volatility-methods          package:fGarch          R Documentation

_E_x_t_r_a_c_t _G_A_R_C_H _M_o_d_e_l _V_o_l_a_t_i_l_i_t_y

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

     Extracts volatility from a fitted GARCH object.

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

     ## S3 method for class 'fGARCH':
     volatility(object, type = c("sigma", "h"), ...)

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

  object: an object of class 'fGARCH' as returned from the function
          'garchFit()'. 

    type: a character string denoting if the conditional standard
          deviations '"sigma"' or the variances '"h"' should  be
          returned. 

     ...: additional arguments to be passed. 

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

     The function extracts the '@volatility' from the slots '@sigma.t'
     or '@h.t' of an object of class '"fGARCH"'  as returned by the
     function 'garchFit'.

     The class of the returned value depends on the input to the
     function 'garchFit' who created the object. The returned value is
     always of the same class as the input object to the argument
     'data' in the function 'garchFit', i.e. if you fit a
     '"timeSeries"' object, you will get back from  the function
     'fitted' also a '"timeSeries"' object,  if you fit an object of
     class '"zoo"', you will get back  again a '"zoo"' object. The same
     holds for a '"numeric"' vector, for a '"data.frame"', and for
     objects of class '"ts", "mts"'.

     In contrast, the slot itself returns independent of the class  of
     the data input always a numceric vector, i.e. the function  call
     r'slot(object, "fitted")' will return a numeric vector.

_M_e_t_h_o_d_s:



     _o_b_j_e_c_t = "_A_N_Y" Generic function.

     _o_b_j_e_c_t = "_f_G_A_R_C_H" Extractor function for volatility or standard
          deviation from  an object of class '"fGARCH"'.


_N_o_t_e:

     'volatility' is a generic function which extracts volatility
     values  from objects returned by modeling functions.

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

     Diethelm Wuertz for the Rmetrics R-port.

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

     ## Swiss Pension func Index -
        x = as.timeSeries(data(LPP2005REC))
       
     ## garchFit
        fit = garchFit(LPP40 ~ garch(1, 1), data = 100*x, trace = FALSE)
        fit
        
     ## volatility - 
        # Standard Deviation:
        volatility = volatility(fit, type = "sigma")
        head(volatility)
        class(volatility)
        # Variance:
        volatility = volatility(fit, type = "h")
        head(volatility)
        class(volatility)
        
     ## slot - 
        volatility = slot(fit, "sigma.t")
        head(volatility)
        class(volatility)
        volatility = slot(fit, "h.t")
        head(volatility)
        class(volatility)

