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G@RCH ™ v7.0
G@RCH版,是一套OxMetricsTM应用程序,专著于评估和预测单变量ARCH类型模型.G@RCH 提供用户友好的界面(带有滚动菜单),同时叶提供一些图形特征(通过OxMetrics图形接口).
对于重复性的任务,模型能够通过OxMetrics的’批处理编辑器’或Ox的编程语言(提供了好几个使用G@RCH类的示例文件)来评估.G@RCH同样也是OxMetrics企业版■的一部分.
G@RCH is an OxMetrics module dedicated to the estimation and forecast of univariate and multivariate ARCH-type models. It also allows the estimation of univariate and multivariate non-parametric estimators of the quadratic variation and the integrated volatility. G@RCH provides a menu-driven easy-to-use interface, as well as some graphical features. For repeating tasks, the models can be estimated via the Batch Editor of OxMetrics or using the Ox language together with the ‘Garch’, ‘MGarch’ and ‘Realized’ classes. Version 7.0 is a major update that features many improvements. G@RCH is also part of OxMetrics Enterprise Edition.
New features in G@RCH 7
Version 7.0 is a major upgrade of G@RCH and includes the following new features:
Four univariate models of the class of Generalized Autoregressive Score (GAS) models proposed by Harvey and Chakravarty (2008) and Creal, Koopman, and Lucas (2012) have been added, i.e. the GAS, Asymmetric GAS, Exponential GAS, and Asymmetric Exponential GAS models with a Normal, Student-t, GED and Skewed-Student distribution. See GAS Models ?
New procedures have been added to simulate the above mentioned GAS models.
The Spline-GARCH and Spline-GJRmodels of Engle and Rangel (2008) have been added to G@RCH. The estimated spline can be plotted and stored in the datafile. See Spline-GARCH Models ?
A new procedure to simulate the Spline-GARCH of Engle and Rangel (2008) is also available in the garch class. An illustration is given in Simul_Spline_Garch.ox.
The path of the garch and mgarch packages have been changed. They moved from packagesGarch6 and packagesMGarch1 to packagesGarch and packagesMGarch respectively.
Bug corrected for univariate GARCH forecasts with variance targeting.
New functions have been added to the the garch class to get the conditional mean, conditional variance and the spline. See Get_cond_mean(), Get_cond_var() and Get_spline(); An example is provided in GarchEstim_Spline.ox.
TestGraphicAnalysis(). Two additional arguments to plot ?σt and ?τt.
Thanks to Luc Bauwens: The name of the graphs generated via the options in the rolling menus contains an incremental index, e.g. ‘G@RCH Forecasting (1)’. This avoids overwriting graphs that have not been saved.
A new procedure to simulate a multivariate Riskmetrics model is available in the mgarch class. See Simul_RiskMetrics().
A new example of ox code is provided to compute and print h-step-ahead forecasts of the Value-at-Risk. An option ‘reestimate_every’ is given to chose the number of observations for which the parameters of the model are kept constant. The model is re-estimated every ‘reestimate_every’ observations. See VaR_outofsample_h_steps.ox.
New function Get_Info_Criteria() in the garch class. It returns a vector containing the 4 information criteria.
New tool to convert a date of the format yyyymmdd, yyyyddmm, ddmmyyyy or mmddyyyy into a proper OxMetrics format. This option is available in Category ‘Other Models’ and Model Class ‘Convert Date using G@RCH’ or by calling the function Convert_Date(const vDate, const type) of the garch class.
G@RCH 7.0 proposes a new test for detecting big Poisson jumps at an intradaily frequency. This test, proposed by Lee and Hannig (2010), is an extension of the one of Lee and Mykland (2008), that is robust to infinite activity jumps (i.e. Levy jumps).
Supported Platforms
G@RCH 7 supports the latests versions of Microsoft Windows, Mac OS and Linux. See below to see if your machine is compliant with the latest version:
Microsoft Windows:
Windows 8, 7, Vista, XP, 2000 (32-bit)
Windows 8, 7, Vista (64-bit)
Mac OS:
OS X 10.4 (Tiger)
OS X 10.5 (Leopard)
OS X 10.6 (Snow Leopard)
OS X 10.7 (Lion)
OS X 10.8 (Mountain Lion)
Linux:
32-bit
64-bit
