Performance & Backtests
How performance data is generated, interpreted, and limited when evaluating breakout strategies.
Performance is context, not proof
Why results must be interpreted carefully
Performance data can provide insight, but it is not proof of future outcomes.
Market conditions change. Execution varies. Risk settings differ. Because of this, performance should be viewed as illustrative, not predictive.
This page explains how backtests and performance examples are produced and, just as importantly, what they cannot tell you.
What backtests can show
Understanding historical behavior
Backtests are simulations run on historical price data using predefined rules.
They can help illustrate:
- how a strategy behaved in past market conditions
- trade frequency and distribution
- periods of drawdown and recovery
Backtests are useful for understanding behavior, not for forecasting results.
What backtests cannot show
Important limitations
Backtests cannot accurately account for:
- real-time slippage
- spread variation during volatility
- broker execution differences
- psychological factors
As a result, live trading outcomes will always differ from backtested results, sometimes significantly.
Methodology used
How tests are conducted
When backtests are presented, they are conducted using:
- fixed, rule-based strategy logic
- historical price data available at the time
- predefined risk parameters
No optimization is performed to “fit” results to specific periods. Strategy rules remain unchanged across tests.
Risk settings matter more than strategy
Why results vary
Two traders using the same strategy can experience very different results.
Differences arise from:
- risk per trade
- position sizing
- markets traded
- execution conditions
Risk configuration has a larger impact on outcomes than most traders expect.
Live trading vs testing
Reality introduces friction
Live trading includes factors that simulations cannot fully replicate:
- delayed execution
- partial fills
- market gaps
- emotional decision-making
For this reason, testing results should never be treated as a guarantee of live performance.
Transparency over marketing
What we choose not to show
Lanami avoids:
- isolated “best period” performance examples
- exaggerated win-rate claims
- hypothetical profit projections
The goal is to set realistic expectations and allow traders to evaluate tools responsibly.
How to evaluate performance responsibly
Better questions to ask
When reviewing performance data, consider:
- how drawdowns are handled
- whether risk is capped
- how the strategy behaves in different conditions
Consistency and risk control matter more than short-term returns.
Review the rules and logic behind the strategy before evaluating performance.
Explore indicators and Expert Advisors that apply the breakout framework.
Important information about trading risk and limitations.
Performance FAQs
Common questions about results and testing
Do backtests guarantee future results?+–
No. Backtests illustrate historical behavior only. Market conditions and execution vary over time.
Why don’t you show equity curves?+–
Equity curves can be misleading when presented without full context. We focus on methodology and risk considerations instead.
Can I expect the same results shown in examples?+–
No. Results depend on risk settings, execution, and market conditions. Individual outcomes will differ.
Are results optimized?+–
No. Strategy rules are fixed and not optimized to fit specific historical periods.
Should I test strategies myself?+–
Yes. Demo testing helps you understand behavior and configuration before trading live.
Understand the risks before trading
Performance examples are educational, not promises. Review the risk disclaimer to ensure you understand the limitations before using any trading tools