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