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Market Intelligence

Market Sentiments

A market-regime desk that brings quick stress checks, slower confirmation layers, lawmakers activity, and watchlist context into one static review surface.

Type: dashboard Status: live Role: regime desk

Context

The project outgrew the insider-dashboard framing.

What started around insider activity became a broader market review desk once volatility, credit, breadth, positioning, macro, and lawmaker disclosures all proved useful as supporting context.

Problem

The signals that mattered lived on very different clocks.

Daily stress gauges, weekly sentiment, monthly regime studies, event-driven lawmaker disclosures, and ticker-level watchlist setups all carried useful context, but they were scattered across too many separate views.

Collection Pipeline

How the dashboard is actually built.

Scheduled Python collectors write market studies, watchlist state, and lawmaker disclosures into committed JSON snapshots. The walkthrough below shows how the GitHub Pages dashboard turns mixed-cadence inputs into one static market desk.

FRED + Yahoo AAII + NAAIM House PTR + watchlists GitHub Actions cron static JSON publish

Inputs

Preparation

Scoring / Context

Outputs

Decision

System design

Use scheduled JSON snapshots and client-side assembly.

GitHub Actions runs separate collectors for stress studies, macro and breadth regimes, historical insider context, watchlist price state, and House trading disclosures, then the single-page frontend assembles those datasets into one static dashboard.

What changed

The dashboard became a market desk instead of one niche panel.

The project now treats insider activity as one slower confirmation layer inside a wider operating surface that includes volatility, credit, positioning, macro, lawmakers, and watchlist workflows.

Limitations

Mixed public data means mixed reliability.

Some sources still depend on scrapers, browser fallbacks, or incomplete coverage, and the dashboard remains constrained by the uneven cadence of public market and disclosure datasets.

Next step

Make the desk resolve into clearer staging signals.

The next improvement is tightening how fast indicators, slower regime evidence, lawmakers activity, and watchlist targets roll up into one sharper opportunity or caution read.