FAQ Section | Frequently Asked Questions
Simulations are useful when their purpose is clearly defined. They are particularly suitable:
for developing and structuring trading ideas
- for understanding market mechanisms
- for comparing different control approaches
- for training technical processes
- for analyzing interdependencies
In these contexts, simulations provide precise and reliable findings.
They are unsuitable where statements are to be made about real resilience, discipline or behavior under pressure. Simulations cannot answer how a strategy is experienced, maintained or questioned under real risk.
Here too, motivation determines the value of the findings:
- Simulations are a suitable tool for anyone who wants to know whether an approach works logically. If you want to know whether you can implement a strategy in real life, you need an environment with real value retention.
Simulations and real implementation are therefore not successive stages of development, but different areas of knowledge. They answer different questions and should not be played off against each other or equated.
Only when purpose, context and expectation are clearly separated do simulations unfold their actual benefits - without encouraging false conclusions.
Backtesting refers to the retrospective application of a trading strategy to historical market data. The aim is to check how a defined set of rules would have behaved in the past and what results would have been achieved.
The persuasive power of backtests stems from several factors:
- They are based on real historical data
- They deliver quantitative results
- They generate clear key figures and curves
- They suggest objectivity and reproducibility
Backtests therefore appear precise, rational and resilient. They translate a strategy into figures and seem to clearly demonstrate its performance. Especially in comparison to subjective assessments or theoretical assumptions, they convey a high degree of certainty.
This effect is understandable - and not unfounded. Backtesting is a legitimate analytical tool.
The decisive factor, however, is which questions a backtest actually answers - and which it does not.
A backtest answers a clearly defined question:
How would a firmly defined set of rules have behaved if it had been applied consistently in the past under certain assumptions?
It checks:
- the logical consistency of a strategy
- its reaction to historical market phases
- statistical properties such as hit rate, drawdown or volatility
What a backtest does not check:
- the real feasibility of the strategy
- human behavior under pressure
- deviations from the rules
- psychological stress
- decision-making in real time
Backtests operate retrospectively, completely and without uncertainty. They know the entire data flow and are free from expectation, doubt or time pressure. They therefore provide insights into structure and logic - not into real action.
In the context of trading, investment strategies and performance presentations, different analysis and testing tools are used to prepare decisions, evaluate strategies or shape expectations. However, these tools differ not only in their methodology, but also in the type of reality to which they refer. The reality framework serves to clearly categorize these differences. It does not describe quality levels or a sequence, but rather different areas of knowledge, each of which answers its own questions - and has its own limits.
1. Demo accounts - decision without real value Demo accounts depict decisions under realistic market and system conditions, but without real value. They allow learning, orientation and functional understanding, but make no statement about behavior under real decision-making pressure.
2. Simulation & strategy tests - strategy without real stress Simulations test the logical functionality of sets of rules under controlled conditions. They are tools for developing and comparing strategies, but consistently abstract from the human being as the stress carrier of the strategy.
3. Backtesting - past without uncertainty Backtests apply strategies retrospectively to historical data. They provide statistical plausibility and consistency, but operate without uncertainty, without decision points in time and without a real implementation situation.
4. Real money trading - Decision under real value Only in real money trading do real value retention, loss aversion, psychological pressure and irreversibility come together. This not only shows whether a strategy works, but whether it can be sustained.
A track record is the documented historical development of a trading or investment strategy over a defined period of time. It summarizes results in key figures, curves and time series and serves to make performance visible. Its persuasive power comes from three elements:
- History: It is based on past results.
- Quantification: It provides measurable key figures.
- Condensation: Complex behavior is reduced to a few indicators.
This makes a track record appear objective, comparable and verifiable. It appears as empirical proof that a strategy has "worked".
A track record answers a clearly defined question: How has a strategy developed under certain conditions in the past?
It shows:
- results
- fluctuations
- loss phases
- statistical characteristics
It does not answer:
- how these results came about
- how they were experienced psychologically
- how they would come about under changed conditions
- how viable they would be for other people
A track record is thus a description of historical results, not an explanation of how they came about and not a promise for the future.
Performance presentations suggest comparability because they reduce different strategies to common key figures. However, it is often overlooked that these key figures can originate from different areas of knowledge
A track record can be based on:
- real money trading
- simulated trading
- backtesting
- mixed forms
On the outside, these representations look identical. Internally, they are fundamentally different. Without context, the impression is created that the results are directly comparable - even though they were produced under different real-life conditions.
Performance representations are subject to systematic effects, regardless of intention or quality:
- Selection bias: Successful processes are shown, failed ones disappear.
- Time window effects: The selected time period significantly influences the statement.
- Representation reduction: Complex decision-making processes are shortened to final results.
- Psychological smoothing: Drawdowns are presented mathematically, not experienced.
These effects are not caused by manipulation, but by the necessary simplification of historical data.
A track record measures results - not stress.
It does not show:
- how losing phases felt
- whether rules were ever questioned
- how high the mental pressure was
- whether discipline was maintained over the long term
Thus missing a central dimension: human realization under real value.
A performance can be historically convincing and yet be based on assumptions that are not sustainable in real terms - such as long periods of losses, high volatility or rare but extreme risks.
Track records should be understood as classification tools, not as evidence.
They are suitable:
- for historical orientation
- for plausibility checks
- for describing past developments
They are not suitable:
- as a promise of success
- as a prediction of behavior
- as a guarantee of repeatability
The crucial evaluation question is therefore not: How good is this performance? but: Under what conditions was it created - and which of these no longer apply today?
Track records are useful if:
- their context of origin is transparent
- it is clear whether they originate from demo, simulation, backtest or real money
- they are read as historical information
They become problematic if:
- they are presented without context
- they are interpreted as a promise of performance
- they are supposed to replace real decision-making reality
Here, too, it is not the presentation itself that is decisive, but the claim that is made of it.
1. origin & knowledge space
Where did the track record originate?
☐ Real money trading
☐ Demo account
☐ Simulation
☐ Backtest
☐ Mixed form (please explain)
Classification: Results from different knowledge spaces are not directly comparable, even if they are presented in the same way.
2. time period & market phase
Which market conditions does the time period cover?
☐ Several market phases (trend, sideways, stress)
☐ Only selected phases
☐ Unclear / not explained
Classification: A limited time period says more about the phase than about the strategy.
3. Continuity & interruptions
Is the process documented throughout?
☐ Complete
☐ Interrupted (e.g. restarts, resets)
☐ Not comprehensible
Classification: Interruptions significantly change the informative value - regardless of the result.
4. Presentation of risk
Is risk presented explicitly and comprehensibly?
☐ Maximum drawdown clearly stated
☐ Volatility / fluctuation range visible
☐ Position sizes comprehensible
☐ Risk only presented implicitly or not at all
Classification: Return without context to risk is no information.
5. loss phases & stress
Are loss phases transparently recognizable?
☐ Duration and depth visible
☐ Frequency recognizable
☐ Psychological stress at least indirectly deducible
☐ Loss phases are shortened or smoothed
Classification: It is not the amount of profit, but the sustainability of the loss phases that determines feasibility.
6. Rules & implementation
Is it clear how the results were generated?
☐ Rules defined
☐ Decision logic comprehensible
☐ Deviations explained
☐ Black box presentation
Classification: A track record without a rule context is a number, not a strategy.
7. Human dimension
Is the human factor recognizably taken into account?
☐ Real money implementation
☐ Indications of discipline & stress
☐ Handling of drawdowns described
☐ Human factor completely abstracted
Classification: Results without human implementation say nothing about real sustainability.
8. Transferability
For whom should this track record be meaningful?
☐ For exactly this person / this setup
☐ For comparable risk profiles
☐ In general
☐ Unclear
Classification: Performance is not universal - it is context-dependent.
9. Expectation management
How is the track record categorized?
☐ As historical information
☐ As a learning or analysis example
☐ As proof of success
☐ Implicit performance promise
Classification: The greatest distortion is not caused by numbers, but by expectations.