Monte Carlo Price Path Simulation from Historical Returns

Summary

This indicator simulates possible future price paths from the latest bar using historical return estimates. It calculates returns over a configurable candle step, estimates their mean and standard deviation over a selected lookback, and uses random draws transformed into approximately normal shocks. Each shock shifts and scales the estimated return distribution; paths then update price multiplicatively. The indicator draws multiple scenarios and tracks the highest and lowest prices reached across them as potential uncertainty envelopes.

Users can adjust the number of paths, forecast horizon, lookback window, and return step size. The document explains that a full-history window can blend market regimes, a shorter rolling window can reflect recent conditions, longer horizons widen dispersion, and more paths or longer horizons increase rendering load. The output is a scenario visualization, not a forecast or backtest. The random generator is unseeded, so results change on refresh; normal shocks are unbounded, and the method assumes historical mean and volatility are informative for future returns. It supplies no performance evaluation.

Key ideas

• The simulator estimates drift and volatility from historical returns over a configurable window.
• It generates multiple random paths by scaling approximate normal shocks and compounding returns multiplicatively.
• The reported upper and lower envelopes are extremes across simulated paths, not probability bounds.
• Lookback length, step size, path count, and horizon affect the simulation and its rendering cost.
• Unseeded randomness and unbounded shocks make runs variable and can produce large outliers.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.