Snowtrail Documentation
Snowtrail builds regime classification data products for institutional commodity traders, covering natural gas, LNG and European power. Every dataset is delivered point-in-time correct, so a backtest sees only what was knowable at the time.
- New to Snowtrail? Start with the Quick Start Guide
- Ready to integrate? See our API Reference or Python SDK
- Explore products: Browse our Product Catalogue
What We Provide
Snowtrail organises market data into four core types:
Signals
Quantitative classifications derived from fundamental data. They describe the state the market is in for position sizing and risk conditioning.
Features
Curated, transformed datasets created from raw inputs. Research-ready building blocks for quantitative analysis.
Events
Structured records of market developments (outages, regime transitions, supply disruptions).
Backtests
Pre-computed test results for each product's headline claim, published whether the test passes or fails, so you can see what each signal has and has not been shown to do.
Products
Our products cover major energy and commodity markets:
| Product | Market | Data Types |
|---|---|---|
| GBSI-US | US Natural Gas | Models structural imbalance across US supply, demand, storage and flows to classify the prevailing gas regime |
| GBSI-EU | European Natural Gas | Point-in-time, country-level record of storage, LNG, weather demand and balance across European markets; a data product with no price claim |
| GLMI | Global LNG | Identifies the basin setting marginal LNG price formation between Europe and Asia (validated as coincident with the JKM-TTF spread; no measured lead) |
| PEMI | European Power | Grid-stress data feed: classifies power plant and transmission outage exposure by bidding zone, with no price claim |
| WRSI | Weather | Classifies forecast instability and weather relevance from ensemble spread, run-to-run change and model disagreement; no forward or sizing claim |
| WSSI-US | Weather | Classifies population-weighted weather demand anomalies against US gas storage surprises (validated in-sample; winter 2026-27 hold-out pre-registered) |
Getting Started
from snowtrail import Snowtrail
client = Snowtrail(api_key="your-api-key")
# Fetch the latest system stress signal for US natural gas
df = client.gbsi_us.system_stress()
print(df[["signal_date", "stress_regime_label", "confidence_score"]])
Who Uses Snowtrail
- Quantitative researchers building systematic trading strategies
- Commodity trading desks seeking timely market intelligence
- Risk management teams monitoring market exposures
- Portfolio managers focused on energy markets
Need Help?
- Browse the FAQ for common questions
- Review the API Reference for technical details
- Contact us at support@snowtrail.ai