Fuero Inversanza processes market data with low latency and applies predictive models to flag risks and opportunities before they materialize. The final decision remains in the hands of the operator; the system provides the quantitative context.
The platform combines structured and unstructured data sources to build a consistent market reading, reducing the margin of error associated with human bias in decision making.
News, regulatory reports and corporate communications become quantifiable variables through natural language processing, integrated into the same flow as price and volume data.
The models apply the same criteria consistently in each analysis cycle, avoiding deviations due to fatigue, overconfidence or loss aversion during prolonged sessions.
Correlation matrices between indices, currencies and raw materials are calculated continuously, alerting when a position is exposed to an unanticipated systemic movement.
| Technical parameter | Description | Reference value |
|---|---|---|
| Average inference latency | Time between data ingestion and signal generation | < 15ms |
| Refresh Rate | Predictive model recalculation cycle | 250ms |
| Instruments covered | Currencies, indices, raw materials and fixed income | 4,500 assets |
| Training history | Time window used in backtesting | 10 years |
The risk module operates continuously, even outside normal desk hours, applying limits defined by the operator himself and executing adjustments when established thresholds are exceeded.
Constant reading of implied volatility and net exposure by instrument.
Each position is checked against the configured drawdown parameters.
If a threshold is exceeded, the system automatically rebalances or notifies the operator.
Fuero Inversanza follows a white-box approach: each recommendation can be traced back to the source data and applied rules. The system supports the operator's strategy; does not replace it.
Market data, news and reports are incorporated from verified sources in real time.
Heterogeneous information is standardized to a common format, comparable between assets and periods.
Predictive models generate a probabilistic reading on direction and associated risk.
The recommendation is moved to the operator panel or, if configured, to the automated order.
Each data source used in the inference is recorded with a time stamp, allowing the origin of any generated signal to be audited.
Models are periodically retrained with historical data and validated through backtesting before replacing a version in production.
The environment is organized in compact modules and tabular views, designed for sessions of several hours in front of the screen without added visual fatigue.
Each interface block can be reordered, hidden or expanded depending on the operator's strategy. Tabular views prioritize information density over visual decoration.
The connection via API is usually completed in a few business days, depending on the broker or internal system to be connected. The technical team accompanies the configuration of credentials and risk limits.
Operational data is processed in infrastructure located in the European Union, under the principles of minimization and purpose limitation established by the RGPD. No customer data is shared with third parties outside the service.
Inference latency is typically kept below 15 milliseconds. It may vary depending on market load and network distance between the operator and the processing node.
Auto-execution is optional and is activated only within the risk limits defined by the trader. Outside those limits, the system notifies rather than acts.
We offer a guided technical demo, focused on your current instrument and broker mix. This is not a generic free trial, but rather a session geared toward your use case.
A specialist will review latency requirements, connectivity and risk parameters before proposing an initial configuration.