Fahali publishes a live accuracy scorecard. Every signal is tracked from creation to outcome against subsequent price action. Correct and incorrect are measured on the same scale. There is no separate scorekeeping.
The scorecard measures detection performance across four axes. Directional engines predict market direction (up/down). Magnitude engines predict a move exceeding 0.5%. Volatility engines predict regime expansion. Crash detection predicts a rapid decline exceeding 2% within 72h.
| Engine | Axis | Precision | Base rate | Lift | Signals |
|---|---|---|---|---|---|
| Volatility | Magnitude | 93.2% | 54.1% | +39.1pp | 18,412 |
| Momentum | Direction | 65.1% | 55.0% | +10.1pp | 21,048 |
| Dark Pool | Magnitude | 86.3% | 54.1% | +32.2pp | 14,672 |
| Order Flow | Direction | 64.8% | 55.0% | +9.8pp | 19,204 |
| Regime Detection | Volatility | 89.7% | 58.3% | +31.4pp | 11,554 |
| Crash Predictor | Crash | 80.5% | 42.6% | +37.9pp | 6,201 |
| Correlation | Volatility | 87.2% | 58.3% | +28.9pp | 9,887 |
| Order Imbalance | Direction | 61.3% | 55.0% | +6.3pp | 22,418 |
| Liquidity | Volatility | 85.0% | 58.3% | +26.7pp | 12,338 |
| Squeeze | Magnitude | 84.1% | 54.1% | +30.0pp | 8,109 |
| Funding | Magnitude | 82.6% | 54.1% | +28.5pp | 5,217 |
| Capital Flow | Direction | 59.4% | 55.0% | +4.4pp | 15,663 |
| Skew | Volatility | 83.8% | 58.3% | +25.5pp | 7,441 |
| Volume Spike | Magnitude | 91.5% | 54.1% | +37.4pp | 16,892 |
| Reversal | Magnitude | 87.6% | 54.1% | +33.5pp | 10,235 |
| Divergence | Magnitude | 88.4% | 54.1% | +34.3pp | 9,718 |
| Confluence | Magnitude | 93.8% | 54.1% | +39.7pp | 7,016 |
| Stealth | Magnitude | 85.5% | 54.1% | +31.4pp | 11,906 |
Every alert created by a Fahali detection engine is assigned a unique ID and recorded in the outcomes ledger with its engine, symbol, timestamp, predicted direction (if directional), and confidence score. After the forecast horizon expires (1-72 hours depending on engine type), the outcome is resolved against actual price action. The outcome is then classified into one of four axes: direction (bullish/bearish correct/incorrect), magnitude (>0.5% move detected), volatility (regime expansion), or crash (>2% decline within 72h). Blended precision is the weighted average across all engines within each axis.
The base rate is calculated from a 90-day rolling window of the same metric. For magnitude, it is the frequency of 1-hour windows where absolute return exceeds 0.5%. For direction, it is the frequency of the more common direction in 1-hour windows. For crash detection, it is the frequency of 72-hour windows where decline exceeds 2%. Base-rate lift = precision − base rate. A positive lift means the engine performs better than a naive "always guess the most common outcome" strategy — the only metric that separates genuine signal from market drift.
To prevent the same signal from being counted multiple times in consecutive scans, Fahali enforces a 900-second (15 minute) cooldown per (symbol, alert_type) pair. During the cooldown window, duplicate alerts are suppressed at the write boundary. This ensures the scorecard reflects the accuracy of the detection, not the frequency of its activation. The deduplication layer operates independently of the detection engines — no engine is aware of another's cooldown state.
The scorecard measures precision (how many of our alerts are correct), not recall (how many correct alerts we could have produced). This is intentional: in risk surveillance, false positives erode trust faster than missed opportunities. Fahali prioritizes precision over recall because an alerting system that cries wolf is tuned out. The 7-engine consensus layer and 900-second cooldown are both precision-maximizing design decisions.
If Fahali were optimized for recall, we could emit alerts on every scan cycle and catch every move. The scorecard would show 95%+ recall. But the false positive rate would destroy usefulness. The 80-88% blended precision you see reflects the deliberate design choice to only alert when the evidence is strong and confirmed across independent engines.
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