GJR模型

Glosten-Jagannathan-Runkle Garch型号用于波动率集群

If negative shocks contribute more to volatility than positive shocks, then you can model the innovations process using a GJR model and include leverage effects. For details on how to model volatility clustering using a GJR model, seeGJR.

Apps

Econometric Modeler

分析和模型计量经济学时间序列

Functions

expand all

Create Model

GJR GJR conditional variance time series model

Fit Model to Data

`estimate`	将条件差异模型拟合到数据
`推断`	推论条件差异模型的条件差异
`总结`	Display estimation results of conditional variance model

Generate Monte Carlo Simulations

`simulate`	Monte Carlo simulation of conditional variance models
`筛选`	Filter disturbances through conditional variance model

Generate Minimum Mean Square Error Forecasts

forecast 预测条件方差模型的条件差异

示例以及如何

Create Model

Specify GJR Models

Create GJR models usingGJR或计量经济学建模应用程序。

Modify Properties of Conditional Variance Models

改变properti修改模型es using dot notation.

指定条件差异模型创新分布

Specify Gaussian or t distributed innovations process.

指定汇率的条件差异模型

为每日Deutschmark/英镑外汇率创建有条件的差异模型。

Specify Conditional Mean and Variance Models

Create a composite conditional mean and variance model.

Fit Model to Data

Compare Conditional Variance Model Fit Statistics Using Econometric Modeler App

交互式指定并将GARCH，EGARCH和GJR模型拟合到数据。然后，通过比较拟合统计信息来确定最适合数据的模型。

Likelihood Ratio Test for Conditional Variance Models

将两个竞争性的条件差异模型拟合到数据，然后使用似然比测试比较其拟合。

Estimate Conditional Mean and Variance Model

Estimate a composite conditional mean and variance model.

Perform GARCH Model Residual Diagnostics Using Econometric Modeler App

Interactively evaluate model assumptions after fitting data to a GARCH model by performing residual diagnostics.

推断条件差异和残差

Infer conditional variances from a fitted conditional variance model.

Share Results of Econometric Modeler App Session

导出变量到MATLAB^®Workspace, generate plain text and live functions that return a model estimated in an app session, or generate a report recording your activities on time series and estimated models in an Econometric Modeler app session.

Using Extreme Value Theory and Copulas to Evaluate Market Risk

此示例显示了如何使用学生的T Copula和极值理论（EVT）使用Monte Carlo模拟技术来模拟假设的全球股权指数投资组合的市场风险。