Prumezza Wealth cross-references data from multiple exchanges in real time and applies predictive models to isolate relevant signals, reducing noise and risk exposure in volatile contexts.
The system does not issue absolute predictions. Analyzes historical and current patterns, assigns confidence levels and exposes the logic behind each generated signal.
Prices, volumes and market depth are collected continuously from each linked source, with automatic normalization between different formats.
They combine technical indicators, correlations between assets and historical volatility to generate probabilities, not guarantees of results.
Each signal is accompanied by an explicit confidence level, allowing you to distinguish robust recommendations from marginal hypotheses.
Exposure limits, correlation between positions and stress scenarios are recalculated with each new batch of data processed.
Portfolios and positions spread across different platforms make it difficult to objectively read the total risk. Prumezza Wealth consolidates these sources into a single dashboard, eliminating the need to switch between interfaces to get an aggregated view.
Each link is read-only on market and balance data, with no default funds movement permissions.
The process is documented at each stage, so that the origin of any recommendation can be audited.
Continuous aggregation of market data from connected sources, with latency and integrity recording.
Normalization, removal of outliers and calculation of derived indicators before entry into the model.
Application of predictive models trained on historical series, with periodic reassessment of performance.
Each signal is compared to defined exposure limits before being presented as a recommendation.
No signal is presented in isolation from its risk context. The platform exposes the level of confidence, the correlation with existing positions and the potential impact on the portfolio's total exposure, allowing the final decision to always remain on the investor's side.
The data structure adapts to different capital volumes and risk tolerances, maintaining the same analytical rigor.
Consolidation of personal positions across multiple exchanges, with concentrated exposure alerts and signals filtered by confidence level.
Aggregated view of different portfolios managed under different mandates, with consolidated risk reports by period.
Processing of data volumes greater than those that can be processed manually, with signal history available for internal auditing.
Monitoring of positions held in treasury, with configurable risk limits in accordance with the company's internal policy.
The metrics presented in each profile refer to exposure, concentration and correlation between assets — never to forecasts of guaranteed returns. The past performance of any model is not an indication of future results.
Direct answers to the most common questions about security, data and model operation.
Connections are made through API keys with permissions limited to market and balance reading. Prumezza Wealth does not request or store keys with permission to withdraw funds.
No. The signals result from statistical and probabilistic analysis, presented with the respective level of confidence. The execution decision always remains on the user's side.
Model performance is continuously measured against recent data, allowing accuracy degradation to be identified and parameters adjusted when necessary.
Latency depends on the data source and the complexity of the applied model. The panel indicates, for each signal, the reference moment of the underlying data.
The list of integrations is subject to prior technical validation. Requests for additional integration can be submitted via the contact form.
Access the Prumezza Wealth unified dashboard and analyze the consolidated exposure of your positions before making your next investment decision.
Connections to exchanges are configured with read-only permissions. Market and portfolio data are processed in accordance with data protection requirements applicable in the European Union.