garchOxModelling           package:fSeries           R Documentation

_R _I_n_t_e_r_f_a_c_e _f_o_r _G_a_r_c_h _O_x

_D_e_s_c_r_i_p_t_i_o_n:

     A collection and description of functions to  fit the parameters
     of an univariate time  series to GARCH models interfacing the
     GARCH OX Package.  

     The family of GARCH time series models includes the following 
     processes:

       1  garch   generalized AR conditional heteroskedastic models,
       2  egarch  exponential GARCH models,
       3  aparch  asymmetretic power ARCH models.

_U_s_a_g_e:

     garchOxFit(formula.mean = ~ arma(0, 0), formula.var = ~ garch(1, 1), 
             series = x, cond.dist = c("gaussian", "t", "ged", "skewed-t"), 
             include.mean = TRUE, truncation = 100, trace = TRUE, title = NULL,
             description = NULL)
             
     ## S3 method for class 'garchOx':
     print(x, digits, ...)
     ## S3 method for class 'garchOx':
     summary(object, ...)
     ## S3 method for class 'garchOx':
     plot(x, ...)

_A_r_g_u_m_e_n_t_s:

cond.dist: a character string describing the distribution of
          innovations.  By default the optimization is based on
          gaussian log likelihood  parameter optimization denoted by
          "gaussian". Alternatively, a  Student-t "t", a generalized
          error "sged", or a skewed Student-t "skewed-t" can be chosen. 

description: a character string which allows for a brief description. 

  digits: the number of digits to be printed. 

formula.mean: formula object which specifies the mean. AR and MA models
          can be specified as ARMA(0,q) and ARMA(p,0) respectively. 

formula.var: formula object which specifies the variance. Use
          '~garch(p,q)' to specify GARCH(p,q) models, ... 

include.mean: should the mean be included? By default TRUE. 

  object: an object of class 'garchOx' as returned from the function
          code{garchOxFit}. 

  series: the series to be modeled. 

   title: a character string which allows for a project title. 

   trace: a logical. Trace optimizer output? By default TRUE. 

truncation: number of truncation points. 

       x: an object of class 'garchOx' as returned from the function
          code{garchOxFit}. 

     ...: additional arguments to be passed to the 'print',  'summary',
          and 'plot' methods. 

_D_e_t_a_i_l_s:

     *Ox Interface:* 
           The function 'garchOxFit' interfaces a subset of the
     functionality  of the G@ARCH 4.0 Package written in Ox.  G@RCH 4.0
     is one of the most sophisticated packages for modelling 
     univariate GARCH processes including GARCH, EGARCH, GJR, APARCH, 
     IGARCH, FIGARCH, FIEGARCH, FIAPARCH and HYGARCH models. Parameters
     can be estimated by approximate (Quasi-) maximum likelihood
     methods under four assumptions: normal, Student-t, GED or skewed
     Student-t  errors. 

     *About Ox:* 
      "Ox" is an object-oriented matrix language with a comprehensive 
     mathematical and statistical function library. Many packages were 
     written for Ox including software mainly for econometric
     modelling.  The Ox packages for time series analysis and
     forecasting, Arfima, Garch and State Space Modelling are
     especially worth to note.  Since most of the R-users wan't to
     change to another Statistical  Computing environment, we made
     selected parts of the G@RCH OX software  available for them
     through an R-Interface. What you have to do, is  to check the "Ox
     citation and copyright" rules and if you agree and  fullfill the
     conditions, then download the OxConsole Software  together with
     the "OxGarch" Package, currently G@RCH 4.0. If you are  not
     qualified for a free license, order your copy from Timberlake 
     Consultants. We recommend to install the "Setup.exe" under the
     path  "C:\Ox\" and to unzip the OxGarch Package in the directory 
     "C:\Ox\Packages".  

     *Installation of the Interface:* In addition you have to copy the
     file "GarchOxModelling.ox" from  the "fSeries/data/" directory to
     the Ox library directory  "C:\Ox\lib". 

     *Ox Citation and Copyright Rules:* 
      Ox and all its components are copyright of Jurgen A. Doornik. The
      Console (command line) versions may be used freely for academic 
     research and teaching purposes only. Commercial users and others 
     who do not qualify for the free version must purchase the Windows 
     version of Ox and GiveWin with documentation, regardless of which 
     version they use (so even when only using Ox on Linux or Unix). 
     Ox should be cited whenever it is used. Refer to the two
     references  given below. Note, failure to cite the use of Ox in
     published work  may result in loss of the right to use the free
     version, and an  invoice at the full commercial price. Ox is
     available from Timberlake  Consultants. The Ox syntax is public,
     and you may do with your own  Ox code whatever you wish. 

     *Work to do:* 
      Note, only a small part of the functionalities are interfaced
     until now to R. But, principally it would be possible to interface
     also other functionalities offered by the Ox Garch Package.

_A_u_t_h_o_r(_s):

     Jurgen Doormik for the Ox Environment, 
       NN for the Ox Garch package, and 
      Diethelm Wuertz for R's Ox Garch interface.

_R_e_f_e_r_e_n_c_e_s:

     Doornik, J.A. (2002),  Object-Oriented Matrix Programming Using
     Ox,  London, 3rd ed.: Timberlake Consultants Press and Oxford: 
     www.nuff.ox.ac.uk/Users/Doornik. 

     Doornik, J.A. and Ooms, M. (1999),  A Package for Estimating,
     Forecasting and Simulating Arfima Models,  Oxford:
     www.nuff.ox.ac.uk/Users/Doornik.

_S_e_e _A_l_s_o:

     'garchModelling', and 'garch' from R's tseries package.

