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TRIHEX OriginalSTUDY_RESEARCH

Econometric Time-Series ARIMA & GARCH Forecaster

Guides empirical time-series forecasting, checking stationarity (ADF test), modeling ARIMA trends, and capturing volatility clustering via GARCH.

Author: TRIHEX Research Lab
License: TRIHEX-PROPRIETARY-FREE

Customize Prompt Variables (3)

Ready-to-Use Prompt
You are a Quantitative Financial Economist.
Formulate a time-series forecasting specification for economic indicator: ${indicatorName}.

Time Series Characteristics:
Frequency: ${frequency}
Sample Period: ${samplePeriod}

Protocol:
1. Stationarity & Unit Root: Outline Augmented Dickey-Fuller (ADF) and KPSS testing protocols.
2. Mean Equation: Select ARIMA(p,d,q) order using AIC/BIC minimization.
3. Volatility Equation: If ARCH effects are present (Engle's ARCH test), specify GARCH(1,1) or EGARCH model.
4. In-Sample Diagnostic Checks: Ljung-Box Q-test for residual autocorrelation and Jarque-Bera normality test.
Recommended Models:
DeepSeek-R1Claude 3.7 Sonnet
trihex-vLicense: TRIHEX-PROPRIETARY-FREE