benchmarks

Benchmarks

End-to-end benchmarking using BEAM (Backtesting, Evaluation, Analysis, Metrics).

BEAM replays historical data day by day, trains your model, makes forecasts, and scores them — all without data leakage.

Which notebook do I need?

I want to…	Start here
See how OpenSTEF performs (just run, no code changes)	XGBoost & GBLinear
Benchmark my own model	Implement a Custom Forecaster
Benchmark on my own data	Configure a Custom Benchmark
Score predictions I already have	Evaluate Existing Forecasts

Quick start

# Install (requires uv: https://docs.astral.sh/uv/)
uv sync

# Run the built-in Liander 2024 benchmark (XGBoost + GBLinear)
uv run python -m examples.benchmarks.liander2024.run_xgboost_gblinear_benchmark

Liander 2024

Pre-made benchmarks on the Liander 2024 STEF benchmark dataset. No code changes needed — just run.

Build Your Own

Templates for benchmarking custom models or custom data. See the Build Your Own section for a detailed walkthrough.