The need for the Markov model

Given the range of models we are discussing in this book, is there a need to discuss Markov models? When we speak about forecasting, one of the main inputs is the historical information. This could be in the form of a time series. However, Markov models don't need historical information to be able to forecast. When we build a Markov model, we are interested in the state (value/behavior/phenomenon) of a subject at the present time. We are also interested in the states that the subject can get transitioned to and the transition probabilities involved. A textbook definition of the Markov model would be a stochastic model describing a sequence of possible events in which the probability of each event depends only on the state attained in the previous event. To understand the terms better, let's look at the states that a car being driven may...