{"uid":"cap_FePrZ-eaiVRXYuCWn088a","slug":"api-quantoracle-dev-67af3bde","name":"QuantOracle GARCH Volatility Forecast","description":"QuantOracle: stats/garch-forecast","url":"https://api.quantoracle.dev/v1/stats/garch-forecast","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"returns":{"type":"array","items":{"type":"number"},"title":"Returns","maxItems":5000,"minItems":30,"description":"Array of return data (max 5000)"},"mean_model":{"enum":["zero","constant"],"type":"string","title":"Mean Model","default":"zero","description":"Mean model specification"},"forecast_periods":{"type":"integer","title":"Forecast Periods","default":5,"maximum":252,"minimum":1,"description":"Number of periods to forecast ahead (max 252)"}}},"responseSchema":null,"example":{"request":{"p":1,"q":1,"horizon":10,"returns":[0.0125,-0.0089,0.0234,-0.0156,0.0098,0.0167,-0.0203,0.0145,-0.0112,0.0189,0.0076,-0.0134,0.0201,-0.0167,0.0143,0.0098,-0.0176,0.0212,-0.0145,0.0167,0.0089,-0.0198,0.0156,-0.0123,0.0178,0.0134,-0.0167,0.0201,-0.0089,0.0145,0.0112,-0.0176,0.0198,-0.0134,0.0167,0.0098,-0.0145,0.0189,-0.0156,0.0123,0.0167,0.0145,-0.0198,0.0176,-0.0112,0.0134,0.0201,-0.0167,0.0089,0.0156],"mean_model":"constant"},"response":{"ms":21.13,"beta":0.914412,"_meta":{"url":"https://quantoracle.dev","docs":"https://api.quantoracle.dev/docs","powered_by":"QuantOracle"},"alpha":0,"omega":0.00001956,"persistence":0.9144,"log_likelihood":138.58,"current_vol_annualized":0.24,"forecast_vol_annualized":[0.240029,0.240026,0.240024,0.240022,0.24002],"long_run_vol_annualized":0.24}},"exampleRequest":{"p":1,"q":1,"horizon":10,"returns":[0.0125,-0.0089,0.0234,-0.0156,0.0098,0.0167,-0.0203,0.0145,-0.0112,0.0189,0.0076,-0.0134,0.0201,-0.0167,0.0143,0.0098,-0.0176,0.0212,-0.0145,0.0167,0.0089,-0.0198,0.0156,-0.0123,0.0178,0.0134,-0.0167,0.0201,-0.0089,0.0145,0.0112,-0.0176,0.0198,-0.0134,0.0167,0.0098,-0.0145,0.0189,-0.0156,0.0123,0.0167,0.0145,-0.0198,0.0176,-0.0112,0.0134,0.0201,-0.0167,0.0089,0.0156],"mean_model":"constant"},"tags":["x402"],"displayCostAmount":"0.015","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.015/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.015","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.015","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_gEneYa19MTR37hTfl5tgz","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.015","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Fits a GARCH model to a time series of returns and forecasts future volatility (conditional variance) over a specified horizon","exampleAgentPrompt":"Run a GARCH(1,1) volatility forecast on this daily BTC return series [0.02, -0.01, 0.03, ...] and give me the predicted conditional volatility for the next 10 days with 95% confidence intervals.","exampleUseCases":null,"resultDescription":"Returns GARCH model coefficients (omega, alpha, beta), forecasted conditional variance and volatility for each step in the horizon, and confidence intervals around the volatility forecast. May also include model fit statistics such as log-likelihood or AIC.","failureModes":["Non-stationary or insufficient return series causes model fitting failure","Invalid GARCH order (p or q = 0 or excessively large) returns parameter error","Return series too short to estimate parameters reliably","Convergence failure if series has extreme outliers or near-unit-root behavior","Missing or malformed input array returns 400 validation error"],"whenToPreferThis":"Use this endpoint when you need a statistically rigorous conditional volatility forecast based on GARCH modeling, especially for assets exhibiting volatility clustering (e.g., crypto, equities). Prefer this over simple rolling-window volatility when you need forward-looking variance estimates with confidence bounds rather than just historical realized volatility.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-15T12:49:30.066Z","isFirstParty":false}