CortelioTrade processes large amounts of data in real time, continuously calibrates risk parameters and presents results in a publicly comprehensible manner. No promise without proof.
The platform divides the analysis process into clearly defined stages. Each stage provides an independent contribution to the decision-making basis - from raw data collection to risk assessment.
Market, order and volume data is continuously collected and normalized. Delays between data collection and evaluation are minimized by the architecture.
Models evaluate position sizes and volatility bands based on historical and current patterns. Results are presented as parameters, not as recommendations with a guarantee of success.
The same analysis logic is applied to different instruments and time horizons. Scaling occurs without adjusting the underlying model parameters.
CortelioTrade is designed for users who see market analysis as an ongoing process, not a one-time forecast. The platform complements existing trading processes and does not replace independent evaluation.
The focus is on the traceability of the results: every key figure in the performance log can be traced back to the underlying model run. This transparency is the basis of cooperation with the user community.
Results are not proven by third-party references, but rather by a publicly viewable log. Entries are time-stamped and will not be changed subsequently.
| field | Description | format |
|---|---|---|
| timestamp | Time of model release | ISO 8601 |
| instrument | Analyzed trading instrument | string |
| signal_id | Reference to the model run | hash |
| risk_band | Calibrated risk class | enum |
| verified_by | Number of independent community confirmations | int |
Each model output receives an immutable timestamp before market execution. Subsequent adjustments are excluded.
Users with active access can compare log entries with their own trading data and report discrepancies.
The log remains visible over the entire observation period, regardless of whether individual periods were positive or negative.
The processing route is divided into four steps. Each step is individually documented and traceable in the system.
Market, order and reference data are merged from multiple sources and normalized to a consistent format.
Statistical models evaluate patterns in the normalized data and derive probability distributions for possible market movements.
Expenses are compared with defined risk parameters. Position sizes and volatility thresholds are adjusted accordingly.
Results are provided as structured metrics, not as an automated trading instruction. The final decision remains with the user.
The analysis logic remains the same, the weighting of the parameters differs depending on the time horizon of the decision.
For positions with short holding times, the latency between data collection and evaluation is prioritized. Risk parameters are calibrated to narrow time windows.
Signals refer to intraday patterns and are updated more frequently than in the long-term model.
For strategic decisions with a longer horizon, patterns are evaluated over several weeks and months. Short-term swings are included with less weight.
Risk parameters are considered at portfolio level, not at individual position.
System access is limited to verified users. After submitting your application, you will receive an overview of the data connection, log structure and account conditions.