This page summarizes recent prediction performance (last 7 days of 10‑minute snapshots). We focus on short-horizon directional accuracy and probability calibration.
| Evaluated predictions | 804 |
|---|---|
| Accuracy | 49.3% |
| Precision (UP) | 51.8% |
| Recall (UP) | 52.0% |
| Brier score (lower is better) | 0.2519 |
| Log loss (lower is better) | 0.6970 |
| Avg |realized return| (10m) | +0.22% |
| Avg hourly sigma (log std) | 0.0083 |
If probabilities are calibrated, then when the model says “60–65%”, UP should happen about 60–65% of the time (in that bucket).
| P(UP) bucket | N | Empirical UP rate |
|---|---|---|
| 0–55% | 775 | 53.3% |
| 55–65% | 29 | 34.5% |
| 65–75% | 0 | — |
| 75–100% | 0 | — |
Large BTC moves are often accompanied by rising realized volatility, outsized |10‑minute returns|, and frequent direction flips—conditions where simple momentum/mean‑reversion signals can become unstable.
To interpret why a specific spike occurred, cross‑reference spike timestamps in the archive with reputable, time‑stamped sources such as:
Practical workflow: find the largest |10‑minute returns| windows → search those timestamps in the sources above → annotate the likely catalyst(s), and whether the move looks like a news shock vs a positioning/liquidation cascade.
Not financial advice. Educational analytics only.