signal-platform/docs/research/regime-monitor-v4.md

AI/Tech Risk Monitor v4 methodology

Named "Regime Monitor" until 2026-08-07; the filename's regime stem, the regime_monitor job id, the /regime route and the METHODOLOGY/snapshot fields keep the old word, because those are persisted or externally linked.

The AI/Tech Risk Monitor is an observational risk thermometer. It does not gate entries, exits, position size, ranking, or alerts about individual setups.

v4 supersedes v3 (2026-08-08). Unlike v3, whose calibration was ad-hoc and never landed, every number below is reproducible:

.\.venv\Scripts\python.exe scripts

un_regime_monitor_calibration.py ^ --methodology v2_reconstruction,v3,v4 --cache-dir .calib-cache

The harness replays the 408 sessions ending 2026-07-24 from the live inputs (Alpaca for all 33 symbols, FRED for VIX and HY OAS) with no database, and reproduces the published v2 and v3 figures before it will emit anything:

figure	published	replayed
v2 State avg	22.6	22.68
v2 State p80	35.1	35.1
v2 State max	91.2	91.2
v2 P3 pegged	39	39
v2 W1 live	108	108
v3 State max	87.4	87.4
v3 band shares	73.3 / 15.0 / 8.3 / 3.4	73.0 / 15.4 / 8.1 / 3.4

It refuses to emit a band recommendation, and exits non-zero, unless every hard gate passes — 33 symbols fetched with full warm-up, the whole basket on every session, the calendar anchors, 100% coverage on every row, and a row-wise state_v4 <= state_v3 invariant. Reading a calibration result out of a run whose pipeline did not validate is meant to be structurally impossible.

What changed in v4

V1 stopped saturating at VIX 30. (vix - 15) / 15 reached 100 at VIX 30 — the same defect v3 had just removed from P3, left in place one sensor over. VIX 30 is a bad week, 50 is a crisis and 82 was March 2020, and all three scored identically. In the calibration window this flattened five distinct April-2025 prints (52.33, 46.98, 45.31, 40.72, 38.57) into a single 100. It pegged on 14 of 408 sessions; under the anchors below, none.

The trend break is graded by depth, not a yes/no. _under_200 returned a bare 0/100, so P1 printed 100 the moment SMH and QQQ were both under their average — and because the price pillar takes max(P1, P2, P3), that pinned the pillar and stopped P3's anchored ladder resolving anything for the whole of a selloff. It pegged on 46 of 408 sessions; now none. A 2% break reads ~30 where it used to read 100.

max() was kept. The defect was the step function feeding it, not the vote itself, and v3's "one capped vote for correlated reads" rationale still holds. Over the window P1 is the sole price argmax on 17 of 408 sessions (4.2%), so it informs the pillar without owning it — the P1_SCORE_CAP fallback considered during design was measured as unnecessary and not shipped.

The top State band moved 80 → 65. See Calibration; this is the one change that is about the band rather than a sensor.

Scope. All three are State-side. WARNING_BANDS, WARNING_WEIGHTS, QUADRANT_WARNING_DIVIDER and the event study's frozen threshold are untouched. QUADRANT_STATE_DIVIDER stays 50 because only breaking moved.

What changed in v3

Fundamentals left the score. F1 (capex) and F3 (good-news-stock-down) carried 12 + 8 of 100 Warning points. Pegged at maximum stress they produced a Warning of exactly 20.0 — below the event study's 25.3 alarm threshold, and still inside the "stable" band. The sourced observation could not change any published conclusion, so refreshing it looked like it did nothing. They are now a qualitative overlay reported beside the scores. Capex also stopped scoring raising and holding identically at 0: holding is the deceleration case and now scores 50, so a boom no longer reads the same as a stall.

The drawdown sensor stopped saturating. v2 used dd_pct * 5, reaching 100 at a 20% drawdown — the 90th percentile of the observed distribution. 39 of 408 sessions sat at exactly 100 with no resolution left, and the price pillar showed the top band on 13.5% of sessions. v3 uses named anchors with headroom past the observed 36% maximum, and blends leader/confirm 2:1 as P1 and P2 already did instead of taking max(). P3's realized share of State falls from 65% to 40%, matching its nominal weight.

Warning gained a sensor with range. The HY OAS level is pinned at zero below the 3.5 mild anchor (2.77 at the cutover), so credit contributed nothing in a calm tape. Its 20-session rate of change still does, and spread widening is a classic lead.

The credit percentile leg was removed. Its reference window silently shrank from 10 years to 3 when ICE restricted the upstream series in April 2026, after which it scored 20 points of stress at a spread the same sensor's anchors call "mild". See Calibration below.

Breadth loss counts during declines. v2's divergence gate was price_ret >= 0, so the sensor zeroed during every selloff. On 2026-07-24 the basket shed 10 points of participation in 20 sessions while SMH fell 11.9% and Warning printed exactly 0. v3 tapers to a floor instead: deterioration counts fully when price masks it (true divergence, the dangerous pre-top case) and at 35% when price confirms it. Breadth level lives in State, but breadth velocity appears nowhere else, so this is not double counting.

Bands are per axis. v2 Warning never exceeded 64.9 in 408 sessions while State reached 91.2, yet both used 30/60/80 with quadrant dividers at 60. The upper half of the Warning axis was unreachable.

Outputs

State — current structural stress:

• Price structure, 40%: max(P1, P2, P3), one capped vote for correlated reads.
• Fixed-basket breadth level, 25%.
• HY option-adjusted credit spread level, 20%.
• VIX level, 15%.

Warning — deterioration and divergence:

• Fixed-basket breadth divergence, 45%.
• 60-session SMH/SPY relative-strength deterioration, 30%.
• HY OAS 20-session widening, 25%.

Combined, RSP/SPY (former F4), and the NVDA canary (former P6) do not enter v3 or v4.

Calibration

Interpolated sensor tables

All three are (x, stress score) pairs read by _interpolate, flat outside the first and last anchor.

sensor	anchors
P3 drawdown (% below the 52w high)	0→0, 4→10, 8→25, 16→50, 28→78, 40→100
P1 trend break (% below the 200-DMA)	0→20, 3→35, 8→55, 15→75, 25→100
V1 volatility (VIX level)	15→0, 20→20, 25→38, 30→55, 40→80, 55→100

P1's floor of 20 at the crossing is deliberate: the break itself is a genuine binary event and deserves a floor; only the depth past it is graded. P1 is calibrated to sit alongside P3 rather than swamp it — the 200-DMA lags, so a 20% drawdown typically coincides with ~10% below the average, where P1 reads ~61 against P3's ~59.

V1 reaches full scale at 55 rather than at 2020's ~82: anchoring the top at a once-in-a-generation print would make VIX 50 — a genuine crisis — read only ~70. The anchors encode the long-run distribution as constants, the same argument the credit level uses. Unlike P3 and V1, whose slopes ease off monotonically, P3's do not (2.5, 3.75, 3.125, 2.33, 1.83) — its gentle onset is intentional and the monotone-slope test excludes it.

Credit impulse is relative (+35% over 20 sessions = 100) rather than absolute, because +0.5pp means something very different at an OAS of 2.7 than at 8.0.

Bands

Round, meaning-anchored numbers, not percentile fits — those would drift on every rebuild and silently rewrite what past snapshots meant.

Why breaking moved 80 → 65. With credit calm, f2_credit_spreads returns 0.0 (not None), so it keeps its full 20 points pinned at zero. Price, breadth and volatility at literal maximum therefore sum to:

(100×40 + 100×25 + 0×20 + 100×15) / 100 = 80.0 exactly

band_for uses >=, so v3's top band was reachable only by touching its floor to the decimal, with nothing above it. The band was fit on v2, when credit's since-removed percentile leg still contributed regularly; the sensor is not wrong — a calm-credit selloff genuinely is less stressed than one with credit contagion — the threshold was stale.

Chosen by scenario arithmetic on unchanged weights (_scenarios in the harness computes these, so they are machine-checked, not prose):

scenario	price	breadth	C1	V1	State
Ordinary tape (3% dd, breadth 65%, VIX 16, OAS 2.8)	7.5	0	0	4.0	3.6
10% correction, calm credit (2% below, breadth 35%, VIX 24)	31.2	62.5	0	34.4	33.3
2022-style drawdown, calm credit, no death cross	90.8	100	0	60.0	70.3
same, with death cross (P2 pegged)	100	100	0	60.0	74.0
Credit event on top (OAS 6.0, VIX 45)	100	100	75.0	86.7	93.0
March 2020 (everything pegged)	100	100	100	100	100

Rows 3 and 4 are the case this monitor exists to measure, and they must print breaking. At 80 they do not. 65 clears them under either P2 assumption, which matters because P2 is set by the 50/200-DMA gap and no drawdown figure implies it; 70 would have left 0.33 points of headroom in row 3, reproducing the defect being fixed.

Realized shares, reported not fitted, over the 408 sessions to 2026-07-24:

Axis	stable	watch	elevated	breaking	thresholds
State (v4)	78.9%	13.0%	4.7%	3.4%	20 / 50 / 65
Warning	69.4%	19.6%	7.6%	3.4%	20 / 40 / 60

The v4 breaking share lands on 3.4% — the same as v3's — having been chosen by scenario reasoning rather than aimed at that number. Sensitivity: 60 gives 5.1%, 70 gives 1.2%.

Quadrant dividers sit at each axis's watch/elevated boundary: State 50, Warning 40. Only breaking moved in v4, so the dividers and every alert threshold are unchanged. test_quadrant_dividers_match_the_band_boundaries now enforces that relationship, which nothing did before.

Scores renormalize over available fixed weights, but a band is published only at 75% or greater coverage. Trend deltas are suppressed when the participating pillar set changes. Zero means ordinary/healthy; only stress contributes.

Credit level is the named HY OAS anchors alone: 3.5 mild, 5.0 elevated, 7.0 stressed, linear between, and nothing else. v2 blended those anchors at 70% with a 30% upper-tail percentile over a nominally 10-year window.

That leg was removed rather than repaired. ICE restricted FRED to a rolling 3-year window for BAMLH0A0HYM2 in April 2026 — the series metadata states it outright ("Starting in April 2026, this series will only include 3 years of observations"), and an unbounded request returns the same 795 observations as a 30-year one. The v2 percentile therefore ranked the current spread against three uniformly tight years (range 2.59–4.61 over the calibration window), which made it fire early and saturate absurdly: at an OAS of 3.50 — the level the anchors call mild, scoring zero stress — the blended sensor read 20.1, and the percentile leg pegged at 100 by an OAS of 4.5. Across the 408 sessions it roughly tripled the credit sensor's average (2.70 vs 1.00) and more than doubled its nonzero days (60 vs 27).

The anchors already encode the long-run distribution as constants, so the percentile was a second, noisier estimate of the same thing. What it was genuinely reaching for — "unusual versus recent history" — is now W3 on the Warning axis, computed as a rate of change, which is where deterioration belongs. Removing it moved State's average by −0.4 and its maximum by −3.8, left Warning bit-identical, and did not shift any band threshold.

A long-history alternative (BAA10Y, Fed-published, 7,712 observations back to 1997) was considered and rejected: ranking an HY spread against investment-grade history is not a coherent statistic, and it would rescue a leg that is redundant anyway.

Every snapshot now records data_quality.credit_history_days and vix_history_days. This defect was invisible for roughly three months because nothing asserted the window the code claimed; the spans make a future upstream truncation show up in the record instead of quietly reshaping a sensor.

Survivorship caveat. The basket was frozen 2026-07-15 but the calibration window reaches back to 2024, so names were partly selected for having done well. Every distribution above inherits that bias. It is the same bias v2 carried, so the v2/v3 comparison is like-for-like, but the absolute band shares are optimistic.

Point-in-time record

The first run under a new METHODOLOGY rebuilds the latest 400 trading sessions with sufficient sensor warm-up; routine runs thereafter insert/update only the latest trading date. The history API and main chart show only snapshots matching the current methodology, so a bump reseeds the series rather than splicing two formulas into one line.

The fundamental overlay keeps its effective date (normally the next session after collection) and is never replayed backward, so a rebuild cannot stamp today's observation onto historical snapshots. Because the observation is stored in a single slot, a refresh replaces the previously effective record: the snapshot therefore reports the overlay as pending until the new effective date.

Two functions, deliberately: fundamental_overlay is the record and keeps the gate — it runs for every replayed date during a rebuild, so it must never grow a bypass flag. current_observation is the live reading behind fundamental_context, and reports the effective date instead of blanking the content.

Until 2026-08-07 the live reading called the gated function, so a just-collected observation stayed hidden until the next weekday — three days over a weekend — and refreshing appeared to do nothing. That was the opposite of what this section already claimed. Showing it early cannot leak into a published number, because nothing in the overlay is scored (see "Fundamentals left the score").

current_observation gates on observed (a non-null fetched_at, the one field every path writing real content stamps). Without it, the default override — unknown for every hyperscaler and mixed for the reaction — was reported as a live observation with available: true, so the card presented placeholders as a collected reading. Those are the absence of an observation, not an observation of absence. fundamental_overlay never had this problem: no observation means no effective date, which means pending, which already blanks the content.

Each snapshot stores the fixed basket symbols, hash, and freeze date. Reconstructed history before that freeze date is retrospective/exploratory.

Presentation

The page is deliberately thin: two gauges, one chart card, one pillar table, the overlay, and a provenance strip. Time and Path are two projections of the same snapshot series and share one card and one query key — they were previously two panels, which read as two datasets. Methodology rationale lives in this document, not on the page; page text is limited to what changes how the reader interprets today's number. The quadrant dividers rendered in Path view come from quadrant_config and are the same constants the alert path consumes (alert_service), so the chart cannot drift from what actually fires.

Warning study

The study calls the outcome a 10% correction, not a regime break. The first 70% of sessions freezes the 80th-percentile warning threshold; alarm episodes are measured on the final 30%. Because v3 dropped fundamentals from the score, the study now measures exactly the live Warning score rather than a technical-only approximation of it, and both are computed from one shared sensor definition (warning_sensor_scores) so they cannot drift apart.

A cached report is discarded when its methodology no longer matches, so the panel reverts to "not run yet" after a bump rather than showing stale numbers. Re-run the Event Study job after cutting over to v4.

Reading the result

The report carries a reliability block and the UI renders its warnings, because the headline numbers invite over-reading in two specific ways.

The holdout is thin. The study detects 11 corrections across 5 years but the 70/30 split leaves only 4 in the test period. Recall is therefore one event away from a materially different headline, and in practice the event that flips is decided by where the frozen threshold happens to land rather than by whether the score saw anything. The v3 cutover run illustrates it: v3 scored 2/4 against v2's 3/4, but "v3 without the credit sensor" scores 3/4 at a higher threshold (35.5) than shipped v3 misses it at (32.3) — because the alarm rule needs a rising edge, and a lower threshold can mean the alarm already fired outside the 20-session horizon and never reset below. Below MIN_EVENTS_FOR_CONFIDENCE holdout events the report says so explicitly.

Some events carry no information at all for comparison: in that run every variant caught 2026-03-06, every variant missed 2026-06-05, and every variant "caught" 2025-11-20 with a 1-session lead, which is coincident rather than a warning.

Sensor coverage can straddle the split. The score renormalises over available sensors, so a training window predating a sensor's history freezes the threshold on a different construct than the holdout is measured against. At the v3 cutover only 39% of training sessions had all three Warning sensors versus 100% of the test period, because credit history begins 2023-07-25.

Restricting the threshold to sensor-matched training sessions was tried and is not the fix: those sessions are a calm recent stretch, so the threshold drops from 32.3 to 22.5 and false alarms rise from 3.3 to 8.6 per year. It trades a coverage bias for a regime-selection bias. The honest position is that the threshold is hypersensitive to window choice at this sample size; the report states its limits rather than pretending to a precision it does not have.

Resolved in v4 (raised 2026-08-07, shipped 2026-08-08)

The three questions this section used to hold are now answered. Kept here because the reasoning that resolved them is not obvious from the code.

1. breaking had zero headroom — resolved by moving the band, not the sensor. f2_credit_spreads returns 0.0, not None, below the 3.5 mild anchor, so credit stays available at weight 20 and is pinned at zero on roughly 93% of sessions rather than being renormalized out. Price + breadth + volatility at literal maximum therefore summed to exactly 80.0 — v3's threshold, to the decimal.

The sensor is deliberately unchanged. A calm-credit selloff genuinely is less stressed than one with credit contagion, so scoring it lower is correct; what was stale was STATE_BANDS, fit on v2 while credit's since-removed percentile leg still contributed. Making credit None when calm was considered and rejected: it would leave State on 80% coverage, which still publishes, but consumes the whole buffer — any second missing pillar would then suppress the band, and the 7d/30d trend deltas would null out every time OAS crossed 3.5, because _delta suppresses on a change of participating pillars. See Calibration for the scenario arithmetic behind 65.

2. V1 saturated at VIX 30 — resolved with an anchor table. See "What changed in v4".

3. max(P1, P2, P3) defeated P3's anchoring — resolved by grading _under_200, keeping max(). The max was deliberate ("one capped vote for correlated reads") and survives; the binary step feeding it was the defect.

Its limit, stated precisely. _death_cross is clamp(-gap_pct * 20), so P2 pegs at a −5% 50/200-DMA gap — routine in a real downtrend. In a deep selloff the price pillar therefore still reaches 100 via P2 even with P1 graded. What v4 repairs is the shallow-to-moderate break, which is where resolution was most obviously missing: a 10% correction 2% below the average now scores 31 where v3 scored 100. It would be wrong to claim "the price pillar no longer pegs".

P2 did not peg once in the 408-session calibration window, so this is a property of the sensor rather than an observed problem. Grading P2 the same way is the natural next item if it starts binding; the replay reports a P2-pegged census alongside P3 and V1 so the evidence accumulates.

Fixed 2026-08-07: the OAS fetch window did not cover a rebuild

HY_OAS_WINDOW_DAYS was 400 calendar days, but a rebuild replays leader_series[-REBUILD_SESSIONS:] — 400 trading sessions, about 579 calendar days. The oldest ~180 calendar days of any rebuild therefore got no OAS data at all, so f2_credit_spreads and w3_credit_impulse both returned None. Verified: State then lands at 80% coverage and Warning at exactly 75.0% — MIN_COVERAGE — so both still publish bands. The rebuilt series would look homogeneous while its oldest rows had been scored without credit, the tell being a null data_quality.credit_history_days on exactly those rows.

The window is now 700 days: it must cover the oldest replayed date (~579) plus W3's lookback and slack, while staying under ICE's ~3-year cap so FRED still honours the request. This required no methodology bump — C1 reads oas_values[-1] and W3 reads oas_values[-21], both indexed from the end, so widening only prepends older observations and every live score is bit-identical. Confirmed by evaluating both windows against a varying synthetic series: today's C1/W3 match exactly, while the oldest rebuild row goes from None/None to real values.

Expect credit_history_days on new snapshots to rise from ~400 to ~700. That is the widened request, not new upstream history — and it makes the chip a better truncation canary, since a 700-day request returning ~1095 days' worth is now the visible ceiling.

Widening the window alone does not repair stored history. Routine runs recompute only the latest trading date, and rebuilding was keyed on "no v3 snapshot exists at all" — which is false once the cutover has run — so every row already written would have kept its credit gap indefinitely. SENSOR_REVISION fixes that: it is stamped into each snapshot, snapshots predating it read as 1, and a stored revision below the current one triggers exactly one reseed.

It is deliberately not METHODOLOGY. That constant partitions the history API and discards the cached event study; neither is warranted here, because the study recomputes its Warning series from source (_warning_series calls warning_sensor_scores against freshly fetched prices and OAS) rather than reading snapshots, so a reseed cannot stale it.

The reseed is bounded by REBUILD_LOOKBACK_DAYS in calendar days rather than a session count, because the binding constraint is the OAS fetch: each replayed row needs W3's 20-business-day lookback inside HY_OAS_WINDOW_DAYS. At 672 days the replay reaches ~464 sessions, W3's oldest requirement lands exactly on the first fetched OAS day, and the ~400-session series the v3 cutover wrote is fully covered. A test asserts that relationship so the two constants cannot drift into recreating the gap.

The fix was sequenced deliberately: acting on items 1–3 above bumped METHODOLOGY, which fires rebuilding, which would have baked the credit-less rows into the fresh series. Fixing the window first meant the v4 reseed replayed a clean window; doing it the other way round would have meant reseeding twice.

Operator rule

Quadrant alerts default off for new/reset configurations. When enabled they require fresh inputs, at least 75% coverage on both axes, two consecutive daily confirmations, hysteresis, and cooldown. Every alert states: Risk thermometer — not a trade signal.