MKLAB / OPEN BENCH
ZephyrTrade
Explore synthetic wind-market observations, compare nine strategies, and calculate hypothetical offers without placing trades.
Loading local workspace controls…
Public browser demonstration
Purpose
ZephyrTrade is a local research application for synthetic wind, weather, and price data. Its browser demo supports scenario calculations and strategy comparisons; an optional local Python service adds a separate SciPy cross-check.
Open app ↗Open comparison (0/3)Your first workflow
- Use Overview to filter the bundled observations by strategy or date.
- Open the Strategy lab to edit assumptions and calculate a hypothetical offer.
- Compare strategies in Model arena or inspect observations in Data explorer.
Published capabilities
- Explore a bundled hourly dataset with filters, charts, and CSV inspection.
- Compare nine sample strategies and review their evidence and method notes.
- Edit assumptions to calculate hypothetical offers and save named scenarios locally.
Before you use the result
- The bundled snapshot is historical and synthetic; it does not show live prices or current forecasts.
- There are no real orders, brokers, accounts, or trading connections.
- The optional Python service is a local cross-check, not an automatic model retraining service or public backend.
Data: synthetic demonstration
Inspect the evidence behind this app →Source and configuration
Verified public source ↗License: MIT. Storage: Not documented.
Start with the published browser edition above. Local backend setup, when available, belongs to the source repository’s own instructions; it is not executed by this overview.
Questions and answers
Does ZephyrTrade use live wind or market data?
No. The browser demo uses a bundled historical test snapshot and synthetic data.
Does the Python service train a new forecast model?
No. It provides a separate local SciPy cross-check; changing filters does not train a new model.