Asset Evaluation Using Sensitivity and Elasticity Measures
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Solution Overview
Problem
Current asset evaluation and screening tools in financial portfolio management primarily rely on accounting data and stock price information, lacking the ability to project asset value changes based on economic scenarios and exogenous variables, which limits their effectiveness in financial planning and portfolio optimization.
Innovation Solution
An asset evaluation and screening tool that processes historical data to calculate sensitivity and elasticity measures of asset values to changes in exogenous variables, allowing users to input 'what if' scenarios and project asset values and portfolio compositions under different economic conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional accounting data and stock price information are used for asset evaluation, then the evaluation process is simple and data is readily available, but the ability to project asset value changes under different economic scenarios is limited
Solution Approach 1:
The patent pre-calculates and stores sensitivity and elasticity coefficients for multiple exogenous variables based on historical data. This preliminary action enables the system to quickly evaluate asset values under different economic scenarios without performing complex calculations in real-time, thus improving adaptability while managing model complexity
Solution Approach 2:
The patent introduces sensitivity and elasticity coefficients as intermediary parameters that mediate between exogenous variables and asset values. These coefficients capture the relationship dynamics, allowing the system to project asset value changes under different scenarios without directly modeling complex economic relationships each time
2Measurement precision
If sensitivity and elasticity measures are calculated using multiple exogenous variables and economic scenarios, then the evaluation comprehensiveness is improved, but the computational complexity and data processing requirements increase
Solution Approach 1:
The system pre-calculates sensitivity and elasticity coefficients using historical data and stores them for reuse. This preliminary computation of complex measures avoids repeating expensive calculations for each new scenario, thereby improving measurement precision while managing computational complexity
Solution Approach 2:
The patent extracts key relationship parameters (sensitivity and elasticity coefficients) from complex economic relationships. By separating these measurable parameters from the full complexity of economic interactions, the system achieves precise measurements without requiring full computational modeling of all underlying factors
3Measurement precision
If historical data processing is performed to obtain sensitivity formulas, then the evaluation accuracy is improved, but the time required for data processing and model calibration increases
Solution Approach 1:
The patent performs historical data processing and sensitivity formula derivation as a preliminary step that is done once or periodically updated. The resulting formulas and coefficients are stored and reused for multiple evaluations, thereby achieving high measurement precision without incurring time costs for each individual asset evaluation
Solution Approach 2:
The system creates simplified representations (formulas with coefficients) that copy the essential relationships from historical data. These copied relationships can be applied repeatedly without re-processing the original historical data, thus maintaining accuracy while reducing time requirements for subsequent evaluations
Data Source
AI summary
Provided is a technique for evaluating an asset, such as a share of stock in a corporation, by processing historical data for value of an asset and historical data values for various exogenous variables to obtain a formula for calculating a measure of a tendency of the value of the asset to change as a result of changes in the data values for the exogenous variables, the formula being a function of the exogenous variables. Projected data values are then obtained for the exogenous variables, and a measure of the tendency of the value of the asset to change based on a change in at least one of the exogenous variables is estimated using the formula and the input projected data values.