Using Random Trade Simulations to Interpret Strategy Metrics and Risk
Summary
The article presents a spreadsheet sandbox that simulates random trades and displays common MetaTrader performance measures, including profit factor, relative drawdown, return, and winning or losing streaks. Users can vary starting capital, stop and take-profit distances, spread, lot sizing, and the fraction of capital risked per trade. The examples compare fixed position size with position sizes that compound as account equity changes.
A central lesson is that win rate depends on the stop-to-target relationship and trading costs: spread can make apparently symmetric price barriers produce an unfavorable payoff. The simulations also illustrate how increasing the percentage risked per trade can magnify drawdowns and the chance of account failure, even when potential gains rise. The article recommends comparing a strategy with random trading under similar trade management as a rough control. These are simplified illustrations, not market evidence: they assume fixed spread, one open position, fixed stop logic, and random outcomes, and depend on spreadsheet random-number quality. Actual strategies and market behavior may differ.
Key ideas
- Win rate is meaningful only alongside the reward-to-risk setup and trading costs.
- Spread can skew the odds even when stop and target distances appear equal.
- Compounding position size amplifies both gains and losses, while higher risk can increase drawdown and failure likelihood.
- Random trading can remain profitable over a limited run, so short samples may mislead strategy evaluation.
- The spreadsheet is a simplified exploration tool rather than a realistic model of every market or trading system.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.