Return.annualized    package:PerformanceAnalytics    R Documentation

_c_a_l_c_u_l_a_t_e _a_n _a_n_n_u_a_l_i_z_e_d _r_e_t_u_r_n _f_o_r _c_o_m_p_a_r_i_n_g _i_n_s_t_r_u_m_e_n_t_s _w_i_t_h _d_i_f_f_e_r_e_n_t _l_e_n_g_t_h _h_i_s_t_o_r_y

_D_e_s_c_r_i_p_t_i_o_n:

     An average annualized return is convenient for comparing returns.

_U_s_a_g_e:

     Return.annualized(R, scale = NA, geometric = TRUE)

_A_r_g_u_m_e_n_t_s:

       R: an xts, vector, matrix, data frame, timeSeries or zoo object
          of asset returns 

   scale: number of periods in a year (daily scale = 252, monthly scale
          = 12, quarterly scale = 4) 

geometric: generate geometric (TRUE) or simple (FALSE) returns, default
          TRUE 

_D_e_t_a_i_l_s:

     Annualized returns are useful for comparing two assets.  To do so,
     you must scale your observations to an annual scale by raising the
     compound return to the number of periods in a year, and taking the
     root to the number of total observations:

                      prod(1 + Ra)^(scale/n) - 1


     where scale is the number of periods in a year, and n is the total
     number of periods for which you have observations.

     For simple returns (geometric=FALSE), the formula is:


                            mean(R)*scale

_V_a_l_u_e:

     annualized return

_A_u_t_h_o_r(_s):

     Peter Carl

_R_e_f_e_r_e_n_c_e_s:

     Bacon, Carl. _Practical Portfolio Performance Measurement and
     Attribution_. Wiley. 2004. p. 6

_S_e_e _A_l_s_o:

     'Return.cumulative',

_E_x_a_m_p_l_e_s:

     data(managers)
     Return.annualized(managers[,1,drop=FALSE])
     Return.annualized(managers[,1:8])
     Return.annualized(managers[,1:8],geometric=FALSE)