G@RCH 2.0: An Ox Package for Estimating and Forecasting Various ARCH Models
AbstractThis paper discusses and documents G@RCH 2.0, an Ox package dedicated to the estimation and forecasting of various univariate ARCH-type models including the GARCH, EGARCH, GJR, APARCH, IGARCH, FIGARCH, FIEGARCH and FIAPARCH specifications of the conditional variance and an AR(FI)MA specification of the conditional mean. These models can be estimated by approximate (quasi-) maximum likelihood under four assumptions: normal, Student-t, GED, or skewed Student errors. Explanatory variables can enter both the conditional-mean and the conditional-variance equations. One-step-ahead (density) forecasts of both the conditional mean and variance are available as well as some misspecification tests and several graphical techniques.
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Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 2001 with number 123.
Date of creation: 01 Apr 2001
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(Density-) Forecasts; GARCH; Asymmetry; Long Memory; Ox; Econometric Software; Financial Time Series;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
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- NEP-ALL-2001-05-02 (All new papers)
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