ev = float(activation.get("min_expected_value", 0.0))
         out.append({
             "direction": direction,
             "entry": entry,
@@ -175,10 +184,11 @@ def _window_setups(
             "confidence": confidences[direction],
             "primary_prob": float(primary["probability"]),
             "best_prob": best_prob,
+            "ev": ev,
             "meets_core": meets_core,
             "action": action,
             "risk_level": risk_level,
-            "qualified": meets_core and best_prob >= min_tp,
+            "qualified": meets_core and ev is not None and ev >= min_ev,
         })
     return out
 
@@ -216,6 +226,7 @@ def _replay_ticker(symbol: str, records: list, config: dict, activation: dict) -
                 "confidence": s["confidence"],
                 "primary_prob": s["primary_prob"],
                 "best_prob": s["best_prob"],
+                "ev": s["ev"],
                 "meets_core": s["meets_core"],
                 "qualified": s["qualified"],
                 "outcome": outcome,
@@ -288,14 +299,17 @@ async def run_backtest(
     longs = [c for c in qualified if c["direction"] == "long"]
     shorts = [c for c in qualified if c["direction"] == "short"]
 
-    # Threshold sweep: re-apply the gate at several min_target_probability values
+    # Threshold sweep: re-apply the gate at several min_expected_value values
     # (holding the other conditions fixed) so the trade-off between how many
     # setups qualify and their expectancy is visible without re-replaying.
-    current_min_tp = float(activation.get("min_target_probability", 60.0))
+    current_min_ev = float(activation.get("min_expected_value", 0.15))
     sweep = []
-    for threshold in (60, 55, 50, 45, 40, 35, 30):
+    for threshold in (0.4, 0.3, 0.25, 0.2, 0.15, 0.1, 0.05, 0.0):
-        cands = [c for c in candidates if c["meets_core"] and c["best_prob"] >= threshold]
+        cands = [
-        sweep.append({"min_target_probability": threshold, **_bucket_stats(cands)})
+            c for c in candidates
+            if c["meets_core"] and c["ev"] is not None and c["ev"] >= threshold
+        ]
+        sweep.append({"min_expected_value": threshold, **_bucket_stats(cands)})
 
     return {
         "generated_at": datetime.now(timezone.utc).isoformat(),
@@ -310,7 +324,7 @@ async def run_backtest(
             "long": _bucket_stats(longs),
             "short": _bucket_stats(shorts),
         },
-        "min_target_probability": current_min_tp,
+        "min_expected_value": current_min_ev,
         "sweep": sweep,
         "calibration": _calibration(candidates),
         "note": (

app/services/qualification.py

@@ -1,9 +1,11 @@
 """Shared definition of a 'qualified' (actionable) trade setup.
 
 A single predicate, driven by the admin activation config, used by the
-performance stats (server) and mirrored on the frontend. Beyond raw R:R and
+performance stats (server) and mirrored on the frontend. The core gate is
-confidence, an actionable setup must show genuine conviction: a high-conviction
+expected value (in R): a setup must promise positive, probability-weighted
-recommended action, a clean (conflict-free) read, and a probable primary target.
+asymmetry, not just a fat-but-improbable target or a likely-but-thin one. R:R
+and confidence remain as floors, and conviction/conflict/target-probability
+survive as optional tighteners (off by default).
 """
 
 from __future__ import annotations
@@ -20,6 +22,37 @@ def best_target_probability(setup: Any) -> float:
     return max(probs, default=0.0)
 
 
+def primary_target_probability(setup: Any) -> float | None:
+    """Probability of the starred primary target (the one the headline R:R refers
+    to). Falls back to the best target's probability when none is flagged primary,
+    and None when there are no targets at all (probability unknowable).
+    """
+    targets = getattr(setup, "targets", None) or []
+    primary = next(
+        (t for t in targets if isinstance(t, dict) and t.get("is_primary")), None
+    )
+    if primary is not None:
+        return float(primary.get("probability", 0.0))
+    probs = [float(t.get("probability", 0.0)) for t in targets if isinstance(t, dict)]
+    return max(probs) if probs else None
+
+
+def expected_value_r(setup: Any) -> float | None:
+    """Expected value per unit of risk, in R: ``p·(R:R) − (1 − p)``.
+
+    ``p`` is the primary target's hit probability. This single number captures
+    "is this worth taking": it rewards both a good payoff ratio and a likely
+    target, so a fat-but-improbable target can't outrank a solid, probable one —
+    and a high R:R no longer fights a high probability the way the old separate
+    gates did. Returns None when no target probability is known.
+    """
+    p = primary_target_probability(setup)
+    if p is None:
+        return None
+    p = p / 100.0
+    return p * setup.rr_ratio - (1.0 - p)
+
+
 def live_risk_reward(setup: Any, current_price: float) -> float | None:
     """R:R recomputed from the CURRENT price, not the (possibly stale) entry.
 
@@ -43,6 +76,11 @@ def setup_qualifies(setup: Any, config: dict) -> bool:
 
     ``setup`` is duck-typed: any object exposing rr_ratio, confidence_score,
     recommended_action, risk_level and a ``targets`` list of dicts.
+
+    Gate order: R:R floor → freshness (live R:R) → confidence floor → expected
+    value (the core test) → optional conviction / conflict / target-probability
+    tighteners. ``min_expected_value`` defaults to -inf for callers that pass a
+    legacy config without the key, so they behave exactly as before.
     """
     if setup.rr_ratio < config["min_rr"]:
         return False
@@ -56,6 +94,13 @@ def setup_qualifies(setup: Any, config: dict) -> bool:
             return False
     if (setup.confidence_score or 0.0) < config["min_confidence"]:
         return False
+    # Expected value (R): the core gate. Only enforced when computable — setups
+    # without target probabilities (e.g. legacy historical rows) defer to the
+    # R:R + confidence floors above rather than being silently dropped.
+    min_ev = float(config.get("min_expected_value", float("-inf")))
+    ev = expected_value_r(setup)
+    if ev is not None and ev < min_ev:
+        return False
     if config.get("require_high_conviction"):
         if (setup.recommended_action or "") not in HIGH_CONVICTION_ACTIONS:
             return False

frontend/src/api/admin.ts

@@ -6,6 +6,7 @@ import type {
   AlertTestResult,
   PipelineReadiness,
   RecommendationConfig,
+  ScheduleConfig,
   SentimentProviderConfig,
   SentimentTestResult,
   SystemSetting,
@@ -85,6 +86,18 @@ export function updateActivationSettings(payload: Partial<ActivationConfig>) {
     .then((r) => r.data);
 }
 
+export function getScheduleSettings() {
+  return apiClient
+    .get<ScheduleConfig>('admin/settings/schedule')
+    .then((r) => r.data);
+}
+
+export function updateScheduleSettings(payload: Partial<ScheduleConfig>) {
+  return apiClient
+    .put<ScheduleConfig>('admin/settings/schedule', payload)
+    .then((r) => r.data);
+}
+
 export function getSentimentSettings() {
   return apiClient
     .get<SentimentProviderConfig>('admin/settings/sentiment')

frontend/src/components/admin/ActivationSettings.tsx

@@ -4,11 +4,12 @@ import { useActivationSettings, useUpdateActivationSettings } from '../../hooks/
 import { SkeletonTable } from '../ui/Skeleton';
 
 const DEFAULTS: ActivationConfig = {
-  min_rr: 2,
+  min_expected_value: 0.15,
-  min_confidence: 70,
+  min_rr: 1.2,
-  min_target_probability: 60,
+  min_confidence: 55,
-  require_high_conviction: true,
+  min_target_probability: 0,
-  exclude_conflicts: true,
+  require_high_conviction: false,
+  exclude_conflicts: false,
 };
 
 export function ActivationSettings() {
@@ -39,13 +40,27 @@ export function ActivationSettings() {
         <h3 className="text-sm font-semibold text-gray-200">Activation Gate</h3>
         <p className="mt-1 text-xs text-gray-500">
           What counts as a signal worth acting on. Drives the Dashboard's "Qualified" metric, the
-          Signals "Qualified only" view, and the Track Record's qualified stats. All setups are
+          Signals "Qualified only" view, and the Track Record's qualified stats. The core test is
-          still evaluated regardless — tighten the gate, then watch qualified expectancy in the
+          <span className="text-gray-300"> expected value</span> — probability-weighted asymmetry —
-          Track Record to find what actually wins.
+          so R:R and target probability no longer fight each other. All setups are still evaluated
+          regardless; tune the EV floor against the Track Record's EV sweep to see what actually wins.
         </p>
       </div>
 
       <div className="grid gap-4 md:grid-cols-3">
+        <label className="block space-y-1">
+          <span className="text-xs text-gray-400">Min Expected Value (R)</span>
+          <input
+            type="number"
+            min={-1}
+            max={10}
+            step={0.05}
+            value={form.min_expected_value}
+            onChange={(e) => setForm((prev) => ({ ...prev, min_expected_value: Number(e.target.value) }))}
+            className="w-full input-glass px-3 py-2 text-sm"
+          />
+          <span className="text-[11px] text-gray-600">p·R:R − (1−p), in R. 0.15 ≈ +0.15× risk/trade. The core gate.</span>
+        </label>
         <label className="block space-y-1">
           <span className="text-xs text-gray-400">Min Risk:Reward (1 : x)</span>
           <input
@@ -56,7 +71,7 @@ export function ActivationSettings() {
             onChange={(e) => setForm((prev) => ({ ...prev, min_rr: Number(e.target.value) }))}
             className="w-full input-glass px-3 py-2 text-sm"
           />
-          <span className="text-[11px] text-gray-600">Set above your scanner floor or it does nothing.</span>
+          <span className="text-[11px] text-gray-600">Floor only — keeps symmetric/negative trades out.</span>
         </label>
         <label className="block space-y-1">
           <span className="text-xs text-gray-400">Min Confidence (%)</span>
@@ -70,6 +85,12 @@ export function ActivationSettings() {
             className="w-full input-glass px-3 py-2 text-sm"
           />
         </label>
+      </div>
+
+      <div className="border-t border-white/[0.06] pt-4">
+        <p className="text-xs font-medium uppercase tracking-widest text-gray-500">Optional tighteners</p>
+        <p className="mt-1 text-[11px] text-gray-600">Off by default — turn on to be more selective on top of the EV gate.</p>
+        <div className="mt-3 grid gap-3 md:grid-cols-3">
           <label className="block space-y-1">
             <span className="text-xs text-gray-400">Min Target Probability (%)</span>
             <input
@@ -83,9 +104,6 @@ export function ActivationSettings() {
             />
             <span className="text-[11px] text-gray-600">Best target's probability must clear this. 0 disables.</span>
           </label>
-      </div>
-
-      <div className="grid gap-3 md:grid-cols-2">
           <label className="flex cursor-pointer items-start gap-2.5 text-sm text-gray-300">
             <input
               type="checkbox"
@@ -115,6 +133,7 @@ export function ActivationSettings() {
             </span>
           </label>
         </div>
+      </div>
 
       <div className="flex items-center gap-2">
         <button className="btn-primary px-4 py-2 text-sm" onClick={onSave} disabled={update.isPending}>

frontend/src/components/admin/JobControls.tsx

@@ -147,7 +147,7 @@ export function JobControls() {
                             : 'Inactive'}
                   </span>
                   {job.via_pipeline ? (
-                    <span className="text-[11px] text-gray-500">runs in daily pipeline</span>
+                    <span className="text-[11px] text-gray-500">runs via pipeline</span>
                   ) : (
                     job.enabled && job.next_run_at && (
                       <span className="text-[11px] text-gray-500">

frontend/src/components/admin/ScheduleSettings.tsx

@@ -0,0 +1,100 @@
+import { useEffect, useState } from 'react';
+import type { ScheduleConfig } from '../../lib/types';
+import { useScheduleSettings, useUpdateScheduleSettings } from '../../hooks/useAdmin';
+import { SkeletonTable } from '../ui/Skeleton';
+
+const DEFAULTS: ScheduleConfig = {
+  schedule_timezone: 'Europe/Berlin',
+  schedule_daily_pipeline_cron: '0 7 * * *',
+  schedule_intraday_pipeline_cron: '0 14-22 * * 1-5',
+  schedule_fundamentals_cron: '0 4 * * 1',
+};
+
+const FIELDS: { key: keyof ScheduleConfig; label: string; hint: string; mono?: boolean }[] = [
+  {
+    key: 'schedule_timezone',
+    label: 'Timezone',
+    hint: 'IANA name, e.g. Europe/Berlin. All times below are in this zone.',
+  },
+  {
+    key: 'schedule_daily_pipeline_cron',
+    label: 'Daily pipeline (full)',
+    hint: 'OHLCV → sentiment → R:R scan → outcomes → regime. Default 07:00 so data is ready by 8.',
+    mono: true,
+  },
+  {
+    key: 'schedule_intraday_pipeline_cron',
+    label: 'Intraday pipeline (light)',
+    hint: 'Refresh prices + resolve outcomes. Default hourly across the US session, weekdays.',
+    mono: true,
+  },
+  {
+    key: 'schedule_fundamentals_cron',
+    label: 'Fundamentals (weekly)',
+    hint: 'Slow, rate-limited. Default early Monday so it finishes well before the day starts.',
+    mono: true,
+  },
+];
+
+export function ScheduleSettings() {
+  const { data, isLoading, isError, error } = useScheduleSettings();
+  const update = useUpdateScheduleSettings();
+
+  const [form, setForm] = useState<ScheduleConfig>(DEFAULTS);
+
+  useEffect(() => {
+    if (data) setForm(data);
+  }, [data]);
+
+  if (isLoading) return <SkeletonTable rows={2} cols={2} />;
+  if (isError) return <p className="text-sm text-red-400">{(error as Error)?.message || 'Failed to load schedule'}</p>;
+
+  return (
+    <div className="glass p-5 space-y-4">
+      <div>
+        <h3 className="text-sm font-semibold text-gray-200">Pipeline Schedule</h3>
+        <p className="mt-1 text-xs text-gray-500">
+          When the jobs run, as 5-field cron (<span className="num">min hour day month weekday</span>).
+          Saved changes apply to the running scheduler immediately — no redeploy. The big nightly run
+          does the full refresh; the light intraday run just keeps prices current.
+        </p>
+      </div>
+
+      <div className="grid gap-4 md:grid-cols-2">
+        {FIELDS.map((f) => (
+          <label key={f.key} className="block space-y-1">
+            <span className="text-xs text-gray-400">{f.label}</span>
+            <input
+              type="text"
+              value={form[f.key]}
+              spellCheck={false}
+              onChange={(e) => setForm((prev) => ({ ...prev, [f.key]: e.target.value }))}
+              className={`w-full input-glass px-3 py-2 text-sm ${f.mono ? 'num' : ''}`}
+            />
+            <span className="block text-[11px] text-gray-600">{f.hint}</span>
+          </label>
+        ))}
+      </div>
+
+      <div className="flex items-center gap-2">
+        <button
+          className="btn-primary px-4 py-2 text-sm"
+          onClick={() => update.mutate(form)}
+          disabled={update.isPending}
+        >
+          {update.isPending ? 'Saving…' : 'Save Schedule'}
+        </button>
+        <button
+          className="px-4 py-2 text-sm rounded border border-white/[0.1] text-gray-300 hover:text-white"
+          onClick={() => {
+            setForm(DEFAULTS);
+            update.mutate(DEFAULTS);
+          }}
+          disabled={update.isPending}
+        >
+          Reset to Defaults
+        </button>
+      </div>
+    </div>
+  );
+}

frontend/src/components/signals/BacktestPanel.tsx

@@ -161,18 +161,19 @@ export function BacktestPanel() {
             {report.sweep && report.sweep.length > 0 && (
               <div>
                 <p className="mb-2 text-xs font-medium uppercase tracking-widest text-gray-500">
-                  Min target-probability sweep
+                  Min expected-value sweep
                 </p>
                 <p className="mb-2 text-[11px] text-gray-500">
-                  How many setups qualify — and how they perform — at each gate threshold (other
+                  How many setups qualify — and how they perform — at each expected-value gate (other
-                  gate conditions held fixed). Lower = more trades, watch that expectancy holds.
+                  gate conditions held fixed). EV is in R: 0.15 means +0.15× your risk per trade on
-                  Your current setting is highlighted; set it in Admin → Settings → Activation.
+                  average. Lower = more trades, watch that expectancy holds. Your current setting is
+                  highlighted; set it in Admin → Settings → Activation.
                 </p>
                 <div className="glass overflow-x-auto">
                   <table className="w-full text-sm">
                     <thead>
                       <tr className="border-b border-white/[0.06] text-left text-xs uppercase tracking-wider text-gray-500">
-                        <th className="px-4 py-2.5">Min Target Prob</th>
+                        <th className="px-4 py-2.5">Min EV (R)</th>
                         <th className="px-4 py-2.5 text-right">Qualified</th>
                         <th className="px-4 py-2.5 text-right">Wins</th>
                         <th className="px-4 py-2.5 text-right">Losses</th>
@@ -183,12 +184,12 @@ export function BacktestPanel() {
                     </thead>
                     <tbody>
                       {report.sweep.map((row) => {
-                        const current = Math.abs(row.min_target_probability - report.min_target_probability) < 0.5;
+                        const current = Math.abs(row.min_expected_value - report.min_expected_value) < 0.001;
                         return (
-                          <tr key={row.min_target_probability} className={`border-b border-white/[0.04] ${current ? 'bg-blue-400/10' : ''}`}>
+                          <tr key={row.min_expected_value} className={`border-b border-white/[0.04] ${current ? 'bg-blue-400/10' : ''}`}>
                             <td className="num px-4 py-2.5 text-gray-200">
                               {current && <span className="mr-1 text-blue-300">★</span>}
-                              {row.min_target_probability}%
+                              {row.min_expected_value.toFixed(2)}
                             </td>
                             <td className="num px-4 py-2.5 text-right text-gray-200">{row.total}</td>
                             <td className="num px-4 py-2.5 text-right text-emerald-400">{row.wins}</td>

frontend/src/hooks/useAdmin.ts

@@ -140,6 +140,31 @@ export function useUpdateActivationSettings() {
   });
 }
 
+export function useScheduleSettings() {
+  return useQuery({
+    queryKey: ['admin', 'schedule-settings'],
+    queryFn: () => adminApi.getScheduleSettings(),
+  });
+}
+
+export function useUpdateScheduleSettings() {
+  const qc = useQueryClient();
+  const { addToast } = useToast();
+
+  return useMutation({
+    mutationFn: (payload: Partial<import('../lib/types').ScheduleConfig>) =>
+      adminApi.updateScheduleSettings(payload),
+    onSuccess: () => {
+      qc.invalidateQueries({ queryKey: ['admin', 'schedule-settings'] });
+      qc.invalidateQueries({ queryKey: ['admin', 'jobs'] });
+      addToast('success', 'Schedule updated');
+    },
+    onError: (error: Error) => {
+      addToast('error', error.message || 'Failed to update schedule');
+    },
+  });
+}
+
 export function useSentimentSettings() {
   return useQuery({
     queryKey: ['admin', 'sentiment-settings'],

frontend/src/lib/qualification.ts

@@ -48,6 +48,10 @@ export function qualifiesSetup(setup: TradeSetup, config: ActivationConfig): boo
     return false;
   }
   if ((setup.confidence_score ?? 0) < config.min_confidence) return false;
+  // Expected value (R) is the core gate. Only enforced when computable — setups
+  // without target probabilities defer to the R:R + confidence floors above.
+  const ev = expectedValueR(setup);
+  if (ev != null && ev < config.min_expected_value) return false;
   if (config.require_high_conviction && !HIGH_CONVICTION_ACTIONS.has(setup.recommended_action ?? '')) {
     return false;
   }
@@ -60,7 +64,7 @@ export function qualifiesSetup(setup: TradeSetup, config: ActivationConfig): boo
 
 /** Short human summary of the active gate, e.g. for tooltips/labels. */
 export function activationSummary(config: ActivationConfig): string {
-  const parts = [`R:R ≥ ${config.min_rr.toFixed(1)}`, `conf ≥ ${config.min_confidence.toFixed(0)}%`];
+  const parts = [`EV ≥ ${config.min_expected_value.toFixed(2)}R`, `R:R ≥ ${config.min_rr.toFixed(1)}`, `conf ≥ ${config.min_confidence.toFixed(0)}%`];
   if (config.require_high_conviction) parts.push('high-conviction');
   if (config.exclude_conflicts) parts.push('clean');
   if (config.min_target_probability > 0) parts.push(`target ≥ ${config.min_target_probability.toFixed(0)}%`);

frontend/src/lib/types.ts

@@ -158,6 +158,7 @@ export interface PerformanceStats {
 
 // Activation gate: what counts as an actionable signal
 export interface ActivationConfig {
+  min_expected_value: number;
   min_rr: number;
   min_confidence: number;
   min_target_probability: number;
@@ -165,6 +166,14 @@ export interface ActivationConfig {
   exclude_conflicts: boolean;
 }
 
+// Cron schedule for the daily/intraday pipelines + fundamentals
+export interface ScheduleConfig {
+  schedule_timezone: string;
+  schedule_daily_pipeline_cron: string;
+  schedule_intraday_pipeline_cron: string;
+  schedule_fundamentals_cron: string;
+}
+
 // Runtime sentiment LLM configuration
 export interface SentimentProviderConfig {
   provider: string;
@@ -212,7 +221,7 @@ export interface BacktestCalibrationRow {
 }
 
 export interface BacktestSweepRow extends BacktestBucket {
-  min_target_probability: number;
+  min_expected_value: number;
 }
 
 export interface BacktestReport {
@@ -224,7 +233,7 @@ export interface BacktestReport {
   overall_qualified: BacktestBucket;
   overall_all: BacktestBucket;
   by_direction: Record<string, BacktestBucket>;
-  min_target_probability: number;
+  min_expected_value: number;
   sweep: BacktestSweepRow[];
   calibration: BacktestCalibrationRow[];
   note: string;

frontend/src/pages/AdminPage.tsx

@@ -6,6 +6,7 @@ import { DataCleanup } from '../components/admin/DataCleanup';
 import { JobControls } from '../components/admin/JobControls';
 import { PipelineReadinessPanel } from '../components/admin/PipelineReadinessPanel';
 import { RecommendationSettings } from '../components/admin/RecommendationSettings';
+import { ScheduleSettings } from '../components/admin/ScheduleSettings';
 import { SettingsForm } from '../components/admin/SettingsForm';
 import { TickerManagement } from '../components/admin/TickerManagement';
 import { TickerUniverseBootstrap } from '../components/admin/TickerUniverseBootstrap';
@@ -41,6 +42,7 @@ export default function AdminPage() {
         )}
         {activeTab === 'Jobs' && (
           <div className="space-y-4">
+            <ScheduleSettings />
             <JobControls />
             <PipelineReadinessPanel />
           </div>

tests/unit/test_activation_settings.py

@@ -25,30 +25,35 @@ class TestActivationConfig:
     async def test_defaults_when_unset(self, session: AsyncSession):
         config = await get_activation_config(session)
         assert config == {
-            "min_rr": 2.0,
+            "min_expected_value": 0.15,
-            "min_confidence": 70.0,
+            "min_rr": 1.2,
-            "min_target_probability": 60.0,
+            "min_confidence": 55.0,
-            "require_high_conviction": True,
+            "min_target_probability": 0.0,
-            "exclude_conflicts": True,
+            "require_high_conviction": False,
+            "exclude_conflicts": False,
         }
 
     async def test_update_and_read_back(self, session: AsyncSession):
         updated = await update_activation_config(
-            session, {"min_rr": 1.5, "min_confidence": 60.0}
+            session, {"min_expected_value": 0.25, "min_confidence": 60.0}
         )
-        assert updated["min_rr"] == 1.5
+        assert updated["min_expected_value"] == 0.25
         assert updated["min_confidence"] == 60.0
 
         config = await get_activation_config(session)
-        assert config["min_rr"] == 1.5
+        assert config["min_expected_value"] == 0.25
         assert config["min_confidence"] == 60.0
 
     async def test_partial_update_keeps_other_value(self, session: AsyncSession):
         await update_activation_config(session, {"min_confidence": 80.0})
         config = await get_activation_config(session)
-        assert config["min_rr"] == 2.0  # default untouched
+        assert config["min_rr"] == 1.2  # default untouched
         assert config["min_confidence"] == 80.0
 
+    async def test_rejects_out_of_range_expected_value(self, session: AsyncSession):
+        with pytest.raises(ValidationError):
+            await update_activation_config(session, {"min_expected_value": 50.0})
+
     async def test_conviction_flags_round_trip(self, session: AsyncSession):
         await update_activation_config(
             session,

tests/unit/test_backtest_service.py

@@ -113,8 +113,8 @@ async def test_run_backtest_smoke(session):
     # the oscillating series should yield at least some resolved setups
     assert report["candidates"] >= 1
 
-    # sweep: lowering the threshold can only add qualifiers, never remove them
+    # sweep: lowering the EV threshold can only add qualifiers, never remove them
-    sweep = sorted(report["sweep"], key=lambda r: r["min_target_probability"], reverse=True)
+    sweep = sorted(report["sweep"], key=lambda r: r["min_expected_value"], reverse=True)
     counts = [r["total"] for r in sweep]
     assert counts == sorted(counts)  # ascending as threshold descends
     # every calibration row is internally consistent

tests/unit/test_qualification.py

@@ -1,12 +1,30 @@
-"""Unit tests for the activation qualification predicate."""
+"""Unit tests for the activation qualification predicate (EV-based gate)."""
 
 from __future__ import annotations
 
 from types import SimpleNamespace
 
-from app.services.qualification import best_target_probability, setup_qualifies
+from app.services.qualification import (
+    best_target_probability,
+    expected_value_r,
+    primary_target_probability,
+    setup_qualifies,
+)
 
-FULL_GATE = {
+# Default gate: expected value is the core test; conviction/conflict/target-prob
+# are optional tighteners, off here.
+DEFAULT_GATE = {
+    "min_expected_value": 0.15,
+    "min_rr": 1.2,
+    "min_confidence": 55.0,
+    "min_target_probability": 0.0,
+    "require_high_conviction": False,
+    "exclude_conflicts": False,
+}
+
+# Strict gate: every optional tightener turned on (the old shipped defaults).
+STRICT_GATE = {
+    "min_expected_value": 0.0,
     "min_rr": 2.0,
     "min_confidence": 70.0,
     "min_target_probability": 60.0,
@@ -21,73 +39,101 @@ def _setup(**kwargs):
         confidence_score=80.0,
         recommended_action="LONG_HIGH",
         risk_level="Low",
-        targets=[{"probability": 65.0}],
+        targets=[{"probability": 50.0, "is_primary": True}],
     )
     base.update(kwargs)
     return SimpleNamespace(**base)
 
 
-class TestSetupQualifies:
+class TestExpectedValue:
-    def test_clean_high_conviction_setup_passes(self):
+    def test_uses_primary_target_not_best(self):
-        assert setup_qualifies(_setup(), FULL_GATE) is True
+        s = _setup(
+            rr_ratio=1.5,
+            targets=[
+                {"probability": 80.0},
+                {"probability": 30.0, "is_primary": True},
+            ],
+        )
+        # EV from the primary (30%): 0.3*1.5 - 0.7 = -0.25
+        assert expected_value_r(s) == -0.25
+        assert primary_target_probability(s) == 30.0
 
-    def test_low_rr_fails(self):
+    def test_falls_back_to_best_when_no_primary_flag(self):
-        assert setup_qualifies(_setup(rr_ratio=1.5), FULL_GATE) is False
+        s = _setup(rr_ratio=2.0, targets=[{"probability": 40.0}, {"probability": 60.0}])
+        assert primary_target_probability(s) == 60.0
+        # 0.6*2.0 - 0.4 = 0.8
+        assert abs(expected_value_r(s) - 0.8) < 1e-9
+
+    def test_none_when_no_targets(self):
+        assert expected_value_r(_setup(targets=[])) is None
+        assert primary_target_probability(_setup(targets=[])) is None
+
+
+class TestSetupQualifies:
+    def test_positive_ev_setup_passes(self):
+        # primary 50% @ rr 3.0 → EV = 1.0
+        assert setup_qualifies(_setup(), DEFAULT_GATE) is True
+
+    def test_negative_ev_fails(self):
+        # primary 30% @ rr 1.3 → EV = -0.31, below the 0.15 floor
+        s = _setup(rr_ratio=1.3, targets=[{"probability": 30.0, "is_primary": True}])
+        assert setup_qualifies(s, DEFAULT_GATE) is False
+
+    def test_thin_positive_ev_below_floor_fails(self):
+        # Positive but thin: 0.45*1.3 - 0.55 = 0.035, under the 0.15 floor.
+        s = _setup(rr_ratio=1.3, targets=[{"probability": 45.0, "is_primary": True}])
+        assert setup_qualifies(s, DEFAULT_GATE) is False
+
+    def test_low_rr_floor_fails(self):
+        assert setup_qualifies(_setup(rr_ratio=1.0), DEFAULT_GATE) is False
 
     def test_low_confidence_fails(self):
-        assert setup_qualifies(_setup(confidence_score=60.0), FULL_GATE) is False
+        assert setup_qualifies(_setup(confidence_score=40.0), DEFAULT_GATE) is False
 
-    def test_moderate_action_fails_when_high_conviction_required(self):
+    def test_no_targets_defers_to_rr_and_confidence(self):
-        assert setup_qualifies(_setup(recommended_action="LONG_MODERATE"), FULL_GATE) is False
+        # No probability → EV uncomputable → not blocked on EV; passes on floors.
+        assert setup_qualifies(_setup(targets=[]), DEFAULT_GATE) is True
+        # ...but still subject to the rr/confidence floors.
+        assert setup_qualifies(_setup(targets=[], rr_ratio=1.0), DEFAULT_GATE) is False
 
-    def test_neutral_action_fails(self):
+    def test_conviction_and_conflict_ignored_by_default(self):
-        assert setup_qualifies(_setup(recommended_action="NEUTRAL"), FULL_GATE) is False
+        # Moderate action + medium risk still pass when tighteners are off.
-
+        s = _setup(recommended_action="LONG_MODERATE", risk_level="Medium")
-    def test_short_high_passes(self):
+        assert setup_qualifies(s, DEFAULT_GATE) is True
-        assert setup_qualifies(_setup(recommended_action="SHORT_HIGH"), FULL_GATE) is True
-
-    def test_non_low_risk_fails_when_excluding_conflicts(self):
-        assert setup_qualifies(_setup(risk_level="Medium"), FULL_GATE) is False
-        assert setup_qualifies(_setup(risk_level="High"), FULL_GATE) is False
-
-    def test_low_target_probability_fails(self):
-        assert setup_qualifies(_setup(targets=[{"probability": 40.0}]), FULL_GATE) is False
-
-    def test_no_targets_fails_when_probability_required(self):
-        assert setup_qualifies(_setup(targets=[]), FULL_GATE) is False
 
     def test_over_progressed_setup_fails_on_live_rr(self):
-        # long target 120, stop 95; price already at 117 → live R:R ≈ 0.14
         s = _setup(direction="long", target=120.0, stop_loss=95.0, current_price=117.0)
-        assert setup_qualifies(s, FULL_GATE) is False
+        assert setup_qualifies(s, DEFAULT_GATE) is False
 
     def test_fresh_setup_passes_live_rr(self):
-        # price near entry (100): live R:R ≈ 3.2, well above min
         s = _setup(direction="long", target=120.0, stop_loss=95.0, current_price=101.0)
-        assert setup_qualifies(s, FULL_GATE) is True
+        assert setup_qualifies(s, DEFAULT_GATE) is True
 
     def test_past_stop_fails_live_rr(self):
         s = _setup(direction="long", target=120.0, stop_loss=95.0, current_price=94.0)
-        assert setup_qualifies(s, FULL_GATE) is False
+        assert setup_qualifies(s, DEFAULT_GATE) is False
 
-    def test_no_current_price_skips_live_check(self):
+    def test_missing_min_ev_key_skips_ev(self):
-        # Historical setups have no current_price → live check skipped
+        # Legacy callers without min_expected_value: EV defaults to -inf (no floor).
-        assert setup_qualifies(_setup(), FULL_GATE) is True
+        legacy = {k: v for k, v in DEFAULT_GATE.items() if k != "min_expected_value"}
+        s = _setup(rr_ratio=1.3, targets=[{"probability": 30.0, "is_primary": True}])
+        assert setup_qualifies(s, legacy) is True
 
-    def test_conviction_filters_can_be_disabled(self):
-        relaxed = {
-            "min_rr": 2.0,
-            "min_confidence": 70.0,
-            "min_target_probability": 0.0,
-            "require_high_conviction": False,
-            "exclude_conflicts": False,
-        }
-        # Moderate action, medium risk, no targets — still passes on rr+confidence alone
-        s = _setup(recommended_action="LONG_MODERATE", risk_level="Medium", targets=[])
-        assert setup_qualifies(s, relaxed) is True
 
-    def test_missing_confidence_treated_as_zero(self):
+class TestStrictTighteners:
-        assert setup_qualifies(_setup(confidence_score=None), FULL_GATE) is False
+    def test_clean_high_conviction_passes(self):
+        assert setup_qualifies(_setup(targets=[{"probability": 65.0, "is_primary": True}]), STRICT_GATE) is True
+
+    def test_moderate_action_fails(self):
+        s = _setup(recommended_action="LONG_MODERATE", targets=[{"probability": 65.0, "is_primary": True}])
+        assert setup_qualifies(s, STRICT_GATE) is False
+
+    def test_non_low_risk_fails(self):
+        s = _setup(risk_level="Medium", targets=[{"probability": 65.0, "is_primary": True}])
+        assert setup_qualifies(s, STRICT_GATE) is False
+
+    def test_low_target_probability_fails(self):
+        assert setup_qualifies(_setup(targets=[{"probability": 40.0, "is_primary": True}]), STRICT_GATE) is False
 
 
 class TestBestTargetProbability:

tests/unit/test_schedule_config.py

@@ -0,0 +1,61 @@
+"""Unit tests for the cron pipeline schedule config."""
+
+from __future__ import annotations
+
+import pytest
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from app.exceptions import ValidationError
+from app.scheduler import SCHEDULE_DEFAULTS, validate_cron
+from app.services.admin_service import get_schedule_config, update_schedule_config
+
+
+@pytest.fixture
+async def session() -> AsyncSession:
+    from tests.conftest import _test_session_factory
+
+    async with _test_session_factory() as session:
+        yield session
+
+
+class TestValidateCron:
+    def test_accepts_valid(self):
+        validate_cron("0 7 * * *", "Europe/Berlin")
+        validate_cron("0 14-22 * * 1-5", "UTC")
+
+    def test_rejects_bad_cron(self):
+        with pytest.raises(Exception):
+            validate_cron("not a cron", "UTC")
+
+    def test_rejects_bad_timezone(self):
+        with pytest.raises(Exception):
+            validate_cron("0 7 * * *", "Mars/Phobos")
+
+
+class TestScheduleConfig:
+    async def test_defaults_when_unset(self, session: AsyncSession):
+        config = await get_schedule_config(session)
+        assert config == SCHEDULE_DEFAULTS
+
+    async def test_update_and_read_back(self, session: AsyncSession):
+        updated = await update_schedule_config(
+            session, {"schedule_daily_pipeline_cron": "30 6 * * *"}
+        )
+        assert updated["schedule_daily_pipeline_cron"] == "30 6 * * *"
+        # untouched keys keep their defaults
+        assert updated["schedule_intraday_pipeline_cron"] == SCHEDULE_DEFAULTS["schedule_intraday_pipeline_cron"]
+
+        config = await get_schedule_config(session)
+        assert config["schedule_daily_pipeline_cron"] == "30 6 * * *"
+
+    async def test_rejects_bad_cron(self, session: AsyncSession):
+        with pytest.raises(ValidationError):
+            await update_schedule_config(session, {"schedule_fundamentals_cron": "every monday"})
+
+    async def test_rejects_bad_timezone(self, session: AsyncSession):
+        with pytest.raises(ValidationError):
+            await update_schedule_config(session, {"schedule_timezone": "Nowhere/Void"})
+
+    async def test_rejects_unknown_key(self, session: AsyncSession):
+        with pytest.raises(ValidationError):
+            await update_schedule_config(session, {"schedule_bogus": "0 0 * * *"})

tests/unit/test_scheduler.py

@@ -88,6 +88,7 @@ class TestConfigureScheduler:
             "market_regime",
             "backtest",
             "daily_pipeline",
+            "intraday_pipeline",
         }
 
     def test_configure_is_idempotent(self):
@@ -100,6 +101,7 @@ class TestConfigureScheduler:
             "alerts",
             "backtest",
             "daily_pipeline",
+            "intraday_pipeline",
             "data_collector",
             "fundamental_collector",
             "market_regime",