Markov chain · daily direction model
Add a ticker. See its up · down · flat rhythm.
Enter one or more symbols. We pull six months of daily closes, classify each day as up, down, or flat, build a transition matrix, and simulate the next ten trading days.
What is a Markov chain?
A Markov chain is a simple model of state-to-state transitions: the probability of the next state depends only on the current state, not on the full past. Here, each trading day is one of three states based on its percent change versus the prior close:
- Up change > +0.5%
- Flat change within ±0.5%
- Down change < −0.5%
From the historical sequence of states we count how often each state follows each other state, then normalize the rows to get a transition matrix. Starting from the latest day, we sample forward ten steps using a seeded pseudo-random draw, so results are reproducible.
Educational only. This is a toy statistical exercise, not investment advice. Real markets are not Markovian.
Enter a ticker above to build its Markov chain.