[DEMO] Will FTC ruling on AI data practices be favorable?
Market 47.0% against model 55.0%. Resolves in 168d 7h, data updated 13d ago.
Why this is not actionable
The model can still be informative here, but one or more gates blocks a trade call.
Decision layer
No-trade decision
The model may still be informative, but at least one gate blocks an action-style signal.
Expected value after costs, not raw probability spread.
How much support the model sees across available inputs.
Thin markets can erase apparent edge through spread and slippage.
Resolution ambiguity, timing, and data quality pressure the decision.
poor feature coverage.
Why / why not trade
One decision layer for the market read.
This public box mirrors the internal diagnostic style without exposing execution controls: decision, probability gap, cost-adjusted edge, blocker, and next thing to monitor.
no side selected
55.0% model / 47.0% market
fees, spread, slippage, risk
Model confidence 0.31 below 0.40 — inputs too weak to disagree with the market.
Model confidence 0.31 below 0.40 — inputs too weak to disagree with the market.
Read this market in three passes
Model 55.0% vs market 47.0%.
Raw disagreement is reduced by fees, spread, slippage, and risk controls.
No trade
Why this read matters
The model may disagree with price, but the gates say the disagreement is not actionable right now.
[DEMO] Will FTC ruling on AI data practices be favorable?
Volume $105,625
Why the engine declines to trade this market
- - Model confidence 0.31 below 0.40 — inputs too weak to disagree with the market.
Declining to trade is a feature: most markets are priced fairly within costs, and the risk gates run before any edge is considered.
Market-implied vs model probability
Factor attribution
The model estimates a 8-point higher probability than the market, primarily driven by historical base rate.
| FACTOR | SIGNAL | WEIGHT | LOG-ODDS ΔLog-odds contribution measures how much each factor shifted the model's probability estimate in log-odds space — the mathematically correct way to stack independent evidence. Formula: Δlog-odds = weight × signal. Positive values push the probability up; negative values push it down. Log-odds are converted back to probability via the logistic function at the end. | DIRECTION | DESCRIPTION |
|---|---|---|---|---|---|
| Historical base rate | 35% | — | −0.619 | Bearish | Historical frequency for this kind of event — the prior before any market-specific evidence. |
| Model probability | 55.0% | Prior: 35% · Market: 47.0% | |||
| Confidence (λ)Confidence λ (lambda) controls how much weight to give the model vs. the market. Formula: p_final = λ·p_model + (1−λ)·p_market. λ is derived from data quality, factor agreement, and liquidity. When inputs are weak, the model shrinks toward the market — not toward 50%. | 0.31 | Final: 55.0% = λ·model + (1−λ)·market | |||
Comparable eventshistorical base rate 37.5% - n=8
| Event | Date | Outcome | Prior mkt prob. |
|---|---|---|---|
| SEC vs Terraform/Do Kwon — Default judgment | 2024-04-05 | SEC won $4.5B judgment by default after Do Kwon convicted in Montenegro. | -- |
| SEC Crypto enforcement — Coinbase wins dismissal motion | 2024-03-27 | Court denied some SEC claims; case continues. Mixed for Coinbase. | -- |
| EU AI Act — Final passage | 2024-03-13 | EU AI Act passed European Parliament. First comprehensive AI law. | 92% |
| Binance — DOJ settlement and guilty plea | 2023-11-21 | Binance pled guilty, $4.3B fine. CZ resigned as CEO. | 60% |
| FTX — Sam Bankman-Fried criminal conviction | 2023-11-02 | CONVICTED on all 7 counts. Sentenced to 25 years. | 90% |
| SEC vs Ripple (XRP) — Summary judgment on programmatic sales | 2023-07-13 | Partial win for Ripple. Programmatic XRP sales not securities. Institutional sales were. | 35% |
| OpenAI — FTC investigation opened | 2023-07-13 | FTC opened investigation into OpenAI's data practices. | -- |
| EU MiCA Regulation — Final passage | 2023-04-20 | MiCA passed European Parliament. Comprehensive EU crypto framework. | 90% |
Real historical events from the comparable-events library (showing 8 of 8 matched). The model's base rate is the realized frequency over the full matched set.
Scenario treeEngine template
Node probabilities are conditional on the parent; hover for cumulative path probability. Leaf EV is per $1 YES contract at the current price, before fees (fee-adjusted EVs in the table on the left).
| Path | Path prob. | YES pays | EV (YES, after costs) |
|---|---|---|---|
| Decision issued before deadline > Approved / enacted | 55.0% | $1 | +49.6c |
| Decision issued before deadline > Denied / rejected | 32.1% | $0 | -50.4c |
| Delayed past deadline | 12.9% | $0 | -50.4c |
Root-implied probability 55.0% reconciles with the model's 55.0% (±1pt invariant).
Description
Poor data quality on AI regulatory outcomes collapses model confidence below the threshold.
Resolution criteria (verbatim, with analyzer flags)
analyzed by heuristicResolves YES if the Federal Trade Commission issues a final ruling deemed favorable to AI companies regarding their data collection and training practices in 2026.
- Subjective judgment Resolution depends on someone's judgment call rather than an observable fact.
Resolves Sat, 12 Dec 2026 03:48:52 GMT. The contract pays on these exact criteria, not on the thesis.
Suggested paper position
The engine sizes NO TRADE markets to zero. Sizing never overrides the risk gates.
Paper position only. No real-money execution
Live open-market tracking
Since the first stored model read on 2026-06-09, the market has moved from 47.0% to 47.0%.
This is a directional diagnostic for unresolved markets, not final performance. Resolved outcomes still determine the official live record.
Data quality28/100 - poor
When features are unavailable, the model increases uncertainty and weights the final estimate closer to the market price. Lower data quality does not mean the market is wrong. It means the model is being appropriately humble.
Risk factor breakdownsim
| Inverse liquidity | 35 | |
| Price volatility | 29 | |
| Resolution proximity | 0 | |
| Data quality | 38 | |
| Category base risk | 60 | |
| Resolution ambiguity | 28 | |
| Regulatory exposure | 0 | |
| Portfolio concentration | 0 |
Composite score 44/100, higher = riskier.
Related markets
| Market | Mkt | Delta |
|---|---|---|
| Category context | ||
| [DEMO] Crypto regulatory bill passes Senate vote this week? same event: same venue event + same event type | 55.0% | +8pt |
Divergences > 5pt flagged in amber. For cross-venue pricing, see the Scanner.