Netrivexo processes real-time market data and provides quantifiable signals for short to medium-term trading. Every model decision is logged and can be traced in the public performance log.
Verified performance · publicly visible since productive operationNetrivexo combines statistical forecasting models with a real-time data pipeline. The aim is not to predict individual price movements, but rather to systematically classify market behavior into quantifiable probability ranges.
The platform was developed for users who need a technical basis for decision-making and want to check model assumptions themselves instead of blindly following ready-made forecasts.
Two components determine the technical basis: the type of modeling and the speed of data processing. Both are optimized independently of each other.
The models are trained on historical and ongoing market data and continually recalibrated. The output value is not a fixed price forecast, but rather a probability interval per signal that adapts to changing market conditions.
Incoming market data is processed continuously, not in periodic batches. This reduces the time between data event and available signal and is particularly relevant for short-term trading decisions.
Every model decision is logged. The following format shows which information is recorded for each entry - regardless of the specific result of individual signals.
| Timestamp | model | Market segment | Signal type | Log status |
|---|---|---|---|---|
| 2024-03-04 09:12 | Model A.2 | Index futures | Long | verified |
| 2024-03-04 11:47 | Model B.1 | FX pair | Short | verified |
| 2024-03-05 08:03 | Model A.2 | Single value | Neutral | verified |
| 2024-03-05 14:29 | Model C.3 | raw material | Long | verified |
Example excerpt from the log format. Complete, continuously updated entries are available to registered users in the customer area.
Technical precision is not an end in itself. It specifically impacts three areas of daily decision-making.
Probability-based signals replace blanket assessments. Position sizes and entry points can be determined based on quantifiable key figures instead of subjective assessment.
The same analytics infrastructure processes a single instrument or several hundred in parallel. The transition from manual observation to systematic monitoring does not require any additional personnel effort.
Through continuous data processing, signals are available as soon as relevant market changes occur. This shortens the reaction time compared to purely manual market observation.
The platform complements existing analysis processes without replacing them. Three steps lead from raw data to actionable insights.
Market and price data is continuously collected from connected sources and normalized before being passed into the model pipeline.
The forecast models evaluate the incoming data, reweight relevant factors and generate a signal with an associated probability value.
Results are displayed in the customer area and documented in the performance log so that they can be incorporated into existing decision-making processes.
The data pipeline processes incoming market data continuously. The actual latency depends on the respective data source and the chosen instrument and is shown per feed in the customer area.
No. The platform provides signals and probability values as a basis for decision-making. The final trading decision, including position size and timing, remains with the user.
Entries are created automatically at the time the signal is generated and can be viewed by registered users in the customer area. Subsequent editing of existing entries is not technically possible.
The models are designed for liquid, data-rich segments such as indices, currencies and selected individual stocks. The suitability for illiquid or data-poor instruments is limited.
Access is via the browser-based customer area. Local installation of additional software is not required.