The answer above is for the Markov switching model. If you mean a Markov model and you have time series data with values equally spaced in time , you can consider a pure autoregressive model.
Please specify if you are strictly referring to the Markov model or Markov switching model?
Note:
A Markov model estimates pseudo changing systems or stochastic processes - based on the assumption that future states depend only on the present state, and not on events that occurred before the current state (Markov property).
On the other hand, a Markov switching model falls under the family of regime switching models which are most commonly used to model time series data that fluctuates between recurring 'episodes or states'. In that regard, a Markov switching model assumes that unobserved states are determined by an underlying stochastic process known as a Markov-chain; whereby a Markov-chain is a stochastic process used to describe how uncertain and unobserved outcomes emerge or occur.
Yes EViews yields reliable results but that depends on how you specify your model based on how you would have addressed relevant timeseries properties of your data.