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Cobblestone Cross-Commodity Monitor

A repeatable monitor that transforms public European gas and carbon fundamentals into a clear trading narrative for European power.

Author

Filippo Grandoni
Email: filippo@grandoni.it

Project Objective

This project was built as a case study around the theme:

European Cross-Commodity Risk Pack: Gas + Carbon → Power Curve Implications

The goal is to automate a daily workflow that:

  • ingests public gas, carbon, and power inputs,
  • computes desk-usable monitor metrics,
  • generates charts,
  • produces a short daily brief,
  • structures unstructured market inputs through a code-integrated AI/LLM-style layer.

The output is designed to answer three practical questions:

  1. Are gas and carbon increasing or easing European power cost pressure?
  2. Is the risk concentrated in the prompt or extending into the curve?
  3. Is the dominant driver gas, carbon, or both?

What the Monitor Does

The pipeline:

  1. loads raw data from standardized input files,
  2. cleans and merges the series,
  3. computes daily monitor metrics,
  4. generates chart outputs,
  5. writes a daily desk brief,
  6. classifies headlines into structured JSON using a prompt-driven AI workflow.

This is intended to simulate a lightweight desk-ready recurring process rather than a one-off note.


Source Preparation Scripts

The repository includes explicit source-preparation scripts so that each dataset is traceable:

  • scripts/convert_agsi.py
  • scripts/prepare_power_de.py
  • scripts/prepare_ttf.py
  • scripts/create_placeholder_eua.py

These scripts document how public-source inputs are transformed into the standardized files consumed by the monitor.

Notes

  • Storage, power, and TTF are integrated as real public inputs.
  • The carbon leg is included as a public proxy series rather than a licensed exchange-grade feed.
  • The workflow is designed so that the raw data layer can be upgraded without changing the reporting logic.

Programmatic API Pull

The repository includes a programmatic public API pull for EU gas storage via GIE AGSI.

Run the full sequence from the repository root:

python scripts/fetch_agsi.py
python scripts/build_raw_inputs.py
PYTHONPATH=. python scripts/run_monitor.py

Core Metrics

The monitor currently computes:

  • Gas Tightness Score
  • Carbon Pressure Score
  • Cross-Commodity Cost Pressure
  • Power Pass-Through Monitor
  • Prompt vs Curve Stress Indicator
  • TTF 5D Momentum
  • EUA 5D Momentum
  • Event Risk Flags

These metrics are designed to map directly to power pricing risk rather than just describe raw market moves.


Repository Structure

cobblestone-cross-commodity-monitor/
├── config/
├── data/
│   ├── raw/
│   └── processed/
├── outputs/
│   ├── briefs/
│   └── charts/
├── prompts/
├── scripts/
└── src/

About

Automated cross-commodity monitor linking European gas and carbon fundamentals to power risk, with daily metrics, charts, and AI-structured desk brief outputs.

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