We transform large volumes of market data—including traditional assets and crypto assets—into actionable recommendations, validated through historical backtesting, to optimize your portfolio and reduce operational risk.
Request Technical DemoIn markets that operate 24 hours a day, such as cryptoassets, processing speed makes the difference between a captured opportunity and an avoidable loss. Litiosur bridges the gap between data capture and strategic execution through predictive models trained on long historical series.
Instead of reacting to every market movement, the platform filters out statistical noise and retains only the signals that, based on the history analyzed, correlated with specific results.
Each recommendation that Litiosur delivers can be traced back to a specific stage in the process. There is no black box: there is a documented and verifiable method.
Processing of heterogeneous sources—exchanges, traditional markets and macro indicators—in real time.
Application of Machine Learning algorithms to detect patterns not evident to the naked eye.
Simulation of scenarios and backtesting against historical data to validate each recommendation before delivering it.
Delivery of insights ready to be incorporated into the team's financial decision-making.
Immediate response capacity to changes in markets that do not respect fixed schedules, such as crypto assets.
Each strategy is validated against historical data from different market cycles before being considered suitable for production.
Designed to handle growing data volumes—new assets, new sources—without loss of accuracy.
Institutional-grade data protection standards, in line with the demands of a regulated financial environment.
Dynamic adjustment of asset composition—including cryptocurrencies—based on risk-reward projections updated with each new market data. The investor retains control of the final decision; The platform provides the analytical foundation.
Preventive identification of operational deviations and price movements that deviate from expected historical patterns, allowing a position to be reviewed before the risk materializes.
The platform connects via standard interfaces to existing portfolio management systems and data sources, without requiring a complete migration of already operational infrastructure.
Data from traditional markets, cryptoasset exchanges, macroeconomic indicators and historical price series are processed, normalized into a common format before analysis.
Each model is backtested over different periods and market conditions before going into production, and its performance is periodically reviewed for loss of accuracy.
Talk to a specialist about how to apply predictive models and backtesting to your own portfolio, including your exposure to crypto assets.
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