Fitting Markov Switching Models to data in R

Question

I'm trying to fit two kinds of Markov Switching Models to a time series of log-returns using the package MSwM in R. The models I'm considering are a regression model with only an intercept, and an AR(1) model. Here is the code I'm using:

library(tseries)

#Prices
ftse<-get.hist.quote(instrument="^FTSE", start="1984-01-03", end="2014-01-01", quote="AdjClose", compression="m")

#Log-returns
ftse.ret<-diff(log(ftse))

library(MSwM)

#Model with only intercept
mod<-lm(ftse.ret ~ 1)

#Fit regime-switching model
msmFit(mod, k=2, sw=c(T,T), p=0, data=ftse.ret)

#AR(1) model
mod<-lm(ftse.ret[2:360] ~ ftse.ret[1:359])

#Fit regime-switching model
msmFit(mod, k=2, sw=c(T,T,T), p=1, data=ftse.ret)

In both cases the function msmFit doesn't work. Here is the error message I get:

Error in (function (classes, fdef, mtable)  : 
  unable to find an inherited method for function ‘msmFit’ for signature ‘"lm", "numeric", "logical", "numeric", "zoo", "missing"’

I don't know why I get this error message, since I'm using as first argument of the function msmFit a lm object and this is a suitable class for the argument of the function.

Answer 1

You have an unnecessary argument as you pass data to msmFit, which is not necessary. The data is already contained in mod. The following code runs for me:

library(tseries)

#Prices
ftse<-get.hist.quote(instrument="^FTSE", start="1984-01-03", end="2014-01-01", quote="AdjClose",     compression="m")

#Log-returns
ftse.ret<-diff(log(ftse))

library(MSwM)

#Model with only intercept
mod<-lm(ftse.ret ~ 1)

#Fit regime-switching model
mod.mswm=msmFit(mod, k=2, sw=c(T,T), p=0)
plot(mod.mswm)