Backtest report now includes research-only hold-to-horizon portfolio variants comparing raw vs residual 12-1 momentum, cutoff 80 vs 90, max 10 vs 15 positions, and SPY-200 risk scaling. A dynamic research recommendation panel flags residual momentum, cutoff 90, or regime scaling only when transparent promotion rules pass.
Adds signal_context_snapshots with migration 016 and captures one point-in-time context row per newly generated TradeSetup: setup fields, composite/dimensions, latest sentiment, latest fundamentals, and strategy_version=momentum_12_1_rr_time_v1. This is forward-only; no historical sentiment/fundamental backfill is attempted.
No live gate, paper-trade exit, or production ranking behavior changes.
Verification: 458 backend tests pass, ruff check app/ clean, frontend npm run build clean.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Adds a research-only 12-1 residual momentum signal to the cross-sectional signal-evaluation harness. The signal estimates benchmark beta over the 12-1 formation window and ranks cumulative stock return minus beta-adjusted benchmark return; it only appears when benchmark closes are available.
No production qualification behavior changes. The Backtest signal table labels the new row as 12-1 residual momentum. Tests cover benchmark-gated emission and beta removal while keeping stock-specific drift.
Verification: 453 backend tests pass, ruff check app/ clean, frontend npm run build clean.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Production strategy change based on the July 2026 backtest: paper trades now default to a 30-trading-day hold with the initial stop (classic momentum hold-and-rerank), while target and trailing exits remain available in Admin. The exit policy API/UI now carries hold_days and close_reason can be 'time'.
The activation confidence floor default is now 0/off because the gate ablation showed it added no per-trade edge while filtering out usable setups. Migration 015 clears stored activation_min_confidence and paper_exit_mode so the new defaults take effect; this intentionally resets Track Record comparability from this deploy.
Verification: 451 backend tests pass, ruff check app/ clean, frontend npm run build clean.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
The robustness warning was computed on the target-model distribution
while the same panel recommends the hold exit — internally inconsistent.
_robustness_stats (median, profit factor, ex-top-5% expectancy) is now
shared by _bucket_stats and _time_exit_bucket, the time-exit table shows
Median Net R and Ex-Top-5% per hold length, and _build_recommendation
reads the trimmed expectancy from the recommended exit's bucket (falling
back to the target model when no hold is recommended).
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Robustness (answers 'is the edge just outliers?'):
- _bucket_stats gains median_net_r, profit_factor, and net_avg_r_ex_top5
(expectancy with the top 5% of winners removed); shown as stat tiles.
- Portfolio sim gains per-calendar-year returns, shown in the sim table.
Dynamic recommendation ('What this backtest recommends' panel):
- _build_recommendation derives advice from the report's own numbers on
every run — exit policy (target vs best hold, with sim CAGRs), which
gate floors earn their keep (ablation Hold column), best momentum
cutoff, book-vs-SPY verdict, and an outlier-dependence warning when
the trimmed expectancy goes non-positive.
Retired (conclusions reached, tables removed from report + UI):
- Take-profit sweep (no interior optimum — fixed TP is the wrong tool
for momentum), trailing sweep (converged to the hold-to-horizon exit),
probability calibration (model is display-only by decision).
- _tp_primitives slimmed to _risk_and_stop_day; trailing machinery gone.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Per-trade additions to the report:
- Gap-through-stop fills: stops now fill at the worse of the stop or the
bar's open across every exit model (target, TP, trailing, time), so a
loss can exceed -1R; targets never fill better than their level.
- best_r / worst_r, avg holding days, and net R per day of capital
deployed on the summary buckets and the time-exit sweep.
Portfolio simulation (the stats a per-setup replay cannot give):
- One capital-constrained book over the qualified setups: 10k start, max
10 concurrent positions (one per ticker, best momentum first), 1%
fixed-fractional risk with a 20% no-leverage notional cap, entries at
the detection close, 0.1%/side costs, daily mark-to-market.
- Two exit policies compared: S/R target race vs hold-to-horizon.
- Equity-curve stats: final equity, total return, CAGR, max drawdown,
annualized daily Sharpe, win rate, avg P&L, best/worst trade, avg
hold, entries skipped on a full book, and SPY price return over the
same window (benchmark history refreshed to cover the replay span).
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
The ablation judged floors under the target/stop model, but the exit
sweeps point at replacing that exit with a fixed hold — under which the
R:R floor's rationale (bigger payoff at the target) may not apply. Each
ablation row now also carries hold_avg_r / hold_net_avg_r / hold_total_r
(30d hold, initial stop only), so the Phase 3 gate decision can be read
under the exit policy that would actually be used.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
_window_setups computed them but _replay_ticker dropped them, so the
ablation's NEUTRAL/tightener checks saw None for every candidate and the
'without confidence floor' / 'without R:R floor' rows collapsed to 0
setups (impossible — removing a floor can only add setups). Regression
test now goes through the real _replay_ticker path.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Phase 1 of the strategy-measurement plan — report-only, no production
trading behavior changes:
- Cost haircut: every bucket/sweep now reports net_avg_r/net_total_r
alongside gross (COST_PER_SIDE=0.1% of notional, converted to R via
each setup's stop distance); params carry cost_per_side_pct.
- Gate ablation table: re-qualifies candidates at the current momentum
cutoff with one floor removed per row (confidence / R:R / NEUTRAL /
momentum-only) to show which floors earn their keep.
- Time-based exit sweep: hold 5/10/21/30 days with the initial ATR stop,
exit at the day-N close — the classic momentum implementation, to
disambiguate the wide-trailing result.
- TP sweep extended to +40/+50%, trailing to 25/30% so the optima are
interior instead of starred at the sweep edge.
- BacktestPanel: Net Avg R columns everywhere, gate-ablation and
time-exit tables, stars now mark best net avg R; stale cached reports
still render (all new fields optional/guarded).
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Adds the validated-vs-not verdict table, the iron rule for strategy
changes, ranked next experiments, a maintainer guide (invariants, file
map, verification, roadmap), and corrects the deploy docs: deploys are
automated by Gitea Actions (push to main = deploy), service is
signalplatform.service at /opt/signalplatform.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Store an optional company name on Ticker (migration 014) and backfill it from
Alpaca's asset list in a single Trading-API call for the whole universe — no
per-ticker fetch. Runs automatically at the end of universe bootstrap and via a
manual "Backfill Names" button (admin) / POST /admin/tickers/backfill-names.
The name ships on /tickers; a shared symbol→name map (useTickerNames) lets any view
show it without its own request. Displayed subtly next to the symbol — in the global
search, the ticker header, and as a small muted line under the symbol in Top Setups
and Open Trades (no extra column, truncated so it never widens the table).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
get_score computed base_score / sentiment_score / sentiment_adjustment /
max_sentiment_adjustment, but the router's _map_composite_breakdown built the
response model from only the five original keys and silently dropped the rest — so
the API always returned null for them. That's why the ticker page showed neither the
"Composite = Base + Sentiment" caption nor the ± marker on the sentiment row despite
the frontend and scoring service both supporting it. Pass the fields through, with a
guard test so they can't be dropped again.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The ticker page renders the composite via the Standing matrix (ScoreCard runs with
showComposite=false), so the "Base X · sentiment +Y" line in the ScoreCard header
was never visible there. Add a compact caption beneath the matrix — "Composite 83 =
Base 78 + Sentiment 5.0" — shown only when sentiment actually moves the score, so
the composition of the number has a visible home where the number lives.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Sentiment is now a signed adjustment (± points on top of the base), not part of
the averaged dimensions — but the weights form still squeezed all five sliders to
sum to 100%, so dragging sentiment rebalanced the base and you couldn't set a clean
±N. Now the four base dimensions normalize among themselves (share shown as %),
and sentiment is its own "influence (± points)" control passed through raw
(slider 10 → weight 0.10 → ±10), independent of the base.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Going from no sentiment to a bullish read used to be able to *lower* the composite:
sentiment was blended into the weighted average as an absolute level, so a bullish
75 diluted a ticker already scoring 78. That's backwards for a directional signal.
Now the non-sentiment dimensions form a re-normalized weighted-average base, and
sentiment is applied as a signed adjustment around neutral (50):
composite = clamp(base + MAX_ADJ * (sentiment - 50) / 50)
MAX_ADJ = sentiment weight * 100 (default weight 0.10 → ±10)
Neutral leaves the base unchanged, bullish adds and bearish subtracts (scaled by
confidence, since a 50%-confidence call maps to 50 → no effect), and no sentiment
never penalises. Default sentiment weight 0.15 → 0.10; the weight now means "max ±
points." Composite breakdown exposes base_score/sentiment_score/sentiment_adjustment,
and the ScoreCard shows "Base 78 · sentiment +5.0" plus the per-dimension adjustment.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Applies the backtest-validated trailing stop to live paper trading, and surfaces
it transparently.
Exit (A):
- New paper-trade exit policy (paper_exit_mode=trailing, paper_trailing_pct=12),
tunable in Admin → Paper-Trade Exit. resolve_open_trades runs a trailing stop
(initial stop as floor, ratchets up from the peak; target ignored — the
validated rule) and records close_reason (trailing|stop|target|manual; +migration
013).
- list_trades enriches open trades with the live trailing-stop level + distance %.
Open Trades panel shows the active tactic and a Trail Stop column.
Alerts (B):
- Daily digest now lists open trades with unrealized gain, trailing stop, and how
far away it is.
- New "trade closed" alert: one summary per auto-close (trailing/target/stop, not
manual) — direction, reason, days held, P&L abs+%/R — covering wins AND
stop-loss losses. Deduped by trade id; toggle in Admin alerts.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Third exit model alongside target-vs-stop and the fixed take-profit. The TP sweep
showed the edge lives in the fat tail (avg R keeps rising as you let winners run),
but a fixed wide target is win-rate-brutal and gives everything back on a reversal.
A trailing stop harvests the tail while protecting gains.
Per setup the replay computes the realized R for several trail widths (3/5/7/10/
15/20%) in a single conservative pass — stop ratchets up via max(initial_stop,
peak*(1-trail)), exit on the pullback or at the horizon close, R vs the initial
risk. Aggregated into a trailing sweep (win rate = share closed in profit, avg R,
total R) over the qualified set and shown as a new table in the Backtest panel.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Avg R was still rising at the previous top level (+15%), so the optimum was off
the table. Extend TP_LEVELS to 20/25/30% to reveal where letting winners run
stops paying (it plateaus toward "just hold to the horizon close").
Also clarify in the panel that the take-profit model deliberately does NOT use
the setup's S/R target — it's a standalone fixed-% exit; exiting at the target is
the target-vs-stop model above. The two are complementary ends, not in conflict.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The target-vs-stop model counts a near-miss of a far S/R target as a full loss
and ignores the partial gains you actually bank — so it measures a different
strategy than "scalp the early pop, take +8%". Add a realistic take-profit exit
model next to it (original untouched).
Per setup the replay now also records risk%, whether the stop was hit, the
favourable excursion reachable before the stop (MFE), and the horizon-close move.
From those a fixed-take-profit sweep (4/6/8/10/12/15%) is scored in R: bank +X%
if reached before the stop, else -1R, else the horizon close. Hit rate = how
often +X% was banked (the MFE CDF), so you can pick the EV-optimal TP without
top-ticking fantasy. Shown as a new table in the Backtest panel; the IC,
calibration and momentum sweep are unchanged.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
A NEUTRAL ("No Clear Setup") recommendation means the engine found no clear
directional trade, yet such setups could still qualify and even be crowned the
top pick purely on momentum rank (e.g. an extended momentum leader with a far,
5%-probability target). A NEUTRAL signal isn't actionable, so it shouldn't
qualify.
New `exclude_neutral` activation flag (default on): setup_qualifies drops setups
whose recommended_action is NEUTRAL. It lives in the shared gate, so it flows
through the dashboard's qualified/top-pick selection, the track record's
qualified stats, and the backtest (which computes recommended_action and gates on
meets_core). Toggleable in Admin → Settings → Activation; the frontend mirror and
activationSummary ("directional") match.
Re-run the backtest after enabling to confirm it holds/improves expectancy.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Fetching a symbol the provider doesn't cover (e.g. RHM/Rheinmetall — Alpaca
serves US listings only) returned 0 bars but reported "complete · Successfully
ingested 0 records", which the UI showed as green success.
fetch_and_ingest now returns a distinct `no_data` status when the provider
returns nothing AND the ticker has no history (vs. "already up to date" when bars
exist). The fetch endpoint maps it to a `warning` source status, and the fetch
toast renders it as ⚠ with the provider message instead of success.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The outcome section measures the same thing as the backtest with the same code
and data — its only unique value is catching when the live system drifts from
the backtest (a bug, config/data drift, or look-ahead). So reframe it as exactly
that: a one-line "Live X R vs Backtest Y R · n matured · tracking ✓ / drift ⚠"
indicator (like-for-like with the qualified toggle), with the stat cards and
By-Action/By-Confidence tables moved into a collapsed "Outcome details"
disclosure. Drop the always-empty By-Direction table.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The outcome stats were dominated by quick stop-outs: near stops resolve as losses
within days while far targets take weeks, so a young sample (mostly pending,
0 expired) skewed sharply negative (e.g. 13.8% hit / -0.46R vs the backtest's
35.8% / +0.18R) — a maturation artifact, not a real result.
get_performance_stats now counts only setups whose full ~30-day window has
elapsed (_MATURITY_DAYS), so winners had as long as losers (unbiased, and
comparable to the backtest). A new `maturing` count reports the younger setups
held back. The Track Record UI relabels "Evaluated" -> "Matured", shows the
maturing count, and explains the window in the empty state + methodology note.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
- admin_service: register benchmark_collector in VALID_JOB_NAMES, JOB_LABELS and
PIPELINE_MEMBERS. The Admin → Jobs list is built from these hardcoded sets, not
the scheduler, so the job was registered but invisible/untriggerable.
- deploy.yml:
- SSH: verify the host key (StrictHostKeyChecking=yes) now that known_hosts is
supplied; move private-key cleanup to an `if: always()` step.
- Add a concurrency guard so deploys serialize.
- Health-check the service after restart (127.0.0.1:8998/api/v1/health).
- Align CI Python to 3.12 (matches prod); pip + npm caching.
- Clarify the Postgres service only validates migrations (tests use SQLite);
drop the redundant DATABASE_URL from the pytest step.
- Split the monolithic "Deploy to server" step into named steps.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
011 collided with the existing 011_add_regime_snapshots (duplicate revision id
and a second head branching off 010), which broke `alembic upgrade head`. Chain
the benchmark_prices migration after regime_snapshots so the history is linear
again (010 -> 011 regime_snapshots -> 012 benchmark_prices, single head).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Three usability fixes:
1. Global ticker search in the sidebar (TickerSearch) — typeahead over the
tracked universe that opens a ticker's detail page without adding it to the
watchlist. Also wired into the mobile nav.
2. Watchlist table shows the ticker's 12-1 momentum percentile (the top-pick
selector) instead of the noisy full S/R-level list. Enriched from the setup
already loaded in watchlist_service._enrich_entry — no extra query.
3. Alpha vs the S&P 500 on paper trades (open + closed). New benchmark_prices
table + benchmark_service store SPY daily closes (a standalone series, not a
Ticker, so it never enters the scanner / momentum ranking / rankings) via a
new daily-pipeline step. paper_trade_service computes per-trade
benchmark_return / alpha_pct / alpha_usd over each holding period; the open-
trades table, dashboard, and closed-trades panel surface per-trade and total
alpha. The list read path never makes a provider call.
Deploy: alembic upgrade head, then run the benchmark/daily job once to populate
SPY closes (alpha shows "—" until then).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Replace the scattered score readouts with one hero: a quality (composite) x
momentum-percentile scatter that plots this ticker against the whole field and
reads out a verdict by quadrant — Strong Buy / Momentum / Accumulate / Pass. The
dashed divider is the activation gate's momentum percentile, so "above the line =
qualifies" is visible at a glance; peers are clickable. Reuses the regime-quadrant
visual language and is lazy-loaded so recharts stays out of the main ticker chunk.
- New StandingMatrix component (composite x momentum, field cloud, verdict).
- ScoreCard gains showComposite (default true); the ticker page now renders it
without the composite ring (composite lives in the matrix) under "Dimensions".
- Confidence + target probability stay in the recommendation panel (the trade).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
- Add "How It Works": daily load (ordered pipeline steps), intraday flow,
other jobs, and the score -> activation gate -> top pick chain.
- Add "Key Use Cases" (find today's best long setup; track a paper trade).
- Fix stale facts: user-curated (not auto) watchlist, actual routes/pages,
scheduler description, wrong env defaults (RR 3.0->1.5, fundamentals
daily->weekly).
- Add missing surface: paper trading, activation gate, market regime, Telegram
alerts, backtest; API groups (paper-trades, market/regime, jobs); FRED +
Telegram env vars; note that pipeline timing is admin-cron, not env.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Two read-only pills in the ticker header, beside the watchlist toggle:
- "Top Pick" when the ticker is the current #1 — the same ranking the dashboard
highlights, via a shared topPickSymbol() helper so the two stay in sync.
- "Open Trade" when an open paper trade exists on the ticker.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Tiered, uncapped sentiment scope so the names that matter are never shown
without sentiment.
- Priority (always fully refreshed): top-pick feeders — momentum leaders with a
tradeable long setup over the R:R floor (the tickers that are, or could become
with positive sentiment, the dashboard top pick) — plus the curated watchlist
and open paper trades.
- Filler: top-N by composite, a discovery net, fetched after the priority set so
a mid-run rate limit lands the important names first.
- Removed the per-run cap (sentiment_max_per_run): the relevant set is naturally
bounded (watchlist <= 20, composite <= top_composite), so a full refresh stays
inside the free tier. extra="ignore" keeps a stale env var from breaking startup.
- Refresh window 72h -> 120h (5 days): sentiment shifts slowly, score window is 7d.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Fires once when the regime monitor shifts quadrant (regime index x early
warning), so you don't have to watch the tab. Two guards against spam:
- Hysteresis: each axis only flips once the value crosses its divider by a
margin, so a point parked on a boundary keeps its quadrant instead of
flip-flopping day to day.
- Cooldown: a genuine change stays quiet for a few days after the last alert.
Seeds the baseline silently on first run; reuses the existing Telegram dispatch
+ AlertLog. New per-trigger toggle in Admin → Alerts (on by default).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The single solid trail line read like a tangle. Make older→newer legible: the
path now fades from muted slate (older) to bright blue (newer) via per-point
colors, the connecting line is faint, and the points are de-noised with a
centered moving average (today kept exact). Easier to see the direction of travel
through the quadrants.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The combined score collapsed two distinct signals into one not-very-meaningful
number. Replace its gauge with a quadrant scatter that shows both axes directly:
x = regime index (coincident), y = early warning (breadth divergence), with a
trail of the last 60 sessions and today highlighted.
The four quadrants make the readings legible — ① hot & brittle (narrow melt-up,
shakeout risk), ② transition, ③ healthy & broad, ④ real downturn — and the trail
surfaces the actual tell: the ①→④ move (early warning rolling over as the regime
index climbs = divergence resolving downward). Combined still shows as a line in
the score-history chart. Frontend-only; reuses the history endpoint. Lazy-loaded.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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>
Fixes nonsensical "Conservative @ 90%" on far targets (AJG: +39% target
labelled Conservative/90%).
- Probability = chance of touching the level within the outcome horizon
under a driftless random walk: 2*(1 - Phi(d / (ATR*sqrt(T)))), T=30d to
match the outcome evaluator. Distance (in ATR) dominates; strength and
alignment modulate modestly. Far targets are now correctly low-prob.
- Classification derived from that probability (>=60 Conservative,
40-60 Moderate, <40 Aggressive) instead of distance-rank.
- Combined with the most-likely-worthwhile primary pick, the nearest
strong resistance becomes the Conservative primary; far levels demote
to low-probability stretch targets.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
- JWT now carries a username claim; sidebar shows "Signed in as <name>"
instead of the bare user id (sub). Re-login required for the new claim.
- Signals: Min R:R / Min Confidence inputs reflect the effective filter —
auto-filled from the activation gate when "Qualified only" is on, reset
to 0 when off (no more misleading 0 while the gate is active).
- Signals layout: Run Scanner moved to its own action row (it's a job
trigger, not a filter); qualified toggle grouped with the refinement
filters under one Filters panel.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Triggered by MRK: entry 113 shown with no current price (actually ~119).
- Ticker header shows last close + day change % + "last close · Nd ago"
(the age reveals OHLCV collection lag — why entry looked off)
- Setup cards show Current price and entry drift; flag setups as
stale (price moved >1/3 toward target) or invalidated (past stop)
- Chart: draw only nearest support below + nearest resistance above
current price, plus a prominent "Now" price line (full S/R stays in
the S/R tab)
- Chart overlay is selectable (Auto/Long/Short/None) — only the chosen
setup's entry/stop/target render, instead of everything at once
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Triggered by CNC showing "LONG (High Confidence)" with SHORT reasoning
and no long setup.
- A: recommendation action + reasoning are ticker-level and identical
on both setups; reasoning always matches the shown action
- B: recommended_action only picks a direction with a tradeable setup;
strong bias with no setup (e.g. price at ATH) → NEUTRAL with an
explanatory reason instead of a fake LONG_HIGH
- C: confidence is a directional-agreement model — opposing signals push
it below 50 (SHORT on a 92-technical/99-momentum stock ~0%, not 55%)
- D: fundamental score requires >=2 real metrics (market-cap-only no
longer yields a high score)
- E: RSI score peaks at healthy momentum (~60) and penalizes
overbought/oversold extremes instead of treating RSI 90 as maximal
- F: fundamentals chain merges fields across providers (FMP market cap
+ Finnhub P/E) instead of stopping at the first with any field
- NEUTRAL label: "No Clear Setup" (covers untradeable-bias case)
Scores recompute on next scan/scoring run; C and E shift score
distributions intentionally.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
xAI returned 410 — search_parameters/Live Search is retired. Route xAI
through the Responses API web_search tool instead (same path as OpenAI):
- OpenAISentimentProvider parametrized with base_url / tool_type / source
- xAI builds it against https://api.x.ai/v1 with the web_search tool
- Drop the dead Live Search code from the generic compatible provider
- Frontend label: "xAI Grok — web search"
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Providers (admin-switchable, no redeploy):
- DeepSeek and any OpenAI-compatible endpoint (OpenRouter, Together,
Groq, local Ollama) via a generic Chat Completions adapter + base_url
- xAI Grok with Live Search (search_parameters web+X, citations) —
grounded tier alongside OpenAI and Gemini
- DeepSeek / generic compatible endpoints are ungrounded (no web
search); UI shows an amber warning and labels each provider's grounding
- Optional env fallbacks DEEPSEEK_API_KEY / XAI_API_KEY
UI: replace native <select> (unstyleable white popup on Windows) with a
custom dark Dropdown component everywhere — sentiment provider, scanner
filters, market sort, indicators, admin universe, user role.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Make "qualified" mean an edge candidate, not just R:R + confidence.
The gate now also requires (all admin-configurable, defaults on):
- high conviction: recommended_action LONG_HIGH / SHORT_HIGH only
- clean read: risk_level Low (no contradicting signals)
- probable primary target: best target probability >= min (default 60)
- Shared predicate: app/services/qualification.py +
frontend/src/lib/qualification.ts (mirrored)
- Activation config extended (min_target_probability,
require_high_conviction, exclude_conflicts) with bool-aware
get/update + validation
- /trades/performance switched to ?qualified_only=true, applying
the full gate server-side; confidence breakdown stays unfiltered
- Dashboard "Qualified", Signals "Qualified only" toggle, and
Track Record all use the one gate; Admin gains the new controls
Sentiment provider runtime config (prior change) included.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Admin-configurable thresholds (min R:R, default 2.0; min confidence,
default 70%) defining what counts as an actionable signal:
- Admin Settings: new Activation Thresholds panel
(GET/PUT /admin/settings/activation)
- GET /trades/activation exposes values to all users with access
- Signals/Setups: filters initialize from activation values
- Track Record: "Qualified signals only" toggle (default on) via
min_rr/min_confidence params on /trades/performance; the
confidence breakdown always covers the full population so the
thresholds can be validated against outcomes
- Dashboard: "Qualified" metric and qualified-first Top Setups
- Outcome evaluator unchanged: every setup is still evaluated
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
- Technical dimension now uses all directional indicators:
0.30*ADX + 0.20*EMA + 0.20*RSI + 0.15*EMA_Cross (bullish=80 /
neutral=50 / bearish=20) + 0.10*Volume_Profile (POC proximity)
+ 0.05*Pivot_Points (structure confluence); weights re-normalize
when data is insufficient, as before
- ATR stays out of scoring (volatility input for scanner stops,
not a directional signal)
- IndicatorSelector uses the shared Select so the option list is
dark instead of the native white popup
- Update technical scoring tests for the six-component breakdown
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Closes the feedback loop on R:R scanner signals:
- Nightly outcome_evaluator job replays unresolved setups against daily
OHLCV bars: target_hit / stop_hit / ambiguous (same-bar, counted as
loss) / expired after OUTCOME_EVALUATION_MAX_BARS (default 30)
- Migration 004: evaluated_at + outcome_date on trade_setups
- GET /trades/performance: hit rate, expectancy (avg R), total R with
breakdowns by direction, recommended action, and confidence bucket
- New Performance page (stat cards, breakdown tables, Evaluate Now,
methodology disclosure) wired into sidebar and mobile nav
- 17 new unit tests for evaluation logic and stats aggregation
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
