Algorithmic Trading Rule Evaluation Using Conditions Matrix
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Solution Overview
Problem
Current algorithms for evaluating trading rules in financial markets are inefficient, requiring sequential testing of multiple conditions which can lead to slow decision-making and reduced market responsiveness.
Innovation Solution
The use of a conditions matrix and reference rules allows for parallel evaluation of independent conditions, reducing the number of operations required to determine rule satisfaction, and employing sorting and searching algorithms like binary search to efficiently test conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If sequential testing of multiple conditions is used to evaluate trading rules, then the evaluation process is simple to implement, but the decision-making speed is slow and market responsiveness is reduced
Solution Approach 1:
The patent segments the evaluation process by organizing conditions into a matrix structure where conditions are divided into independent groups. This allows parallel evaluation of condition groups rather than sequential testing of individual conditions, significantly improving decision-making speed while maintaining manageable complexity through structured organization.
Solution Approach 2:
The patent introduces a new dimensional approach by using a conditions matrix with multiple dimensions (condition groups, individual conditions, and associated rules). This multi-dimensional structure enables parallel processing across different dimensions, transforming the evaluation from a single-dimensional sequential process to a multi-dimensional parallel process.
2Productivity
If a large number of conditions are evaluated sequentially, then thorough analysis is achieved, but the time complexity increases to O(N*C)
Solution Approach 1:
The patent applies preliminary action by pre-organizing conditions into a structured matrix with defined groups and relationships before evaluation begins. This pre-organization enables efficient parallel processing during actual evaluation, reducing the time complexity from O(N*C) to O(C') by having the structural framework ready in advance.
Solution Approach 2:
The patent creates a copied and simplified representation of the condition evaluation problem through the conditions matrix, where the complex relationships between N conditions and C rules are mapped into a structured format that enables parallel evaluation. This copying approach transforms the computational problem into a more efficient form while preserving the essential evaluation logic.
3Loss of time
If parallel evaluation of independent conditions is implemented, then evaluation speed improves, but the system complexity increases
Solution Approach 1:
The conditions matrix structure serves multiple functions simultaneously: it organizes conditions into evaluable groups, defines relationships between conditions and rules, enables parallel processing, and provides a framework for efficient evaluation. This multi-functionality reduces the need for separate complex mechanisms while achieving parallel evaluation speed improvements.
Data Source
AI summary
Systems and methods of evaluating rules. Other embodiments are also described.