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Stochastic Models
Stochastic Learning StudioBeta
1.1Symmetric Random Walk1.2Rescaled Random Walk1.3Standard deviation1.4Central Limit Theorem2.1Defining the Wiener process2.2Increment explorer2.3Joint distributions and covariance3.1Running maximum and minimum3.2Reflection principle3.3First passage times3.4Hitting probabilities
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Curriculum/Chapter 2 · Brownian Motion Fundamentals/2.2
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2.2

Increment explorer

What do we know about how Brownian motion changes over an arbitrary window?

Goal: verify experimentally that W(t) − W(s) ~ N(0, t − s), and that only the window's length matters, not its position.

Simulation controls

Time window [s, t]Also adjustable on the chart: drag the shaded window or its edges
0.30
0.050.95
0.70
0.11
400
503000
7
19999

Increment W(t) − W(s)

Empirical mean
-0.014
Theoretical mean
0.000
Empirical variance
0.434
Theoretical variance t − s
0.400

Try this

  1. Start the window slide: does the fan change while the window travels? (Stationary increments.)
  2. Halve the window. Predict first: does the spread halve, or shrink by 1/√2?
  3. Follow the coloured paths: does where a path was before s tell you where it goes inside the window?
Paths and the selected window

Drag the shaded window to slide it, its edges to resize. The coloured paths are emphasised inside the window; the thick bar at t is the increment W(t) − W(s) itself.

Every window restarted at zero
t − s = 0.40 · sd √(t − s) = 0.632
  • ±√u
  • Empirical density
  • N(0, t − s)

Each path's segment inside the window is shifted to start at 0. The fan's width depends only on the elapsed time u (±√u); at its end, the histogram of increments sits beside the N(0, t − s) density.