Documentation Index
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Compare forecasting models on their losses: superior predictive ability (SPA) and reality check p-values and the StepM set of models that beat a benchmark, and the model confidence set of the best models, all with block-bootstrap inference.
vol_comparison: 2 tools.
| Tool | What it does | Notes |
|---|---|---|
vol_spa | Tests whether any of several forecasting models beats a benchmark on their losses, with block-bootstrap inference that accounts for data snooping: Hansen’s SPA (lower, consistent and upper p-values, critical values, the models significantly better), White’s reality check, or Romano-Wolf StepM (the set of superior models at the given size). | |
vol_mcs | The model confidence set of Hansen, Lunde and Nason: the models whose losses are not significantly worse than the best, at confidence 1 - size, found by sequential elimination with block-bootstrap p-values. |
fincept_describe_tool.