Markov Chains

  • By Admin
  • November 5, 2014
  • Comments Off on Markov Chains

Theory
A Markov chain exists when the probability of a future state depends on a previous state and when linked together forms a chain that reverts to a long-run steady state level. This Markov approach is typically used to forecast the market share of two competitors. The required inputs are the starting probability of a customer in the first store (the first state) returning to the same store in the next period versus the probability of switching to a competitor’s store in the next state.

Procedure

  • Start Excel and select Risk Simulator | Forecasting | Markov Chain.
  • Enter the required input assumptions (see Figure 1 for an example) and click OK to run the model and report.

    • Note
    Set both probabilities to 10% and rerun the Markov chain, and you will see the effects of
    switching behaviors very clearly in the resulting chart as shown at the bottom of Figure 1.

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