fxlm                package:fxregime                R Documentation

_E_x_c_h_a_n_g_e _R_a_t_e _R_e_g_r_e_s_s_i_o_n

_D_e_s_c_r_i_p_t_i_o_n:

     Interface to 'lm' for fitting exchange rate regression models
     (Frankel-Wei models).

_U_s_a_g_e:

       fxlm(formula, data, ...)

_A_r_g_u_m_e_n_t_s:

 formula: a '"formula"' describing the linear model to be fit. For
          details see below.

    data: a '"zoo"' time series.

     ...: arguments passed to 'lm'.

_D_e_t_a_i_l_s:

     'fxlm' is a function for fitting exchange rate regression models
     also known as Frankel-Wei models. It is a simple convenience
     interface to 'lm': 'data' is assumed to be a '"zoo"' series in
     which, by default, the first column is the dependent variable. If
     'formula' is omitted, the first column is regressed on the
     remaining columns in 'data'. The main difference compared to plain
     'lm' models is that the error variance is reported as a full
     parameter (estimated by maximum likelihood) in the 'coef' method
     and the 'estfun' method (but currently not in the 'vcov' method). 
     Furthermore, the index (also known as the time stamps) of the
     underlying data set can be extracted by the 'time'/'index' method.

_V_a_l_u_e:

     An object of class '"fxlm"' inheriting from '"lm"'.

_R_e_f_e_r_e_n_c_e_s:

     Shah A., Zeileis A., Patnaik I. (2005), What is the New Chinese
     Currency Regime?, Report 23, Department of Statistics and
     Mathematics, Wirtschaftsuniversitaet Wien, Research Report Series,
     November 2005.

     Zeileis A., Shah A., Patnaik I. (2008), Testing, Monitoring, and
     Dating Structural Changes in Maximum Likelihood Models, Report 70,
     Department of Statistics and Mathematics, Wirtschaftsuniversitaet
     Wien, Research Report Series, August 2008.

_S_e_e _A_l_s_o:

     'lm', 'fxregimes'

_E_x_a_m_p_l_e_s:

     ## load package and data
     library("fxregime")
     data("FXRatesCHF", package = "fxregime")

     ## compute returns for CNY (and explanatory currencies)
     ## for one year after abolishing fixed USD regime
     cny <- fxreturns("CNY", frequency = "daily",
       start = as.Date("2005-07-25"), end = as.Date("2006-07-24"),
       other = c("USD", "JPY", "EUR", "GBP"))

     ## estimate full-sample exchange rate regression
     fm <- fxlm(CNY ~ USD + JPY + EUR + GBP, data = cny)
     coef(fm)
     summary(fm)

     ## test parameter stability (with double max test)
     scus <- gefp(fm, fit = NULL)
     plot(scus, aggregate = FALSE)
     ## which shows a clear increase in the variance in March 2006

     ## alternative tests: Andrews' supLM ...
     plot(scus, functional = supLM(0.1))
     ## ... or Nyblom-Hansen test (Cramer-von Mises type test)
     plot(scus, functional = meanL2BB)

