Monte Carlo Expected Move Distribution

The Monte Carlo Expected Move Distribution swaps the single forecast line for an ensemble of Monte Carlo price paths: up to 500 Geometric Brownian Motion simulations, seeded by historical log-volatility and an optional drift component, condensed into a vertical histogram at the end of your projection horizon. The result is an options-style expected move drawn on the chart: median, one-standard-deviation range, and improbable tails.

How to Trade the Monte Carlo Expected Move Distribution?

• Median outcome (50th percentile): the statistically balanced reference given current volatility and drift.
• Colored 1-SD zone (16th–84th percentile): roughly 68% of simulated outcomes land here — home turf for conservative targets.
• Gray tails: aggressive objectives with correspondingly low odds inside the window.
• Early ±1 SD touches: reaching a dashed expected-move line early flags statistical overextension — context for mean reversion and trade management.
• Volatility-aware stops: the lower expected move can guide long-trade stops, while the upper line serves shorts as an invalidation level.

Match Projection Length to your holding period — a few bars for scalps, tens for swings — and enable drift only when you expect momentum to persist. The construction shares its geometry with probability cones, rendered as a full distribution.

Monte Carlo Expected Move Distribution Settings

• Simulations (50–500): more paths produce smoother, more stable distributions.
• Projection Length: forward bars used to compute the expected move.
• Volatility Lookback: window for measuring historical log-return volatility.
• Include Trend (Drift): adds directional bias; disable for a mean-neutral random walk.
• Price Bins / Max Distribution Width: vertical resolution and on-chart footprint of the histogram.

Frequently Asked Questions

What exactly is the expected move here?

The band between the 16th and 84th percentiles of all simulated outcomes — the one-standard-deviation range that contains about 68% of cases under a normal distribution. It is a volatility statement, not a directional call.

How does it differ from the Monte Carlo Mean Reversion Heatmap?

The Monte Carlo Mean Reversion Heatmap scores the odds of price returning to a moving average; this indicator maps the entire forward range instead, which makes it the better fit for target-setting and range planning.

How do I access the Monte Carlo Expected Move Distribution?

The indicator is free from the LuxAlgo Library, and its page lets you run and backtest it in Quant, LuxAlgo's AI.