Sókn Engineering develops proprietary predictive algorithms based on Modular Calculus and quantum quantitative statistical models to enhance algorithmic trading in the commodity futures market. Their technology provides precise entry and exit positions, enabling traders to accurately forecast price movements and specific targets, rather than relying on traditional statistical models.
Funding
Funding not disclosed
Founders
Product
Problem
Algorithmic trading in commodity futures often relies on traditional statistical models that struggle to accurately forecast price movements and specific targets, leading to imprecise entry and exit positions for traders. Existing quantitative models may not fully capture the complexities and non-linear dynamics within commodity markets.
Solution
Sókn Engineering develops proprietary predictive algorithms based on Modular Calculus, a novel mathematical approach derived from deterministic chaos mathematics, and quantum quantitative statistical models to enhance algorithmic trading in the commodity futures market. Unlike conventional statistical models that measure external influences on commodities, Sókn's technology uses synchronized encryption-based mathematical models to evaluate commodities from within the market's internal dynamics. This approach enables the algorithms to predict price action movement and specific price targets with greater accuracy and consistency. By incorporating AI/ML, the algorithms are designed to become self-learning and self-generating, adapting to evolving market conditions.
Target Audience
The primary customers are algorithmic traders and firms in the commodity futures market seeking more precise and predictive tools for price action and target forecasting.
Features
- Modular Calculus: A proprietary determinant mathematics based on vector and decryption mathematics as well as polymorphic differential rate sequencing.
- Quantum Quantitative Statistical (QQS) Models: Models that run data switching and logic sequencers, quantifying logic switches and limits rather than data inputs.
- Predictive Analytics: Provides detailed entry and exit positions based on Modular Calculus and machine learning.
- Self-Evolving AI/ML: Algorithms designed to become self-learning and self-generating.