Macrosentiment

Macro-economic sentiment dashboard that tracks ~40 indicators across 9 categories, classifies the current market regime, and produces a composite sentiment score from -100 to +100.

Overview

The dashboard continuously monitors growth and inflation momentum across the economy, then classifies the environment into one of four market regimes:

Regime	Growth	Inflation	Implication
Goldilocks	↑	↓	Risk-on equities
Reflation	↑	↑	Commodities, cyclicals
Deflation	↓	↓	Bonds, quality
Stagflation	↓	↑	Defensive, cash, gold

Scores are derived from z-scores computed over a 3-year lookback window, weighted by category, and scaled to the -100 → +100 composite.

Tech Stack

• Backend: FastAPI (Python 3.12), SQLAlchemy async, PostgreSQL
• Frontend: React 19, TypeScript, Vite, Tailwind CSS, TanStack Query, Recharts
• Deployment: Docker Compose (3 services: db, backend, frontend)
• Fonts/Theme: JetBrains Mono, Catppuccin dark

Data Sources

Source	Indicators
FRED API	Interest rates, inflation, GDP, labor, credit spreads, liquidity
IBKR Gateway	VIX, DXY, Gold, Oil, Copper, S&P 500
Manual entry	AAII sentiment, forward P/E
Computed	2s10s yield curve spread, SPX vs 200-day MA

Quick Start

Prerequisites

• Docker & Docker Compose
• FRED API key (free at fred.stlouisfed.org)
• Interactive Brokers Gateway running on port 4001 (for market data; FRED-only mode still works)

Setup

# 1. Clone the repo
git clone https://github.com/py77/macrosentiment.git
cd macrosentiment

# 2. Create your .env file
cat > .env << 'EOF'
FRED_API_KEY=your_fred_api_key_here
IBKR_HOST=host.docker.internal
IBKR_PORT=4001
IBKR_CLIENT_ID=78
EOF

# 3. Start all services
docker compose up -d

# 4. Trigger the initial data fetch
curl -X POST http://localhost:8002/api/fetch/trigger

# 5. Open the dashboard
open http://localhost:3002

The backend runs Alembic migrations and seeds the indicators table on first start.

API Endpoints

GET  /health                        Health check
GET  /api/dashboard                 Full dashboard payload
GET  /api/indicators                All indicators with latest values
GET  /api/indicators/{id}/history   Time-series for one indicator
GET  /api/regime/current            Current regime + scores
GET  /api/regime/history            Regime timeline
POST /api/fetch/trigger             Manual data refresh
GET  /api/fetch/status              Last fetch times per source
POST /api/indicators/manual         Submit manual indicator values

Configuration

Variable	Default	Description
FRED_API_KEY	—	Required for FRED data
IBKR_HOST	host.docker.internal	IBKR Gateway host
IBKR_PORT	4001	IBKR Gateway port
IBKR_CLIENT_ID	78	IBKR client ID
DATABASE_URL	set by compose	PostgreSQL connection string
CORS_ORIGINS	—	Additional allowed origins (comma-separated)

Project Structure

macrosentiment/
├── backend/
│   └── app/
│       ├── main.py          FastAPI app, lifespan, CORS, routers
│       ├── config.py        Pydantic Settings
│       ├── database.py      Async SQLAlchemy engine + session
│       ├── models/          ORM models (indicator, value, regime, fetch_log)
│       ├── schemas/         Pydantic response models
│       ├── services/        FRED, IBKR, processor, regime, scoring, data_fetcher
│       ├── tasks/           APScheduler (23:00 UTC daily + 13:30 UTC weekdays)
│       └── api/             Route handlers
├── frontend/
│   └── src/
│       ├── api/             Axios client + API functions
│       ├── hooks/           TanStack Query hooks
│       ├── types/           TypeScript interfaces
│       ├── components/      RegimeQuadrant, CompositeGauge, CategoryCard, etc.
│       └── pages/           DashboardPage
└── docker-compose.yml

Useful Commands

# View backend logs
docker compose logs -f backend

# Run a migration
docker compose exec backend alembic upgrade head

# Rebuild after dependency changes
docker compose up -d --build

# Database shell
docker compose exec db psql -U postgres macrosentiment

# Re-seed indicators table
docker compose exec backend python -m app.services.seed

License

MIT