Markov chains are mathematical systems that hop from one “state” (a situation or set of values) to another. Also a sequence of possible events in which the probability of each event depends only on the state attained in the previous event. The state space, or set of all possible states, can be anything: letters, numbers, weather conditions, baseball scores, or stock performances. Markov chains may be modeled by finite state machines, and random walks provide a prolific example of their usefulness in mathematics and are used in quality SEO services.
In this model, we have made a prediction of apple stocks whether it will go up or down.
Fetching the apple data:
Getting the stock returns:
Sequential daily return:
Using markov chain to get the transition state:
Ploting the output: