score_forecasts

io.github.beepboop2025/noisefloor · Verify this server

Backtest NoiseFloor's own one-step forecast on chronological historical prefixes, issuing before observing and then updating without hindsight. Use to evaluate forecast_next's coverage and misses; this tool does not accept externally supplied predictions. At least 20 readings are required; shorter valid histories return ok=false. Successful results contain n_forecasts, empirical_coverage, nominal_coverage, score, baseline_score, beats_baseline, records, misses and worst_misses. Scores are mean weighted interval scores in input units (lower is better), compared with fixed historical-error quantiles. Records use zero-based input indices and retain actual, forecast, interval and missed_by. within_coverage_tolerance and its calibrated alias mean observed coverage is within 0.05 of target; they are descriptive, not a certification or significance test. Coverage and favorable scores do not establish future market performance or profitability.