090°Open data
Open datasets, fully documented — searchable here, and readable by any LLM.
4 datasets
Corporate Profit Signals (derived)
Quarterly signals derived from BEA corporate-profits data (redistributed by FRED): 30-quarter annualized change volatility, 1-quarter momentum, year-over-year change, 3-sigma anomaly flags vs a trailing 12-quarter baseline, naive-drift 1-quarter forecasts, a per-quarter cross-series volatility rank, the economy-wide profit margin (profits as % of GDP) and a 20-quarter margin z-score (the profitability-regime gauge). Covers corporate profits after tax from 1947. All rows are normalized to country_code USA so they join cleanly with US macro data. Raw series: Federal Reserve Bank of St. Louis (FRED); underlying data: U.S. Bureau of Economic Analysis.
SEC 8-K material-event velocity (agent-curated)
Monthly enrichment panel scoring how actively ~58 SEC-registered US and Canadian companies disclose material events. Each run fetches the keyless SEC EDGAR submissions JSON per company (ticker->CIK resolved from the SEC's own company_tickers_exchange.json) and classifies every 8-K's item codes into a documented 8-category taxonomy over the trailing 12 complete months. Per (company, month): 8-K counts by category, has_earnings_8k (item 2.02) and has_exec_change_8k (item 5.02) flags, event_intensity_score = 100 * (0.60 * min-max(n_8k) + 0.40 * min-max(n_governance + n_financial)) normalized within each month, a deterministic intensity_rank, and spike_flag when n_8k >= 2 with z >= 2.0 against the company's own 12-month baseline; every row carries its CIK and the exact source_url it was built from, the panel is dense and zero-filled, and foreign private issuers (6-K/40-F, no 8-K) keep structural zeros flagged by is_8k_filer. Who joins this: a quant desk joins monthly per-ticker event intensity to returns on ticker + month for event studies, and an IR/comms team benchmarks disclosure cadence against peers on company_name (primary key (as_of, month, company_name); join keys ticker, company_name, month, country_code ISO alpha-3). Caveats: category counts are item-code occurrences (a \"2.02,9.01\" filing counts once as financial and once as exhibits); intensity scores are within-month relative and not comparable across months; private companies and tickers absent from the SEC file are excluded. No filing text is stored.
US State Wage-Growth Signals (derived)
US state-level average hourly earnings signals (BLS via FRED, 50 states + DC, monthly 2007 ->): 12-month wage growth, 3-month momentum, 30-period change volatility, 3-sigma shock flags, drift forecasts, 5-year pay-pressure z-scores, the state-vs-US growth gap and cross-state growth ranks. The regional pay-pressure lens: where wages run hot or cold across the country. BLS data via FRED (free, keyless-by-reuse of the existing FRED key).
Wage & Productivity Signals (derived)
Monthly/quarterly signals derived from FRED's US earnings and productivity data: 30-period annualized change volatility, ~3-month momentum, 3-sigma anomaly flags vs a trailing 12-month baseline, naive-drift 1-month forecasts, a per-date cross-series volatility rank, the real-wage year-over-year gauge (worker purchasing power) and the productivity-minus-pay gap (the decoupling gauge). Covers nominal average hourly earnings, a connector-derived real-earnings series (CPI-deflated) and nonfarm business labor productivity. All rows are normalized to country_code USA so they join cleanly with US macro data. Raw series: Federal Reserve Bank of St. Louis (FRED); underlying data: U.S. Bureau of Labor Statistics.
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