Portfolio Optimization Matrix Transposition for Risk Evaluation
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Solution Overview
Problem
Current technical solutions for evaluating large portfolios of financial instruments, such as insurance portfolios, are inefficient and unable to provide timely analysis due to complexity, leading to difficulties in reacting to various potential scenarios and optimizing portfolio values.
Innovation Solution
A computer system that uses an n-dimensional matrix to store instrument values for each scenario, transposes the matrix to maximize product values under constraints, and adjusts constraints to ensure risk acceptance, enabling efficient evaluation and optimization of financial instrument portfolios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If current technical solutions are used to evaluate large portfolios of financial instruments, then the evaluation can be performed, but the processing time is excessive and the analysis is not timely
Solution Approach 1:
The patent segments the portfolio evaluation problem by representing it as an n-dimensional matrix where instruments, scenarios, and constraints are decomposed into discrete elements. This segmentation allows the complex evaluation to be broken down into manageable matrix operations that can be processed efficiently by computer systems, transforming an intractable problem into a series of computable steps.
Solution Approach 2:
The patent replaces manual or traditional analytical evaluation methods with automated computer-based matrix operations. By substituting the evaluation mechanism with systematic matrix transposition and constraint processing algorithms, the system achieves rapid evaluation of large portfolios that would be impossible to analyze manually, dramatically improving processing speed while handling complexity through structured computation.
2Reliability
If the portfolio evaluation includes many permutations, constraints, and variables to accurately assess different scenarios, then the evaluation becomes more comprehensive, but the complexity increases making timely solutions difficult
Solution Approach 1:
The patent merges multiple evaluation criteria, constraints, and scenario variables into a unified n-dimensional matrix framework. By combining instruments, scenarios, and constraints into a single structured matrix representation, the system maintains comprehensive evaluation accuracy while enabling efficient processing through unified matrix operations, avoiding the need to handle each constraint separately.
Solution Approach 2:
The patent transforms the portfolio evaluation problem by changing parameters from individual instrument assessments to matrix-based scenario evaluations. This parameter transformation allows the system to handle multiple constraints and variables simultaneously through matrix transposition and multiplication, maintaining comprehensive accuracy while reducing computational complexity through dimensional transformation.
3Adaptability or versatility
If traditional methods are used to evaluate portfolio scenarios, then all constraints can be considered, but the evaluation cannot be completed in a timely manner to react to changing conditions
Solution Approach 1:
The patent performs preliminary action by pre-structuring portfolio data into an n-dimensional matrix format with all instruments, scenarios, and constraints already organized before evaluation begins. This preliminary structuring allows rapid scenario analysis when needed, as the framework is already prepared and can quickly process different evaluation conditions without requiring time-consuming data organization during the actual evaluation.
Solution Approach 2:
The patent introduces dynamics by enabling the matrix framework to adaptively evaluate different scenarios and constraints on demand. The system can dynamically switch between evaluating different portfolio configurations, risk scenarios, and constraint combinations by simply changing the input parameters to the matrix operations, providing versatile scenario coverage while maintaining rapid response capability.
Data Source
AI summary
A computer system configured to evaluate a portfolio comprising instruments, comprising a computer memory configured to store, for each instrument, an instrument value for each portfolio scenario in an n-dimensional matrix, a first constraint and a second constraint; and a computer processor configured to transpose the n-dimensional matrix, to determine a first solution by maximizing the product of transpose of the n-dimensional matrix and the first constraint, determine whether the first solution is within an accepted range of an acceptable risk, if the expected first solution is not within an accepted range of an acceptable risk, process the second constraint with the first solution to obtain a second solution, and determine whether the second solution is within the accepted range of the acceptable risk.