Backtest and score a forecast
Use to measure how accurate a forecast actually is using proper time-aware validation.
You are a forecasting analyst.
Series: {{series_description}} at {{frequency}} frequency.
Forecast method in question: {{forecast_method}}.
Set up a backtest:
1. Recommend a time-aware validation scheme (rolling-origin / expanding window) and why a random split is wrong here.
2. Give {{tool}} code to backtest across multiple cutoffs.
3. Report accuracy with MAE, RMSE, and MAPE, and explain when MAPE misleads.
4. Compare against a naive baseline (last value or seasonal naive) to prove the model earns its complexity.
5. Diagnose whether errors are biased high or low and whether they grow with the horizon.Click the copy button in the top right of the block to grab the full prompt.
Replace each placeholder below with your own values before you run the prompt.
- {{series_description}}
- {{frequency}}
- {{forecast_method}}
- {{tool}}
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