Corivitus continuously analyzes over 500 market pairs and condenses this data stream into readable recommendations, to reduce the time spent monitoring prices and the risk associated with rushed decisions.
Corivitus aggregates market data feeds, applies pattern recognition models, then renders only the variations deemed significant. The objective is not to produce more information, but to remove the noise to keep only what really influences a decision.
This approach is aimed at users who wish to delegate technical monitoring without giving up final control over their allocation choices.
The engine crosses several families of indicators — volatility, volume, correlations between assets — to establish probabilistic scenarios rather than simple trend extrapolation. Each recommendation comes with an explicit confidence level, so you can weigh its use in your own strategy.
Quote feeds are continuously ingested and compared to your interest thresholds. When a significant deviation is detected, an alert is generated without waiting for a full analysis cycle, which limits the time between the market event and its inclusion in your dashboard.
Each recommendation includes an assessment of the associated risk, calculated from the recent volatility of the asset concerned. Safety thresholds, defined according to your tolerance, limit exposure automatically reported as excessive, without replacing your final decision.
Quotes from more than 500 pairs are continuously collected from market sources, normalized and then time-stamped to ensure consistency of comparisons over time.
The models identify recurring patterns and statistical anomalies, considering cross-correlations between assets rather than isolated pair-by-pair analysis.
The result is presented in the form of a readable recommendation, accompanied by a confidence level and a reminder of the estimated risk, for quick reading before any decision.
You define your alert thresholds and consult the dashboard for a few minutes per day, without having to monitor prices continuously to spot an opportunity.
Recommendations flag pairs that are changing in their correlation with your portfolio, making it easier to periodically rebalance based on current data rather than intuition.
More experienced users leverage multi-vector indicators to refine their own models, using Corivitus as a complementary analysis layer to their existing method.
Corivitus was designed to process a volume of market data that far exceeds what manual analysis can cover. Rather than multiplying indicators, the approach favors clarity: each recommendation remains traceable back to the data that produced it.
This rigor translates into a deliberately sober interface, designed for rapid reading on a daily basis rather than for the accumulation of graphics.
Learn moreQuotes are collected continuously from standard market feeds, then normalized to allow consistent comparison between pairs and time periods. No data is generated synthetically.
Corivitus automates monitoring and analysis, but the final decision remains yours. The amount of time you spend depends on the number of thresholds and assets you choose to track.
Each recommendation is accompanied by a risk estimate calculated on the recent volatility of the asset. Safety thresholds, which you can adjust, limit the highlighting of positions considered too exposed.