news_bar = tickers_with_news_that_month / total_active_tickersfilings_bar = tickers_with_filing_that_month / total_active_tickers
sector_coverage = tickers_with_content_in_sector / total_tickers_in_sector
ticker_coverage = active_tickers_in_database / target_total (default 5000)
z = (news_count − mean) / std
pct = count_of_sentiment_label / total_news_items × 100
positive_pct = positive_news_that_month / total_news × 100redundancy_pct = mean(word_overlap_score) × 100 — high means we're pulling near-duplicate stories repeatedly.
bar_height = count(tickers with filing_count in that bin)
pct = count(form_type) / total_filings
positive_pct = positive_filings_that_month / total_filings × 100redundancy_pct = mean(word_overlap_score) × 100 (0% = fully unique, 100% = identical copies)
HEALTH = 100 × (0.70 × content_quality + 0.30 × data_presence)| Term | What it means |
|---|---|
| Health Score | A 0-100 data quality score per company. Combines content quality (70% weight) and data presence (30%). Low score = that company has missing or poor-quality data. |
| Content Quality | Weighted average of four sub-metrics: uniqueness (1 − redundancy), relevancy, coverage (specificity), and confidence (corroboration). Scale: 0-1. |
| Presence | Average of three checks: is the latest price recent? are there enough news items? is there any filing in the last 180 days? 1.0 = all present, 0 = nothing. |
| Redundancy | Word-overlap (Jaccard similarity) between items about the same company. High = we're ingesting near-duplicate stories. Shown as 1 − redundancy so higher = more unique. |
| Relevancy | Whether an item is about a company we track AND carries a directional signal. Neutral-sentiment items score 0 — they're data but not a usable signal. |
| Confidence (proxy) | How sure we are about a signal. Based on corroboration: do multiple independent sources agree on the sentiment direction? Saturates at 3 sources. |
| Freshness | Days since the newest item arrived for a company. Low = up to date, high = stale data that may need re-ingestion. |
| σ (Sigma) | Standard deviation — measures spread from the average. ±1σ contains 68% of data, ±2σ contains 95%, ±3σ contains 99.7%. |
| Frequency Distribution | A histogram showing "how many companies have X items?" The bell curve overlay shows the expected normal shape for comparison. |
internal/build_dashboard.py straight from the market tables
and stored in public.internal_dashboard_snapshots.