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What is a naive forecast and a seasonal naive forecast?
A naive forecast simply uses the most recent observed value as the forecast for every future period. A seasonal naive forecast uses the value from the same point in the previous cycle, such as the same week last year or the same weekday last week. Both are free to produce and make strong benchmarks.
Naive works for series without clear seasonality, where the best guess for tomorrow is today. Seasonal naive suits series with strong repeating patterns, such as retail sales by day of week.
They ignore trend and one-off effects, so they can lag when things change. Their value is as a test: if a complex model cannot beat seasonal naive in backtesting, it is probably not worth deploying. They are also useful fall-backs when a model fails or data is missing.
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