Library / Dynamics / Random Walk & Markets

Random Walk & Markets

Unpredictable steps accumulate; efficient markets leave mostly randomness behind.

drift?
spread ∝ √time · recreated schematic
INTERACTIVE LAB

Tolerance sandbox (original recreation)

happy 76% • avg. similar neighbors 49% • red ring = wants to move

DYNAMICS

When to use / misuse

Use → Separate skill from luck before forecasting.

Difficulty → Core

REDCAPE → Reason · Predict

agent: random-walk-checker
family: Dynamics
combine_with: [two other families]
rule: state failure mode before acting

Free sources: SFI Random Walks tutorial • Coursera M9

← LibrarySee Playbook →
◍ Ask mentor about this →See REDCAPE playbook →

Attach to a lattice — combines with

Different families, shared jobs. Click to open alongside.

LINEAR
Categorical & Threshold Models
Buckets and cutoffs turn messy attributes into testable if-then rules.
SHARED JOBS: REASON · PREDICT
LINEAR
Linear Regression
Best-fit line plus a causation audit. A big coefficient is not a big cause.
SHARED JOBS: REASON · PREDICT
DISTRIBUTIONS
Normal Distribution
Bell-curve averaging: many small independent effects sum to a predictable center with thin tails.
SHARED JOBS: REASON · PREDICT

More in Dynamics

Markov Chain
Next state depends only on now. Run it forward to get the long-run mix.
Polya Urn / Path Dependence
Early draws rewrite the odds — history locks in QWERTYs, VHSs and dominant cities.
Lyapunov / Equilibrium
An energy-like function proves a system settles down — and bounds how fast.
← Cellular Automata & Game of LifeMarkov Chain →