01 / Academic exercise
Excel forecasting and model comparison
As part of my university studies, I fitted and compared two models for monthly fuel-oil prices and estimated prices at half-month intervals.
- Status
- Completed academic exercise
- Tools
- Excel / Solver
- Data
- 12 monthly observations
Approach
Two models, one set of observations.
I used Excel and Solver to fit a cubic polynomial and a sinusoidal model by least squares. SSE, RMSE, and charts helped compare the numerical error and the behaviour of each model.
- 01Fit models to monthly fuel-oil prices
- 02Compare least-squares error with SSE and RMSE
- 03Estimate prices at half-month intervals
- 04Read the charts alongside model assumptions and seasonality
Results & limitations
Reading the fit carefully.
| Model | SSE | RMSE |
|---|---|---|
| Polynomial (cubic) | 161.19 | 3.67 |
| Sinusoidal | 164.61 | 3.70 |
These measures describe historical fit. Future forecasting accuracy has not been verified.
The lesson for me was to compare numerical error, model assumptions, and seasonality before choosing a model. Clear charts make that reasoning easier to explain.
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