garchSim               package:fGarch               R Documentation

_U_n_i_v_a_r_i_a_t_e _G_A_R_C_H _T_i_m_e _S_e_r_i_e_s _S_i_m_u_l_a_t_i_o_n

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

     Simulates an univariate GARCH time series model.

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

     garchSim(model = list(omega = 1.0e-6, alpha = 0.1, beta = 0.8), n = 100, 
         n.start = 100, presample = NULL, cond.dist = c("rnorm", "rged", "rstd", 
         "rsnorm", "rsged", "rsstd"), rseed = NULL)

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

cond.dist: a character string naming the desired conditional
          distribution. Valid values are '"dnorm"', '"dged"', '"dstd"',
           '"dsnorm"', '"dsged"', '"dsstd"'. The default value  is the
          normal distribution. 

   model: a list of GARCH model parameters: 
           'omega' - the constant coefficient of the variance equation,
          by default 1e-6; 
           'alpha' - the value or vector of autoregressive
          coefficients,  by default 0.1, specifying a model of order 1; 
           'beta' - the value or vector of variance coefficients, by
          default 0.8, specifying a model of order 1;  
           The optional values for the linear part are: 
           'mu' - the mean value, by default 0; 
           'ar' - the autoregressive ARMA coefficients, by default 0; 
           'ma' - the moving average ARMA coefficients, by default 0.  
           The optional parameters for the conditional distributions
          are:
           'skew' - the skewness parameter (also named xi), by default
          0.9, effective only for the '"dsnorm"', the '"dsged"', and
          the '"dsstd"' skewed conditional distributions; 
           'shape' = the shape parameter (also named nu), by default 2 
          for the '"dged"' and '"dsged"', and by default 4 for the
          '"dstd"' and '"dsstd"' conditional distributions.

           Note, the default model specifies Bollerslev's GARCH(1,1)
          model with normal distributed innovations. 

       n: length of output series, an integer value. An integer value,
          by default 'n=100'. 

 n.start: length of "burn-in" period, by default 100. 

presample: a numeric three column matrix with start values for the
          series,  for the innovations, and for the conditional
          variances. For an  ARMA(m,n)-GARCH(p,q) process the number of
          rows must be at least  max(m,n,p,q), longer presamples are
          cutted. 

   rseed: single integer argument, the seed for the intitialization of
          the random number generator for the innovations. 

_V_a_l_u_e:

     returns an objects of class 'ts' atrributed with an appropriate
     specification structure as returned by the function 'garchSpec'.

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

     Diethelm Wuertz for the Rmetrics R-port.

_E_x_a_m_p_l_e_s:

     ## garchSpec -
        spec = garchSpec()
        spec

     ## garchSim -
        x = garchSim(model = spec@model, n = 500)
        head(x) 

