OryvenqisAI combines extensive market data with statistically tested prediction models and translates complex data patterns into concrete, comprehensible recommendations for action. This creates a basis for decision-making that is based on calculation instead of gut feeling.
Discover strategies nowOur models follow a clearly structured three-pillar principle. Every recommendation can be traced back to the underlying data, without black box logic.
Price, volume and volatility data from multiple market sources are continuously merged and cleaned before being incorporated into the modeling.
Statistical models recognize recurring patterns in historical market phases and derive probabilities for short and medium-term price trends.
Each recommendation is provided with an individual risk assessment that makes the position size and possible loss scenarios transparent.
On the technical basis: All models are backtested against multiple full market cycles, including periods of increased volatility. The aim is not to adapt to a single time period, but rather to ensure the robustness of the model logic across different market conditions.
The platform does not replace your own market knowledge, but it significantly reduces the effort required for data analysis and provides an additional, emotion-free perspective.
Instead of manually viewing charts and news, you receive condensed evaluations that significantly reduce the analysis effort per trading decision.
Model-based signals follow fixed rules and are not influenced by daily form, news noise or fear of loss.
Market changes are continually captured, so recommendations are based on current data rather than an outdated snapshot.
Existing strategies can be checked using historical simulations and adjusted in a targeted manner before capital is actually deployed.
Since we do not use fictional success stories, we rely on disclosure of our backtesting methodology. Past market cycles provide the basis on which the models are trained and tested.
Illustrative representation of a simulated strategy curve (solid) compared to a passive reference (dashed) over a multi-year backtesting period.
Both key figures are shown individually for each strategy in the backtesting report, as they depend heavily on the chosen instrument and time frame.
The maximum drawdown shows the largest simulated loss of value within the test period and serves as an orientation for the risk profile of a strategy. The win rate describes the proportion of profitable trades in the historical test, but alone says nothing about the amount of individual profits or losses.
Whether short-term or long-term, the evaluation logic adapts to the selected time horizon without changing the underlying methodology.
For traders who operate within minutes or hours, OryvenqisAI provides short-term signal updates based on volume and volatility changes. The analysis takes into account that even small deviations can be relevant with short holding periods and provides information accordingly in a timely manner.
For investors with a longer investment horizon, the focus is on evaluating trend phases and position sizes. You will receive regular assessments of the risk distribution of your portfolio as well as information about when an adjustment to your positioning might make sense.
Connections to data sources and broker interfaces are made exclusively via encrypted connections. Credentials are stored separately from analytics data, and access to accounts can be limited to read-only at any time.
The platform is designed for connection via standardized interfaces. Existing depot or data connections can usually be expanded without changing the previous broker.
No. OryvenqisAI provides evaluations and recommendations; the final decision about entry and exit remains with you. The level of automation can be individually adjusted, from pure signal display to rule-based execution.
Basic setup, including data connection and selecting a strategy profile, is usually completed within a day. A detailed introduction takes place as part of the demo access.
Test the analysis environment using real market data and see for yourself how the models behave in your preferred trading style.