Demo trading is useful when entries, stops and outcomes are fixed in advance and settled against real market data. A journal then reveals expectancy, drawdown and behavioural patterns. It cannot reproduce every cost or emotion of live execution.
What to remember
- Record the plan before seeing the outcome.
- Measure in R as well as money.
- Segment by market, style and source.
- Move to live risk gradually, never because of a short winning streak.
What an honest demo should record
A useful demo position inherits server-owned entry, stop and target levels from the saved analysis or setup. It uses a consistent risk rule, starts settlement on later candles and prevents the browser from declaring its own result.
HyperFX demo positions use play money and a fixed risk framework. Position caps reduce hidden correlation and overtrading. Target, stop, breakeven, expired and void remain separate outcomes so neutral cases cannot inflate win rate.
- Source and timestamp
- Market, direction and style
- Entry, stop, targets and 1R
- Opened and closed time
- Outcome, P&L and result in R
Metrics that reveal more than win rate
Expectancy estimates the average R produced per graded trade. Profit factor compares gross winning R with gross losing R. Maximum drawdown describes the deepest decline from a previous equity peak. Each needs an adequate and relevant sample.
Segment results by strategy, market, timeframe and source. A profitable total can hide one weak category subsidised by another. Also track the maximum number of trades per day; performance often deteriorates when activity rises without better opportunities.
- Win rate with sample size
- Average win R and average loss R
- Expectancy and profit factor
- Maximum drawdown
- Results by style, market and source
- Overtrading and rule violations
What demo cannot simulate
A clean demo fill may differ from live execution because of spread, slippage, fees, funding, partial liquidity and platform latency. Real money also changes decision-making: traders move stops, skip valid entries or chase after losses.
Treat stable demo performance as permission for a small, controlled live experiment—not proof that scale is safe. Keep the same journal, lower risk during the transition and compare live slippage with the theoretical plan.
A losing demo is valuable: it exposes a weak process without charging real capital for the lesson.