FAQ Section | Frequently Asked Questions

1. cognitive space & capital commitment 

In which reality space does the signal strategy operate? 

☐ Real money trading by the signal provider 

☐ Demo account 

☐ Simulation / backtest 

☐ Mixed form (clearly explained) 

Classification: Strategies without real capital commitment by the signal provider are not subject to loss aversion - their results are not directly transferable to subscribers 

2. Alignment of interests 

Does the signal provider bear the same risk as the subscribers? 

☐ Own capital in the same structure 

☐ Own capital, but different parameters 

☐ No own capital 

☐ Unclear 

Classification: The lower the risk equality, the greater the structural asymmetry. 

3. transparency of the decision-making logic 

Is it clear how decisions are made? 

☐ Rules roughly described 

☐ Decision logic explainable 

☐ Adjustments communicated 

☐ Black box (only signals visible) 

Classification: A strategy that is only observable but not explainable remains a black box - regardless of its performance 

4. Origin of the performance 

What is the performance shown based on 

☐ Real money track record 

☐ Demo performance 

☐ Backtest

 ☐ Combination (clearly separated) 

Classification: Outwardly identical curves can originate from completely different areas of knowledge. 

5. Presentation of risk & loss phases Are risks presented realistically and completely? 

☐ Maximum drawdown transparent 

☐ Duration of loss phases visible 

☐ Volatility comprehensible 

☐ Losses smoothed or shortened 

Classification: It is not the profit that determines sustainability, but the question of whether loss phases can be endured. 

6. adaptations & strategy changes 

How are changes dealt with? 

☐ Rule adjustments announced 

☐ Reasons explained 

☐ Changes retroactively visible 

☐ Adjustments not transparent 

Classification: It is not adjustments that are problematic, but their invisibility 

7. Degree of automation & loss of control 

How much control remains with the subscriber 

☐ Manual execution 

☐ Partially automated 

☐ Fully automated 

☐ No possibility of intervention 

Classification: Automation does not replace responsibility - it shifts it. 

8. Psychological burden 

Who bears the mental pressure of real losses?

☐ Signal provider and subscriber alike 

☐ Only the subscriber 

☐ Not addressed 

Classification: Drawdowns are key figures for the provider - a reality for the subscriber 

9. Expectation management 

How is the strategy communicated?

☐ As a historical example 

☐ As a learning or observation tool 

☐ As an ongoing trading solution 

☐ Implicit promise of success 

Classification: The greatest danger lies not in the strategy, but in the expectations. 

10. transferability 

Who is the strategy realistically suitable for? 

☐ Only for this specific setup 

☐ For similar risk profiles

☐ For all 

☐ Unclear 

Classification: Performance is not universal - it is context-dependent.

Why is it important to recognize commission models? 

Commission models influence how content is created and how it is presented. If you know the economic incentives behind recommendations, you can better classify statements - regardless of whether the recommendation is well-intentioned or technically correct. 

It's not about discrediting content, but about making interests visible. 

How can you recognize affiliate models? 

Affiliate models can often be recognized by the following characteristics: 

• Links with tracking parameters 
• Notes such as "partner link", "advertising link", "affiliate" (often placed inconspicuously) 
• Emphasis on simple entry points ("Ready to start in a few minutes") 
• Focus on registration or account opening 

Typical is: 
The recommendation ends before the actual use. 

Classification: The economic incentive lies in the conclusion - not in long-term success. 

How can you recognize volume- or activity-based commissions? 

These models are less obvious, but are reflected in the tone and frequency of the content:

• regular calls to action 
• permanent market presence ("There's movement now") 
• little thematization of pauses or non-action 
• emphasis on opportunities instead of weighing up decisions 
• Activity is often presented as the normal state. 

Classification: If inactivity hardly ever occurs, activity is usually economically relevant 

How to recognize order book or flow-based investments 

These models are the most difficult for users to recognize, as they are rarely communicated openly. Indirect indications can be: 

• strong bundling on a few platforms or products 
• emphasis on "liquidity", "tight spreads", "optimal execution" 
• upgrading of high trading frequency 
• hardly any discussion of alternatives 

The recommendation appears neutral, but is structurally bound. 

Classification: It is not the result that is monetized here, but the behaviour 

What role does the labelling of advertising play? 

Formal labels such as: 

• "Advertisement" 
• "Advertising" 
• "Sponsored" 

are legally relevant, but often not very informative in terms of content. 

The decisive factor is not the presence of advertising, but: 

• how strongly it shapes the narrative 
• whether alternatives are mentioned 
• whether risks are treated equally 

Classification: Transparency does not start with the label, but with the classification. 

Why are success stories a strong indicator? 

Success stories fulfill several functions: 

• emotional activation social affirmation 
• simplification of complex contexts 

They are particularly effective when: 

• the way there is presented in a shortened form 
• there is a lack of setbacks 
• transferability is implicitly assumed 

Classification: Where storytelling replaces analysis, there is usually a monetary incentive. 

How do you recognize a lack of alignment of interests? 

A central test criterion is the question: Does the recommender bear the same risk as the following person? 

Warning signals: 

No clear statement on own capital commitment 

Focus on reach instead of responsibility 

Missing statements on own loss phases 

Classification: If risk equality is missing, there is structural asymmetry. 

Are there simple test questions for users? 

Yes. Three simple questions are often enough: 

How does the recommender earn money? 

What will they actually benefit from if I take action? 

What would happen if I did nothing? 

The clearer these questions can be answered, the less information asymmetry there is 

Final classification 

Not every remunerated recommendation is problematic. In certain constellations, remuneration models can be a legitimate and necessary refinancing instrument for developing new products, services or initiatives. In particular, where these funds serve to educate, impart knowledge or develop consumer protection tools, they fulfill a comprehensible function. The decisive factor here is not the existence of economic interests, but the motivation with which they are used - and the purpose they ultimately serve.