Back-tested results are one of the most valuable tools on AlgoMart—but they are also one of the easiest to misunderstand.
New users often focus on headline returns or recent performance without fully considering risk, structure, and context. This article highlights the most common mistakes users make when reading backtests and explains how to avoid them.
The goal is not to distrust backtests—but to use them correctly.
Mistake 1: Treating backtests as predictions
A backtest shows how a strategy would have behaved historically—not how it will perform in the future.
Common misunderstandings include:
Assuming similar returns will repeat
Treating back-tested allocations as forecasts
Expecting smooth performance paths
Backtests provide context, not guarantees. Markets change, regimes shift, and no model can account for every future condition.
How to avoid it:
Use backtests to understand behaviour across environments—not to predict outcomes.
Mistake 2: Focusing only on returns
High cumulative returns are eye-catching, but they rarely tell the full story.
Many users overlook:
Maximum drawdowns
Volatility during stress periods
Recovery times after losses
A strategy that performs well on paper may still be difficult to hold during real drawdowns.
How to avoid it:
Always review drawdowns, volatility, and downside metrics before looking at cumulative performance.
Mistake 3: Comparing strategies with different benchmarks
Not all strategies are designed to beat the same benchmark.
A growth-oriented strategy and a defensive strategy may both succeed—even if their returns differ significantly.
Problems arise when users:
Compare strategies without checking benchmark composition
Assume higher returns mean “better”
Ignore equity/bond mix differences
How to avoid it:
Compare each strategy relative to its own benchmark, not to other strategies with different objectives.
Mistake 4: Ignoring regime behaviour
Many strategies behave differently during:
Bear markets
High-volatility periods
Defensive or emergency regimes
Users sometimes assume allocations are static, when in reality they evolve over time.
How to avoid it:
Review allocation history and understand how the strategy transitions during stress conditions.
Mistake 5: Over-optimising the past
Some users attempt to “reverse engineer” a strategy to find the perfect historical window or allocation.
This often leads to:
Curve-fitting bias
Unrealistic expectations
Fragile decision-making
Backtests are most useful when viewed over long periods, including unfavourable environments.
A safer way to read backtests
A disciplined approach includes:
Reading strategy objectives first
Reviewing risk and drawdowns before returns
Understanding benchmarks and regimes
Treating results as historical context
Avoiding short-term performance bias
Important note (informational use):
All AlgoMart backtests, statistics, and strategy data are provided for informational purposes only. They do not represent investment advice, predictions, or guarantees of future performance.
Users should conduct their own due diligence and consult qualified financial professionals where appropriate.