{"slug":"agent402-tools-api-forecast-naive-69b5b5","title":"Three textbook baseline forecasts","host":"agent402.tools","method":"POST","resource":"https://agent402.tools/api/forecast-naive","category":"other","description":"Three textbook baseline forecasts: mean (forecast = average of history), naive (forecast = last value), drift (linear extrapolation from first to last point). Use as a sanity floor - any sophisticated method (SES, Holt, Holt-Winters) should beat the best of these on a backtest, otherwise the extra c","price_listed":0.001,"price_asked":0.001,"state":"answering","state_label":"Answering","checks_7d":1,"answered_7d":1,"latency_ms_median":933,"reported_calls_30d":3,"reported_payers_30d":1,"networks":["algorand:wGHE2Pwdvd7S12BL5FaOP20EGYesN73ktiC1qzkkit8=","eip155:10","eip155:1329","eip155:137","eip155:143","eip155:42161","eip155:42220","eip155:43114","eip155:4663","eip155:8453","solana:5eykt4UsFv8P8NJdTREpY1vzqKqZKvdp","stellar:pubnet"],"badge":"unverified","paid_checks_7d":0,"paid_ok_7d":0,"example_input":{"body":{"horizon":3,"method":"drift","values":[10,12,13,12,15,16,18,19,21,22]},"bodyType":"json","method":"POST","type":"http"},"output_schema":{"$schema":"https://json-schema.org/draft/2020-12/schema","properties":{"input":{"additionalProperties":false,"properties":{"body":{"properties":{"horizon":{"description":"Number of future periods to forecast (1 to 1000)","type":"number"},"method":{"description":"\"mean\", \"naive\", or \"drift\" (default \"drift\")","type":"string"},"values":{"description":"Numeric series in chronological order (max 10000)","type":"array"}},"required":["values","horizon"]},"bodyType":{"enum":["json","form-data","text"],"type":"string"},"method":{"enum":["POST"],"type":"string"},"type":{"const":"http","type":"string"}},"required":["type","method","bodyType","body"],"type":"object"},"output":{"properties":{"example":{"properties":{"forecast":{"items":{"properties":{"lower95":{"type":"number"},"point":{"type":"number"},"step":{"type":"integer"},"upper95":{"type":"number"}},"type":"object"},"type":"array"},"horizon":{"type":"integer"},"method":{"type":"string"},"n":{"type":"integer"}},"required":["method","n","horizon","forecast"],"type":"object"},"type":{"type":"string"}},"required":["type"],"type":"object"}},"required":["input"],"type":"object"},"history":[{"day":"2026-09-24","reachable":true,"status":402,"valid_402":true,"asked_usdc":0.001,"price_match":true,"latency_ms":933,"error":null}],"description_full":"Three textbook baseline forecasts: mean (forecast = average of history), naive (forecast = last value), drift (linear extrapolation from first to last point). Use as a sanity floor - any sophisticated method (SES, Holt, Holt-Winters) should beat the best of these on a backtest, otherwise the extra complexity isn't earning its keep. Returns point forecasts + 95% prediction intervals per Hyndman §3.1.","last_updated":"2026-09-21T11:12:18.851Z","schemes":["exact","upto"]}