GARCH Overview
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Introduces GARCH and the characteristics of GARCH models that are commonly associated with financial time series.
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GARCH Toolbox Overview
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Discusses allowable models for describing conditional mean and variance to the GARCH Toolbox and presents the default model that is used as the basis of discussion in this manual.
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Analysis and Estimation Example Using the Default Model
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The example in this section uses the GARCH Toolbox default model to examine the equity series of a hypothetical company.
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The GARCH Specification Structure
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Explains the purpose and contents of the specification structure, as well as how to use it for estimation, simulation, and forecasting.
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Simulation
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Shows you how to simulate sample paths for return series, innovations, and conditional standard deviation processes. It also examine transient effects in the simulation process.
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Forecasting
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Uses the estimated default model and the same hypothetical company to demonstrate the use of forecasting.
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Conditional Mean Models with Regression Components
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Discusses the incorporation of a regression component in an estimation, and its use in simulation, inference, and forecasting.
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Model Selection and Analysis
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Explains the use of likelihood ratio tests and Akaike and Bayesian criteria for model selection. It also discusses the setting of equality constraints as a way of assessing parameter significance, and the effect of equality constraints on initial parameter estimates.
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Recommendations and Suggestions
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Provides general recommendations to make it easier for you to use the GARCH Toolbox
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