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Validation & Methods

Public methodology and performance records. Historical backtested results (1990–2025). Not investment advice.

Market Risk ClassifierSpace Weather (SEWS)

Product

Market Risk Classifier (MRC)

1. Performance Record

Episode-level results, 1990–2025 (35 years). Historical backtested performance. Live operation began 2025.

Risk ShapeEpisodesHitsFPPrecisionHorizon
CRISIS1312192%10 BD
SHOCK67571085%5 BD
ELEVATED49371276%7 BD
SHIFTING6964593%20 BD
STABLEMeta-state: ~88% of trading days
WHIPSAW123117695%10 / 20 BD
RESOLVED71521973%20 BD

Historical backtested performance (1990–2025). Past classifications do not guarantee future accuracy. BD = NYSE/Nasdaq trading days.

1.1 Classification Notes

CRISIS (12/13, 92% precision): The single false positive across 35 years is August 2019 (yuan devaluation, US-China trade war). CRISIS fired as the S&P 500 fell 3% that day, but VIX never reached the 35 hit threshold and the market recovered within the 10-business-day scoring horizon, so the scorer counts it as a false positive.Full case study with chart.

ELEVATED (37/49, 76% precision): Lower-confidence early-warning classification. Wider net, more false alarms. That tradeoff is intentional and disclosed.

WHIPSAW (117/123, 95% accuracy): When VIX spikes or SPX falls while the system holds STABLE, the classification is being tested and an Event Risk Brief opens. “Accuracy” means the fraction of episodes where the system was correct: the scare faded, or the system escalated within days. The 6 misses are episodes where the system held STABLE but the S&P 500 fell 5% or more within 20 sessions.

RESOLVED (52/71, 73% call-level precision): When the system returns to STABLE after an escalation episode while VIX remains elevated (≥ 20), the classification is saying the crisis has ended before conventional volatility signals confirm it. The 19 revised episodes cluster in structural bear markets (dot-com 20002002, GFC 20082009, rate cycle 2022) where the system correctly identified interim calms but structural problems resumed. In every case, the system re-escalated within a median of 10 trading days.

An episode = consecutive alert days collapsed with business-day cooldown. Precision = hits / (hits + false positives), scored within the forward-looking horizon. BD = NYSE/Nasdaq trading days. 0 BD = same-session classification, published pre-market. FP evaluated at the episode level, not per trigger day. Historical backtested performance. Live operation began 2025.

2. Event Criteria

What counts as a hit for each risk shape.

Risk ShapeHit if any ofHorizon
CRISISVIX ≥ 35  |  SPX 5d ≤ −3.0%  |  SPX 10d ≤ −6.0%  |  SPX 20d ≤ −10.0%10 BD
SHOCKVIX ≥ 30  |  SPX 5d ≤ −3.0%  |  SPX 10d ≤ −5.0%5 BD
ELEVATEDVIX ≥ 30  |  SPX 5d ≤ −3.0%  |  SPX 10d ≤ −5.0%7 BD
SHIFTINGVIX ≥ 22  |  SPX change ≤ −2.0%20 BD
STABLEActive when all other rules are inactive (meta-state)
WHIPSAWVIX up 25%+ over 5 sessions while STABLE  |  SPX down 4%+ over 10 sessions while STABLE10 / 20 BD
RESOLVEDSystem returns to STABLE after escalation while VIX ≥ 20. Miss = re-escalation to ELEVATED, SHOCK, or CRISIS20 BD
SHOCK and ELEVATED share outcome criteria but are triggered by different input thresholds and operate on different scoring horizons. WHIPSAW and RESOLVED are sub-states of STABLE, not standalone risk shapes. WHIPSAW fires when market conditions test the STABLE classification. RESOLVED fires when the system returns to STABLE after a real crisis while VIX remains elevated.

3. Scoring Methodology

How classifications are evaluated.

3.1 How an Alarm Is Evaluated

  1. Fixed rules: each alarm is specified by an immutable definition. No in-sample tuning in the backtest.
  2. Daily evaluation: conditions are checked per business day against historical inputs.
  3. Episodes: consecutive alert days are collapsed into episodes using business-day cooldowns and windows.
  4. Market events: independent market events (VIX/SPX patterns) are identified and deduplicated into event episodes.
  5. Scoring: an episode is a "hit" if a qualifying event occurs within a forward-looking scoring horizon. Otherwise it is a false positive.
  6. Metrics: precision, recall, and F1 are computed from episodes. All figures on the website come from these validation files.

3.2 Scope

What MRC doesWhat MRC does not do
Classifies market risk with fixed, rules-based definitionsProvide price targets or trade recommendations
Evaluates alerts against independent market events (SPX/VIX)Tune rules on evaluation windows (no in-sample optimization)
Uses business-day horizons and deterministic episode logicScore alerts with look-ahead or calendar-day shortcuts
Publishes definitions and validation methods publiclyClaim endorsement by data sources or agencies

3.3 Overfitting Controls

  • No in-sample optimization: backtests run the published rule logic as-is.
  • Forward-only scoring: hits require future events within a predefined BD horizon. No look-ahead.
  • Deterministic time handling: all windows, horizons, and cooldowns are business-day based.
  • Independent event labeling and deduplication with fixed event cooldown (10 BD).
  • Episode collapsing to prevent double-counting during prolonged spells.
  • Validation file isolation and regression snapshot parity checks.
  • Reproducible artifacts: episode-level CSVs (alerts, events, hits) for independent verification.

3.4 Signal Robustness

MRC classifications undergo perturbation analysis (bootstrapped resampling of episode-level outcomes) to verify that precision and recall remain stable under measurement uncertainty, not dependent on specific boundary conditions. Full perturbation methodology and confidence intervals are available in the institutional validation packet.

3.5 Validation Protocols

  • Held-out era evaluation on excluded historical eras; no tuning on the evaluation period.
  • Walk-forward validation: expanding-window approach with 2-year training, 1-year test, 90-day roll. Era splits (SC24/SC25) validated separately.
  • Leave-one-era-out to assess robustness by omitting eras and testing excluded windows.
  • Era stratification to surface instability and confirm consistency across market conditions.

3.6 Data Sources

Market data: S&P 500 (Yahoo Finance) and VIX (CBOE official daily history). Environmental data: the Mindforge Signal Platform time series, derived from public datasets (NOAA, NASA, USGS). References to third-party providers are for sourcing only and do not imply endorsement.

4. Event Risk Briefs

An Event Risk Brief is a briefing generated when market conditions and the daily MRC classification form a defined anomaly. Each brief contains three elements: the morning's classification, the market context with every value dated, and a historical analog showing every prior occurrence of the same anomaly with the distribution of what followed. The percentages in a brief are historical base rates. They describe history; they are not predictions.

4.1 Event Library

#EventTriggerAnalog Set
1EscalationThe system enters a more severe state than the prior sessionEvery prior first entry into that state
2Stand-DownThe system returns to STABLE after a non-STABLE episodeEvery prior return to STABLE
3Regime ActiveA non-STABLE state persists (reported with day count)Every prior first entry into that state
4Drawdown DivergenceS&P 500 down 4%+ over 10 sessions while STABLEEvery prior such day, de-clustered
5Volatility DivergenceVIX up 25%+ over 5 sessions while STABLEEvery prior such day, de-clustered
6RoutineNone of the aboveOrdinary STABLE days

4.2 Analog Rules

  • As-of discipline. An analog set contains only occurrences that had already happened on the morning of the report. No future information enters any report.
  • De-clustering. Occurrences within 10 sessions of a prior occurrence are counted as the same event, so one episode is never counted twice.
  • Outcome categories, fixed in advance. “Escalated” = system moved to a more severe state within 10 sessions. “Wrong” = no escalation within 10 sessions AND S&P 500 fell 5%+ within 20 sessions. “Resolved” = neither. The wrong category is always published, with dates.
  • Data sources. VIX: CBOE official daily history. S&P 500: Yahoo Finance. Classifications: MRC daily state history. All values are stated with their as-of date.
  • Evidence tiers. 1990–2024 classifications are backtested. January 2025 onward is out-of-sample. April 2025 onward was delivered in live production. Reports label these tiers wherever they are mixed.
Event Risk Briefs are research documents. Historical base rates are descriptive statistics about past occurrences of a defined anomaly; they are not predictions, price targets, or trading recommendations.
Or email sales@mindforge.tech
Space Weather

Space Weather Early Warning System (SEWS)

SEWS is a separate product from MRC. It classifies space weather risk, not market risk.

5. What SEWS Does

SEWS classifies space weather risk using upstream Forbush Decrease detection. It provides probabilistic risk context days ahead of many downstream storm-time indicators and public alerts.

SEWS is a complementary upstream scenario planning layer, not a replacement for official space weather forecasts. It does not predict specific events or their timing.

Not affiliated with NOAA, ESA, NASA, or any government space weather service.

6. SEWS Performance

Full-period backtest (2010–2024, 15 years, 31 cataloged events).

6.1 Full-Period Backtest

TierPrecisionEvents CaughtAvg LeadAlerts/Year
ELEVATED23%58%~7d~7/yr
CRITICAL46%29%~8d~2/yr
ELEVATED
Wider net. More false alarms. Use for early scenario planning.
CRITICAL
Selective. Higher confidence. Worth escalating monitoring posture.

6.2 Walk-Forward Validation (Out-of-Sample)

9-fold walk-forward (train on 2010–2016 base + expanding window, test on each subsequent year 2016–2024). 14 events in walk-forward test periods.

TierPrecision (fold-avg)Events CaughtLead (event-weighted)
ELEVATED17% ± 17%79% (11/14 events)~6.3 days
CRITICAL75% ± 14%57% (8/14 events)~7.6 days

Validates: Multi-day lead time holds out-of-sample (6–8 days). CRITICAL precision strong (75%). ELEVATED recall strong (79%).

Known limitations: High fold-to-fold variance on ELEVATED precision (sparse events per year). Small sample (14 events in walk-forward test periods).

7. SEWS Methodology

7.1 Detection Approach

SEWS uses environmental stress indicators and public space weather data streams to classify Forbush Decrease risk. Validation is performed against a pre-published event catalog (2010–2024) using a fixed 14-day scoring horizon.

7.2 Data Sources

  • Public space weather and geomagnetic datasets (NOAA SWPC)
  • Public CME and solar event catalogs (NASA DONKI)
  • Environmental monitoring networks for event cataloging and cross-checks
  • Mindforge Signal Platform (composite indices)

7.3 Scope

What SEWS doesWhat SEWS does not do
Classifies environmental risk states (NORMAL / ELEVATED / CRITICAL)Predict specific events or their timing
Delivers probabilistic upstream context days before official alertsReplace NOAA/ESA confirmed-event forecasts
Walk-forward validates with expanding-window methodologyClaim affiliation with government space weather services
Publishes tier performance transparently (including false alarm rates)Guarantee future performance based on historical validation

7.4 Overfitting Controls

  • Out-of-sample walk-forward validation (9 folds, 2016–2024)
  • Separate reporting of full-period backtests (descriptive) vs. walk-forward results (out-of-sample)
  • Event-weighted lead time for out-of-sample headline lead time
  • Transparent tier tradeoffs: ELEVATED prioritizes coverage, CRITICAL prioritizes confidence
View SEWS Product Page
Informational research only. Not investment, operational, or safety advice. Past performance does not guarantee future results. For complete reproduction procedures, request an auditor-friendly validation packet via the form above.

Research use only. Not investment advice. Past performance ≠ future results. Mindforge is not a registered investment adviser. Full terms · Methods

Validation & Methods | Mindforge