FAQ Section | Frequently Asked Questions

Standardized KPIs (T1-T3) explain what has happened, but they reach their limits when it comes to behavior, structure and repeatability 

copytrader i/o develops proprietary KPIs (T4) to make patterns visible that cannot be captured or can only be captured indirectly with classic key figures.

What is the fundamental difference between T4 KPIs and T1-T3? 

T4 KPIs ... 

• are not standardized 
• do not follow any external benchmark logic
•  are based on multidimensional observations 
• ask questions instead of providing simple answers 

They are therefore deliberately not ranking instruments, but analysis tools. 

What gaps do T4 KPIs address? 
T4 KPIs start where classic key performance indicators typically fail: 

Behavioral patterns (e.g. running losses, taking profits early) are not always taken into account.

Behavioral patterns (e.g. letting losses run, realizing profits early) 

Temporal asymmetries (e.g. long sideways phases with selective outliers) 

Structural inconsistencies (e.g. performance concentrated on a few trades)  performance concentrated on a few trades) 

Psychological resilience (implicit, not subjective) 

These aspects are real - but rarely explicitly measurable 

Why are T4 KPIs deliberately not universally comparable? 
Because comparability always requires standardization. 
T4 KPIs deliberately avoid this in order to put context before comparison. 

Two strategies can have the same T4 value - and still function completely differently. 

How should T4 KPIs be read? 
T4 KPIs do not answer yes/no questions. They provide clues, tensions and anomalies. 

Read correctly, the questions are not: 
: Is this value good or bad? 
but: 
: Why does this value arise - and is it consistent with the strategy idea? 

Differentiation from classic key figures (brief overview)

Short summary (T4 philosophy) 
T4 KPIs are not a substitute for classic key figures. They are an additional layer of analysis for users who want to understand why a strategy works the way it does.

The Performance Concentration Index measures how strongly the overall performance of a strategy is concentrated on a few individual trades 

It answers the question: 
: Is the performance broadly supported - or dominated by a few outliers 

Why is the PKI a T4 KPI 
No classic KPI answers this question directly. 
The PKI combines: 

• Results distribution 
• Trade frequency 
• Contribution of individual trades to overall performance 

It is therefore structural, not descriptive. 

On which measurement dimension is the PKI considered? 
Primarily at: 

• Strategy level  
• Secondarily at position level (aggregated) 

The PKI is not account-based, as fees and capital size would distort the structure. 

What exactly does the PKI measure? 
Simplified, the PKI measures: 

:: Share of overall performance achieved by the top X percent of the most profitable trades 

The higher this share, the more concentrated the performance. 

Example 
Strategy with 100 trades: 

• Top 5 trades generate 70% of total performance 
• Other 95 trades generate 30% 

→ High PKI 

Another strategy: 

• Top 20 trades generate 45% 
• remaining trades contribute more evenly 

→ Low PKI 

What is the right way to categorize PKI? 

• High PKI 
  → Performance depends heavily on a few events 
• Low PKI 
  → Performance is more widely distributed 

Both are not good or bad per se, but must fit the strategy logic. 

Typical misinterpretation 
A high PKI is bad 

Why this is not true: 
Trend-following or opportunistic strategies thrive on a few large movements. A high PKI only becomes problematic when it cannot be explained or reproduced. 

Interaction with other KPIs 
The PKI unfolds its strength in interaction with: 
Hit rate (T1) 
Average profit/loss (T1) 
Ulcer index (T3) 

This reveals whether outliers are resilient or fragile. 

Short conclusion
The Performance Concentration Index shows whether a strategy is based on structure or chance. It is not a judgment - but an early indicator of fragility or robustness.

The Loss Escalation Index measures whether and to what extent losses escalate over time. It analyzes whether a loss tends to be followed by larger, more frequent or faster losses. 

Core question: 
Are losses processed in a controlled manner - or are they self-reinforcing? 

Why is the VEI a T4 KPI? 
No classic KPI considers loss sequences as a dynamic process. The VEI combines:

•  Loss magnitude time sequence 
• Change in position size 
• Distance between loss trades 

Thus, it addresses behavioral and control mechanisms, not performance 

On which measurement dimension is the VEI considered? 

• Strategy level (strategy level) 
• Position level (sequentially aggregated) 

Not account-based - capital size would distort escalation. 

What does the VEI measure specifically? 
Simplified, the VEI measures: 
:: Whether losses tend to become larger, denser or more aggressive 

Indicators include, among others: 

• increasing loss sizes 
• shorter intervals between losses 
• increasing position size after losses 

Example 
Strategy A: 

• Losses remain of a similar magnitude 
• After losses, longer pauses 

→ Low VEI 

Strategy B: 

• Every loss is followed by a bigger 
• trades always follow faster 

→ High VEI 

How to classify the VEI correctly? 

• Low VEI 
  → controlled loss management 
• High VEI 
  → Indications of escalation, overtrading or loss of control 

The VEI does not evaluate performance, but stability under stress. 

Typical misinterpretation 
A high VEI means bad trading. Not necessarily. A high VEI is only problematic if it is not part of an explainable strategy 

Short conclusion 
The loss escalation index shows how a strategy deals with pressure - not whether it wins.

Hold time asymmetry measures how differently long profit and loss positions are held 

Core question: 
: Are profits treated differently than losses 

Why is the HTA a T4 KPI? 
The HTA makes a classic psychological pattern quantifiable, without subjective assumptions:

• Let losses run 
• Close gains early 

No T1-T3 KPI explicitly maps this behavior. 

On which measurement dimension is the HTA considered?  

• Position level 
• aggregated to strategy level 

What does the HTA measure specifically? 
The ratio of: 
:: average holding period of winning trades 
: is measured: ↔ 
:: average holding period of losing trades 

Example 

• Ø holding period of winning trades: 2 days 
• Ø holding period of losing trades: 8 days 

→ High hold-time asymmetry 

Inverse: 

• Ø Holding period for winning trades: 6 days 
• Ø Holding period for losing trades: 3 days 

→ Inverse asymmetry

How to classify the HTA correctly? 

• High HTA (longer losses) 
  → classic loss aversion pattern 
• Low HTA 
  → symmetrical trade management 

The same applies here: do not evaluate, but explain. 

Typical misinterpretation 
Asymmetry is always bad. 

Not necessarily. Certain strategies require asymmetric holding periods - consistency is key.

In short,
Hold-time asymmetry shows how decisions are made under uncertainty.

The recovery style index (RSI*) analyzes how a strategy typically recovers from drawdowns.

 Key question: 
:: Does the strategy recover quickly and aggressively - or slowly and stably? 

Why is the RSI* a T4 KPI? 
Classical KPIs measure whether a recovery takes place, not how it happens. The recovery style index looks at: 

• Speed of recovery 
• Volatility during the recovery 
• Smoothness of the comeback

On which measurement dimension is the RSI* considered? 

• Portfolio level 
• Strategy level 

What does the RSI* actually measure? 
Simplified, the RSI measures*: 
:: Character of the recovery phase after drawdowns 

Typical patterns: 

• steep, short rebound 
• slow, gradual work back 
• volatile zigzag recovery 

Example 
Strategy A: 

• fast recovery 
• high volatility 

→aggressive recovery style 

Strategy B: 

• slow, steady recovery 

→defensive recovery style 

How to classify the RSI correctly? 

• aggressive ≠ bad 
• defensive ≠ better 

The decisive factor is the fit with the strategy idea and the user profile 

Short conclusion 
The recovery style index shows how a strategy behaves after setbacks - not just that it does.

The Consistency Drift Score measures how much the behavior of a strategy changes over time.

Core question: 
: Is the strategy the same today as it was in the past? 

Why is the CDS a T4 KPI? 
No classic KPI measures style fidelity or behavior change. 
The CDS analyzes changes in: 

• Trade frequency 
• Holding period 
• Risk profile 
• Result distribution 

On which measurement dimension is the CDS considered? 

Strategy level (time-segmented) 

What does the CDS measure specifically?
Measured is: 
:: Deviation of current key figures from historical patterns 

The greater the deviation, the higher the drift. 

Example 

• first 12 months: 
  • quiet trades, 
  • low volatility 
• last 3 months: 
  • higher frequency, 
  • greater swings 

→ High CDS 

How to classify the CDS correctly? 

• Low CDS 
  → high consistency 
• High CDS 
  → style change, adaptation or rule breaking 

Drift can be positive, negative or neutral - transparency is key. 

In short 
The consistency drift score shows whether a strategy remains true to its own logic.