- fundlab/narrative.py: data-driven English prose per fund (performance, drivers tiered by fit, explicit 'what we do NOT know', bottom line) - fundlab/reportdata.py: static build -> reports/report_data.json - app.py Fund Lab Summary: at-a-glance table + per-fund expanders (narrative, equity curve, period table with fund-ref gap, drivers, reference mix, tax, cluster peers) - fundlab/report.py: narrative in the HTML report; forward-selected reference (weak-fit funds anchor to cash); SLEEVE_DESC exposure explanations - BUG: mix_series() never applied the betas (reference curves were raw sleeve sums; JLPSX 'reference' +407% vs fund +123%) - fixed and all reference curves/tables regenerated - reports/fund_report.html + report_data.json regenerated
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20 MiB
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