Markov Analyzer

Assess next-week probabilities, expected run length, and reward stats (horizon: k=2 weeks).

How the Markov model works here

A Markov Chain simplifies weekly price action into states—Down, Neutral, Up—and learns the probability of moving from one to the next. It’s “memoryless”: the next step depends on the current state, not distant history.

We present: Prob. Up Next Week (one-week transition), Prob. Up ≤ k (at least one Up in the next k weeks), Expected Run (typical state duration), and Reward Stats (average weekly returns by state/transition).

Higher Up probabilities / longer Up runs = constructive. Persistent negative rewards or Down bias = caution. Educational only – not financial advice.

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Select a ticker to view Markov screener data.

We’ll show next-week probabilities, expected run length, P20/P80, and reward stats for 2 weeks.

Reading the metrics

Prob. Up Next Week — one-step transition. Higher values are constructive.
Prob. Up ≤ k — chance of at least one Up in the next k weeks.
Expected Run — typical duration of current state; longer Up runs support trends.
P20 / P80 — typical weekly range for risk sizing.
Reward Stats — average weekly returns by state/transition; negatives flag caution.

Legend

Positive Negative Neutral k = weeks ahead Probabilities Ranges (P20/P80)

Accents appear where metrics indicate strength or risk.