Flexport replaces manual data processing with a decision engine based on artificial intelligence. The system analyzes asset volume, volatility and correlation before proposing a portfolio allocation ready for review.
Operational dashboard: exposure by asset, 90-day historical volatility and market sentiment level, updated each trading session.
The Flexport model combines multivariate analysis with continuously updated market data series. Instead of relying on spreadsheets or periodic reviews, the platform recalculates portfolio exposure whenever a relevant change in market conditions is detected.
The process is designed for a user who manages his capital remotely and needs direct execution, without installing additional software or manually configuring parameters.
The platform collects quotes, macroeconomic indicators and volume data from multiple markets in a single input layer, without manual intervention.
A model trained on historical series estimates return and risk scenarios, prioritizing combinations of assets with lower correlations with each other.
The result is presented as an assignment proposal ready for review and approval, with details of the criteria applied.
Flexport is designed for the remote investor who needs to understand the origin of each recommendation. The indicators that feed the model are shown along with the portfolio proposal.
Continuous monitoring of price, volume and liquidity by asset, with updates during active market sessions.
Each asset receives a score based on historical volatility and sensitivity to recent macroeconomic events.
The system identifies correlations between assets to avoid unwanted risk concentrations within the same portfolio.
The following examples are hypothetical and describe how the model would respond to different risk objectives, applying common financial terminology in the Spanish market.
Capital preservation with limited exposure to equities and priority in low volatility assets.
Faced with a spike in volatility in the markets, the system reduces the weighting in equities and increases the allocation in short-term fixed income.
Standard deviation of monthly profitability, with alert threshold adjusted to the low risk profile.
Performance maximization assuming higher exposure to market volatility.
During a phase of economic expansion, the model increases exposure to cyclical sectors and reduces liquidity positions.
Sector momentum and beta against the benchmark, with rebalancing when the divergence exceeds the expected range.
Balanced distribution between asset classes, seeking to reduce dependence on a single sector or geography.
If excessive concentration is detected in a sector after several consecutive increases, the system redistributes part of the position towards uncorrelated assets.
Correlation matrix between assets, reviewed in each processing cycle to avoid risk overlaps.
No complex installation or configuration required. Registration completes in one session and the model immediately begins processing data with the risk parameters you define.
Start right nowAccount data is managed with industry-standard encryption and is not shared with third parties outside of the service.