Plots the index, early-warning, and combined scores over time beneath the live
gauges, with a 1M/3M/6M/All range toggle and band reference lines — so the trend
and any divergence between the scores is visible, not just today's snapshot.
- Backend: GET /regime/history + get_regime_history (the three scores per
snapshot date from regime_snapshots).
- Frontend: recharts line chart, lazy-loaded so recharts ships in its own
regime-tab chunk instead of nearly doubling the main bundle.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The "warned a median -18 days later" line was the median-over-1-event trap: the
coincident baseline's 60d median is a single lucky event, while breadth warned on
7. Replace it with the honest coverage framing (7/11 vs 1/11) and flag that the
median-lead comparison is unreliable when coverage differs this much.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The early-warning score showed n/a because it required an exact date match
between the live benchmark (Alpaca, may have today's bar) and the stored
universe breadth (DB, often a day behind), which blanked the newest snapshot —
the one the UI displays.
- Look up the divergence as-of the snapshot date (newest value within a 7-day
lag) instead of requiring an exact match.
- Backfill early_warning + combined onto recent existing snapshots (the index
history predates this signal) so the 7/30-day trends populate on the first run
rather than only filling in over the coming weeks.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The event study showed the breadth-divergence signal genuinely leads (warned
before 7/11 drawdowns, ~6 weeks median, where the coincident baseline almost
never did). Surface it live to observe before deciding how to embed it — kept
separate from the index, not folded into its weights.
- regime_monitor daily job now computes breadth-divergence live and attaches a
separate early_warning score plus a combined blend (weighted mean, default
0.6/0.4, configurable via combined_weights) to each snapshot, including the
backfill so the 7/30-day trends populate immediately. Stored in breakdown_json
— no schema change. Best-effort: a breadth failure can't break the index.
- get_regime_monitor returns the index, early_warning, and combined scores each
with 7/30-day deltas.
- Regime tab shows three gauges (generalized ScoreGauge): coincident index,
early warning, and a compact combined blend. Stale snapshots render "—".
Note: the daily regime job now also does a universe-wide breadth scan.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The first run gave only 2 events (N=2 is anecdote, not evidence) and an unfairly
weak coincident baseline, so the +42d lead couldn't be trusted. This makes the
measurement meaningful:
- More, cleaner events: default drawdown threshold 15%→10%, and dedup switched
from "recover to the high" to a rising-edge + cooldown (40d), so distinct
drawdowns each register instead of merging.
- Fair comparison: each indicator now warns at its OWN 80th percentile instead of
a shared absolute 60, removing the artifact that muted the coincident baseline.
- Per-event breakdown (date · depth · breadth lead · coincident lead) so a median
over a tiny sample can't hide an apples-to-oranges comparison — you see whether
both warned on the same drawdown.
- Surface precision/recall (best row) + base rate per indicator — the honest edge
read, not just lead time.
Re-run the Event Study job to regenerate the cached report in the new shape.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The overview's Hit Rate and Expectancy were static lifetime aggregates — they
barely move day to day and aren't actionable at a glance. Replace them with the
current state from open paper trades:
- Open Risk: total $ at risk to stops across open positions.
- Unrealized: summed unrealized R (mark-to-market), with $ P&L and win/loss count.
Computed in the frontend from the already-loaded open trades (tradePnl) — no
backend change. The detailed lifetime stats remain on Signals → Track Record.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Adds a leading-by-construction candidate and the harness to measure whether it
actually leads regime breaks, before any of it earns weight in the live index.
- breadth_service: % of the stored universe above its own 200-DMA + a divergence
score (benchmark price up while breadth falls, nudged by low breadth). Genuinely
leading because it keys on divergence, not level. Not wired into the live score.
- event_study_service: detect drawdown events on the benchmark, then measure each
indicator's median lead time (event-centered) and precision/recall vs. the base
rate (signal-centered). Compares breadth-divergence against the deterministic
coincident price composite (reuses the regime price sub-scores). Price/breadth
only — reproducible, no LLM/FRED.
- Manual "Event Study" job (Admin → Jobs), GET /regime/event-study, and an
inline early-warning panel on the Regime tab with an honest small-sample caveat.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
A new /regime tab scoring how far the AI/Tech bull regime has deteriorated
toward a re-rating as a single 0-100 index with per-signal breakdown and a
7/30-day trend. Intentionally decoupled: nothing reads its output to gate or
score trades — the daily-pipeline membership is scheduling only.
- regime_monitor_service: price sub-scores (P1-P6 via Alpaca, like
market_regime), VIX + HY credit spreads via a small FRED helper, weighted
aggregation over available signals (missing source -> n/a, dropped from the
denominator), one snapshot row/day, and a ~90-day history backfill by
replaying the already-fetched series as-of each past day.
- F1/F3 fundamentals proposed by the configured grounded LLM (reuses
sentiment_provider_service config resolution), with a manual override + lock.
- regime_snapshots table (migration 011); endpoints on the existing market
router; admin-editable weights/threshold; standalone /regime page.
Data needs: prices via Alpaca, VIX/credit via FRED (optional key — signals show
n/a without it). No LLM needed for history.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Qualified setups could carry no sentiment because the sentiment job scoped
its relevant-set to watchlist + open trades + top-N composite score, while
the activation gate qualifies on 12-1 momentum percentile — a different axis.
A top-momentum ticker outside the composite top-N never got sentiment, so the
R:R scan enhanced it as neutral.
Add the gate's momentum leaders (percentile >= activation min_momentum_percentile)
to the sentiment relevant-set so scope tracks the gate. Best-effort: a momentum
or config failure falls back to the base set rather than aborting collection.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Behavior-preserving cleanup (345 tests pass, ruff clean):
- scheduler: replace 62 inline logger.x(json.dumps({...})) calls with a
_log_event helper, and collapse 11 identical _job_runtime dicts into an
_idle_runtime() factory over _JOB_NAMES.
- settings: add app/services/settings_store.py (get_setting/get_value/get_map/
upsert_setting) and route ~13 hand-rolled SystemSetting queries + two
identical _settings_map helpers through it.
- scoring.get_rankings: collapse the per-ticker N+1 (3-4 queries + a commit each)
into 2 bulk reads + a single conditional commit; drop the redundant re-fetch.
Lazy recompute-on-read is preserved. Adds first tests for get_rankings.
Net ~ -245 lines across the touched modules.
min_target_probability is gone: it filtered on the probability model the
calibration has repeatedly shown to be weak and overconfident, it was redundant
with the momentum gate, and as an off-by-default knob it just invited bad tuning.
Removed from the backend gate, activation config/schema, the frontend mirror
(qualifiesSetup / activationSummary), and ActivationSettings. The probability
model stays where it does real work (primary-target selection + display).
Charts: with multi-year history the all-bars default was unreadable. Added
time-range presets (1M / 3M / 6M / YTD / 1Y / 3Y / 5Y / All), defaulting to 1Y;
clicking a preset always re-applies (snaps back after a manual zoom). Y-axis
autoscale and wheel-zoom / drag-pan were already there.
339 backend tests pass; frontend build clean.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Part 1 — long-only. The momentum edge is long top-momentum; the gate was
qualifying shorts on high-momentum names (fighting the trend), which showed as
the -0.13R Short(qual.) drag. While the gate is active, shorts no longer qualify
(backend qualification, backtest _momentum_qualifies, and the frontend mirror).
Part 2 — production wiring. Live setups now carry a real momentum rank, so the
dashboard, the Track Record's qualified stats, and outcome evaluation all gate on
the same value instead of deferring to floors:
- new momentum_service.compute_momentum_percentiles: 12-1 momentum per ticker,
ranked across the universe into a {symbol: percentile} map.
- the daily R:R scan ranks the universe up front and stores each setup's
percentile (new trade_setups.momentum_percentile column, migration 010).
- enhance_trade_setup mutates the same row, so the percentile is preserved;
_trade_setup_to_dict + TradeSetupResponse expose it to the API.
Until a fresh scan runs, pre-existing setups have a null percentile and the gate
falls back to floors for them (longs) / excludes them (shorts) — they fill in on
the next scan. 341 backend tests pass; frontend build clean.
Needs the alembic upgrade (migration 010) on deploy.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The replay was CPU-bound and single-core: the earlier asyncio.to_thread offload
kept the API responsive but, because of the GIL, ran on one core. Per-ticker
replay is independent, so fan it out across worker processes (which sidestep the
GIL) for real multi-core speedup.
- New `settings.backtest_workers` (default 4), capped to cpu_count-1 so a core
stays free for the web server.
- Uses a `forkserver` context (workers forked from a clean single-threaded
server — avoids the fork-with-threads deadlock); falls back to `fork`. On
spawn-only platforms (Windows) and for 1-ticker runs it uses the thread path,
so dev/tests are unaffected.
- Worker takes primitive column arrays (cheap to pickle), rebuilds bars, and
returns (candidates, plain-dict signal series) — both picklable across the
process boundary. Bars are still fetched in the event loop (ORM-safe).
- Pool creation is guarded: if the pool can't start, the job falls back to the
sequential thread path instead of failing.
334 backend tests pass (parallel path is POSIX/server-only, so it's covered by
construction + the picklability/worker-count tests; the thread fallback is
exercised by the run_backtest smoke test).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The momentum-sweep table read row.min_momentum_percentile.toFixed(), but a report
cached before the EV->momentum change only has min_expected_value rows. undefined
.toFixed() threw during render and — with no error boundary — blanked the whole
Track Record tab. Guard the sweep block on the new field so a stale report just
hides the sweep; re-running the backtest repopulates it.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The 5-year backtest confirmed the EV gate adds negative value (high threshold =
worst expectancy) and that 12-1 month momentum is the one price signal with a
plausible, right-signed cross-sectional IC (~0.05). So "qualified" now means:
clears the R:R + confidence floors AND the ticker ranks in the top
`min_momentum_percentile` of the universe by 12-1 momentum that week.
- qualification.py: drop expected_value_r / the EV gate; add a momentum-percentile
gate (duck-typed `momentum_percentile`, only enforced when attached + threshold
set, else defers to floors). Mirrored in frontend qualification.ts.
- activation config/schema: min_expected_value -> min_momentum_percentile
(default 80 = top quintile). ActivationSettings, DashboardPage (ranks/【shows】
momentum instead of EV), and the BacktestPanel sweep follow.
- backtest: rank each ISO week's universe by 12-1 momentum, assign a percentile,
and qualify the top slice; the sweep now sweeps the percentile cutoff.
Also offload the backtest's per-ticker compute to a worker thread so the heavy
~5y run no longer blocks the API event loop (the "backend offline" flicker).
Production setups don't carry momentum_percentile yet — wiring the scanner to
attach it (a universe momentum-rank step) is the next step; until then the live
gate defers to floors while the backtest measures the momentum selection. 330
backend tests pass; frontend build clean.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Two changes so the cross-sectional signal results can actually be trusted.
(a) History depth — the binding constraint. Ingestion defaulted to 365 days, so
long-lookback factors (12-month momentum, 52-week high) were only computable on a
handful of weeks at the tail, and every IC reflected a single market regime.
- New `settings.ohlcv_history_days` (default 1825 ≈ 5y); new tickers backfill this
far instead of 1 year.
- New manual "data_backfill" job (Admin → Jobs) re-fetches the full window for
every ticker, ignoring incremental resume — run once to deepen existing
1-year histories. Idempotent (upsert); resumes after rate limits.
(b) Factor-IC honesty. The IC was averaged over weekly rebalances whose 30-day
forward windows overlap, inflating the t-stat ~sqrt(6)x.
- IC now measured on NON-OVERLAPPING windows (weeks thinned to ~HORIZON apart).
- Each signal carries a `reliable` flag (>= 12 independent windows); BacktestPanel
greys out and de-stars thin signals so a lucky 9-week IC of 0.3 can't masquerade
as an edge.
332 backend tests pass; frontend build clean. No migration (config + job + an
added JSON field on the cached backtest report).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The per-setup hit-rate report can't tell whether a signal predicts returns —
only how a target/stop structure built on one performs. This adds a
cross-sectional factor-IC pass: each week the universe is ranked by a price-only
signal and graded by its rank correlation (Spearman IC) and top-minus-bottom-
quintile spread against the forward 30-day return.
Candidate signals (point-in-time from price; sentiment/fundamentals have no
history in the replay): 12-1/6-1/3-1 month momentum, 1-month reversal,
price-vs-200d SMA, proximity to the 52-week high (George/Hwang), and 126-day
realized volatility (low-vol anomaly).
Reuses the existing per-ticker replay loop (no new data, no second DB pass);
results land in the cached backtest_report as `signal_eval` and render as a
"Signal edge" table in BacktestPanel beside the calibration curve.
330 backend tests pass (10 new in test_signal_eval); frontend build clean.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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>
The reset endpoint's schema expects new_password; the client sent password,
causing "body.new_password: Field required".
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Pulled the fundamental collector out of the daily pipeline (where it re-fetched
near-identical numbers every day and burned free-tier API quota) and made it an
independent weekly job. P/E/market-cap drift with price but the score buckets
them coarsely; revenue growth and earnings surprise only change at quarterly
earnings. Added "weekly" to the frequency map; fundamental_fetch_frequency now
defaults to weekly (configurable).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Jobs were independent 24h timers with no ordering, so the scanner could run on
stale OHLCV, and manual runs desynced the offsets. New daily_pipeline job runs
the data→signal flow in dependency order: OHLCV → fundamentals → sentiment →
R:R scan → outcome eval (+paper close) → market regime. Each step keeps its own
enable flag and runtime status; a failing step is logged and the pipeline
continues.
The member jobs are registered PAUSED (no auto-fire) so they only run via the
pipeline — but stay manually triggerable from Admin → Jobs (shown as "runs in
daily pipeline"). Alerts (hourly), ticker universe sync, and backtest keep their
own independent cadence.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
resolve_open_trades walks the daily bars after each open trade and closes it at
the target (target hit) or stop (stop/ambiguous), leaving undecided trades open.
Runs nightly inside the outcome evaluator (so it's coordinated with fresh OHLCV)
and on its manual trigger. New "My Trades" section at the top of Signals → Track
Record shows realized hit-rate, expectancy (avg R), total R, total P&L, and a
closed-trades table — your actual results, separate from the theoretical signal
record below it.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The 500+ row readiness table forced scrolling past it to reach the actual job
controls. Put JobControls first, readiness below.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Richer LLM output (same grounded call, ~no extra cost):
- All providers now also return a recommendation (buy/hold/avoid) and a thorough
reasoning paragraph; Gemini now actually captures reasoning + grounding
citations (it was dropping them). Stored on sentiment_scores (migration 008),
exposed in the API; display-only — NOT fed into the composite/EV.
- Ticker Sentiment panel shows an "LLM view" badge and a "Full analysis & sources"
expander with the complete reasoning + citations.
Search-budget scoping (Gemini grounding free tier = 5000/mo):
- collect_sentiment now targets only watchlist + open paper trades + top-N by
composite, skips tickers refreshed within sentiment_fresh_hours (72h), and caps
per run (sentiment_max_per_run). Once the relevant set is fresh, runs spend 0
searches until it ages out — bounding monthly usage well under the free tier.
- Widened sentiment lookback to 7d (scoring + display) so sparser collection
still feeds the dimension score.
Deploy: alembic upgrade (sentiment_scores.recommendation). Switch provider to
Gemini Flash in Admin for the cost win (grounded, cheapest).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
New paper_trades table (migration 007) + service/router. "Mark as taken" on each
setup card (shares prefilled from position sizing, entry from current price, both
editable) records a simulated trade. Overview gains an Open Trades table that
marks each position to the latest close — P&L in $, %, and R-multiples — with a
total unrealized P&L footer and a Sell button to close at the current price.
Closed trades are retained for future realized-P&L reporting.
Deploy: alembic upgrade (new paper_trades table).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Re-applies the activation gate at several min_target_probability thresholds
(60→30, other conditions fixed) over the already-replayed candidates, so the
trade-off between how many setups qualify and their expectancy is visible in one
table — the cheap "optimize" half of Phase 2. Candidates now carry meets_core +
best_prob so the sweep needs no re-replay. New sweep table in BacktestPanel with
the current threshold starred.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Backtest (32k setups) showed the touch-only probability model was ~2x
over-confident — predicted 70% hit 39%, predicted 88% hit 46% — because it
ignored the competing stop. estimate_probability now multiplies the reach
probability (touch within horizon) by the two-barrier gambler's-ruin ratio
1/(R:R+1) = P(target before stop). A 3:1 setup now reads ~25% base, not ~70%,
which lines up with realized rates. Strength/alignment modulation unchanged.
Recalibrates every probability and the EV ranking; the min_target_probability
gate threshold now means roughly what it says. Re-run the backtest to confirm
the calibration table flattens toward the diagonal.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
New BacktestPanel: shows qualified hit-rate/expectancy vs the all-setups baseline,
a by-direction breakdown, and the probability calibration table (predicted vs
realized, over-confident buckets flagged amber). Includes a "Run backtest" button
that triggers the job and a plain explanation of the method and its limits.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Replays the price-derived engine over stored OHLCV: at each weekly as-of date,
rebuild the setup from bars <= D (no lookahead) and walk the actual forward bars
for the realized outcome. Reports realized hit-rate/expectancy of qualified
setups (and all setups, by direction) plus a probability calibration curve
(predicted target prob vs realized hit rate).
Reuses pure functions throughout; extracted compute_technical_from_arrays /
compute_momentum_from_closes from scoring_service so live and backtest stay in
sync. Runs as a weekly/triggerable 'backtest' job caching the report in a
SystemSetting; GET /backtest/report serves it. Sentiment/fundamentals held
neutral (no point-in-time history) — calibrates the price/S-R/probability machinery.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The Jobs panel only surfaced live progress; once a job finished you couldn't see
when it ran, whether it succeeded, or its message (e.g. a regime/collector error).
Add a "Last run <ago> · <status> — <message>" line per job, colored by status,
from the runtime_* fields the backend already returns.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The spinner arrows clash with the dark glass UI. One base-layer CSS rule removes
them from every type=number input (admin settings, signals filters, data cleanup,
etc.) — values are typed, and type=number still gives the mobile numeric keypad
and validation.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The account/risk inputs are global "set once" settings, so they're moved out of
the panel body into a single compact line in the recommendation header. Replaced
the number-input spinners: risk % is now a segmented preset selector (0.5/1/2/3),
account size a clean text field with a $ prefix. Relabel "at risk" → "max loss".
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Finnhub's earnings calendar now supplies next_earnings_date through the
fundamentals chain; persisted on fundamental_data (migration 006) and exposed in
the fundamentals API. The recommendation panel warns when earnings fall within
the ~30-day target horizon (a report can gap price through stop/target) and
otherwise shows the next date. Informational only.
Deploy: run alembic upgrade (new fundamental_data.next_earnings_date column).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
New market_regime_service computes a benchmark (SPY) trend from its 50/200-day
SMAs, cached in a SystemSetting and refreshed by a nightly job; GET /market/regime
exposes it. Dashboard shows a regime banner; setup cards flag a counter-trend
caution when a setup fights the regime (LONG in a bearish market / SHORT in a
bullish one). Informational only — nothing is suppressed.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Risk-based sizing on each setup card: shares = floor((account × risk%) /
|entry − stop|), with position value and dollars-at-risk. Account size and
per-trade risk % are editable inline and persisted in localStorage. Flags when
a position would exceed the account (needs margin). Frontend-only.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Qualified tickers already get their own "qualified setup" alert, so an S/R
proximity ping on them is redundant noise. Drop the watchlist ∪ qualified scope
(remove now-unused _alert_scope_tickers) and alert only on watchlist tickers.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Trade-setup targets now pre-merge near-duplicate S/R levels into zone
representatives (same 2% clusterer as chart + alerts) before generate_targets
runs. A clustered wall (e.g. 183 + 185) becomes one target carrying the zone's
COMBINED strength (capped 100) instead of two near-identical targets that each
undervalue the wall — which also feeds a more honest reach-probability via the
S/R-strength magnet. Representative price is the zone's near edge; the strongest
constituent's id is retained. Singleton levels pass through unchanged, so the
downstream band-spreading / probability / primary-selection pipeline and its
tests are untouched.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Three fixes to over-firing S/R proximity alerts:
- Route through cluster_sr_zones (the same merger the chart uses) instead of raw
SRLevel rows, so near-duplicate levels (e.g. CVX 183 + 185) collapse into one
zone and one alert.
- Alert only the single NEAREST strong zone per ticker, not every nearby level.
- Scope to watchlist + qualified-setup tickers via _alert_scope_tickers (was
iterating all watchlist entries only; qualified setups are now included too).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Root cause of "price plan needed in bulk but fine on manual reload": on free
tiers FMP returns only market cap (others 402) and the chain merged that as a
partial success — so when the Finnhub/Alpha Vantage fallbacks were rate-limited
during a bulk run, the chain silently returned market-cap-only and the
collector's backoff never engaged. Manual single fetches worked because the
fallbacks weren't throttled at that moment.
Fixes:
- Chain distinguishes RateLimitError from other failures: if a fallback is
rate-limited and fields are still missing, raise RateLimitError (unless
allow_partial=True) so the collector backs off and retries.
- Bulk job paces requests (fundamental_request_spacing_seconds, default 3s) to
stay under Finnhub's ~60/min, and on retry-exhaustion stores partial data and
continues instead of aborting the whole run.
- Manual fetch passes allow_partial=True so a lone 429 doesn't fail the refresh.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Closes the action loop — instead of polling the dashboard, the platform pushes
actionable signals to Telegram. New hourly 'alerts' job dispatches four
toggleable triggers, deduped via a new alert_log table (cooldown-based for
qualified/S-R/digest, watermark-based for score deterioration). Admin → Settings
gains a Telegram panel (write-only bot token, chat ID, per-trigger toggles, Send
Test). Credentials follow DB > env precedence (TELEGRAM_BOT_TOKEN / _CHAT_ID).
Backend: alert_service + AlertLog model + migration 005, scheduler job, admin
endpoints/schema. Frontend: AlertSettings panel, hooks, api, types.
Deploy: run alembic upgrade (new alert_log table).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
AsyncIOScheduler was constructed with no job_defaults, so APScheduler's default
misfire_grace_time of 1s applied. In this single-process app the scheduler shares
one event loop with the API and all other jobs, so when a daily job came due
while the loop was busy (e.g. the scanner mid-run), the fire was processed >1s
late, flagged a misfire, and skipped — while next_run still advanced 24h, making
the job look healthy though it never ran. Set a generous grace window (1h),
coalesce missed runs into a single catch-up, and cap concurrency at 1.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
scan_rr set the total then called scan_all_tickers as one opaque await, so the
runtime snapshot's processed count stayed 0 until the whole scan finished and
jumped straight to 100%. scan_all_tickers now takes an optional progress_callback
invoked per ticker; the scheduler wires it to _runtime_progress so the sidebar's
live indicator advances as tickers are scanned.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Track Record: new "Reset" action (POST /admin/track-record/reset) deletes all
trade setups so stats start fresh after material scoring/setup changes — live
setups regenerate on the next scan. Guarded by a confirm dialog.
Recommendation config: remove distance_penalty_factor, which was exposed in the
admin UI but consumed nowhere (the touch-probability model superseded it). A
knob that silently does nothing is worse than no knob. Remaining defaults are
left as-is — they're reasonable, and the honest way to tune them is backtesting
against accumulated outcomes, not invented "researched" numbers.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Per design decision: the watchlist is now purely user-curated (no auto-seeding
of the top-10), so the auto_populate/dismissed machinery is removed and removals
are plain deletes. Each entry is enriched with latest close + day-over-day move.
Overview now shows two clear blocks: Top Setups (what to trade) and My Watchlist
(my names with current price and today's %). Market watchlist table drops the
now-meaningless auto/manual Type column in favour of Price and Day columns.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Removing a ticker did nothing because get_watchlist re-runs auto_populate on
every read, instantly re-adding any top-ranked ticker the user had just removed.
Removals are now tombstoned as a "dismissed" entry_type: auto-population skips
them, the list hides them, and a later manual add revives the row. Also exposes
an Add/Remove-watchlist toggle in the ticker detail header.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The dashboard Top Setups list showed raw fields in arbitrary order with no
indication of why a ticker was listed or which was best. Now sort by expected
value (R) — probability-weighted payoff per unit risk — so the strongest
opportunity is row 1, badged "Top pick", with a new Exp. Value column that
folds R:R and target probability into one "is this worth taking" number.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Answers "why does a too-far-progressed setup still show": setups are only
recalculated by the scheduled R:R scan and manual fetch; at creation
entry == current price (0% progress), so over-progression is a
between-scans drift effect and must be judged at read time.
- /trades now attaches current_price (latest close per ticker).
- Qualification drops setups whose R:R recomputed from the current price
falls below min_rr — i.e. price already ran toward target (reward
consumed) or through the stop. Reuses the existing min_rr threshold
instead of a separate progress %; far cleaner (a 3:1 is already ~1:1
by 33% progress). Skipped for historical setups (no current_price).
- Fix: useFetchSymbolData now invalidates the trades queries, so a fetch/
recompute actually refreshes confidence/setups in the UI (was the cause
of the stale 100% confidence lingering after recompute).
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
- Overview Top Setups shows the primary target's probability (concrete,
distance-calibrated) instead of the overlapping confidence number. The
stale 100% confidences were leftovers from the old model and self-heal
on rescan; confidence stays in the detail view + gate.
- Each metric now has one home: composite = ranking, target probability =
actionability, confidence = direction conviction.
- Staleness message states the real basis (% of entry->target distance
already covered), not the raw % from entry, so narrow setups read
correctly ("67% of the move is gone").
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Scores never updated ("101d ago"): get_score only recomputes stale/
missing dimensions, but nothing marked them stale on new data, and there
was no scheduled scoring job.
- Fetch endpoint force-recomputes dimensions + composite.
- Scheduled scan (scan_all_tickers) refreshes scores per ticker, so
scores stay current globally, not just on manual fetch.
Granular fetch: /ingestion/fetch accepts a sources filter; the freshness
bar gets a per-row refresh button (OHLCV/Sentiment/Fundamentals fetch
that provider only — marked paid; S/R/Scores recompute for free). Header
button is now "Fetch All".
Job visibility: GET /jobs/running (any user) + sidebar live indicator
showing running scheduled jobs with progress, polled every 10s.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
MKC showed 5 targets all far/Aggressive: target selection was top-5 by
quality (0.35*R:R + ...), and R:R grows with distance, so far levels
crowded out every nearby one.
generate_targets now selects for spread: always include the nearest
level, plus the best-quality representative from each distance band
(Conservative <=2.9 ATR, Moderate <=4.6 ATR, Aggressive beyond), then
fill remaining slots by quality. Restores a Conservative/Moderate/
Aggressive mix with the nearest target always present.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
dennisthiessen