Investment Valuation Using Joint Probability Distributions
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Solution Overview
Problem
Existing valuation methods for investments fail to accurately account for the uncertainty of timing and magnitude of future cash flows, leading to incorrect investment decisions by ignoring these factors and providing only single-number estimates when probability distributions are more accurate.
Innovation Solution
A computer-implemented method that creates separate probability distributions for the uncertainty of magnitude and timing of future cash flows, combining them into a joint-probability distribution function to generate a two-dimensional net present value probability distribution, allowing users to visualize and modify these distributions for more accurate investment valuation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If prior art valuation methods use single-number estimates or limited distributions, then the valuation process is simple, but the accuracy and reliability of investment decisions deteriorate due to ignoring timing and magnitude uncertainty
Solution Approach 1:
The patent segments the valuation process into distinct components: timing distribution and magnitude distribution. By separating these two aspects of uncertainty, the method allows users to independently analyze and input their knowledge about when cash flows will occur and how large they will be, thereby improving valuation accuracy without overwhelming complexity
Solution Approach 2:
The patent transitions from single-number estimates to two-dimensional probability distributions by incorporating both timing and magnitude dimensions. This dimensional expansion allows for a more comprehensive representation of uncertainty while maintaining user-friendly input through graphical interfaces and predefined distribution shapes
2Ease of operation
If users simplify knowledge to accommodate input limitations, then the valuation method is easy to use, but important information is lost reducing decision reliability
Solution Approach 1:
The patent provides predefined distribution shapes and templates that users can select before inputting specific parameters. This preliminary setup guides users through the valuation process while capturing comprehensive uncertainty information, balancing ease of use with information retention
Solution Approach 2:
The patent introduces graphical interfaces and visual tools as intermediaries between user knowledge and the valuation calculation. These intermediaries allow users to express complex uncertainty information through intuitive visual representations rather than raw numbers, preserving information while maintaining usability
3Productivity
If prior art methods ignore timing of cash flows, then the valuation calculation is simplified, but the net present value accuracy deteriorates
Solution Approach 1:
The patent implements dynamic timing distributions that allow cash flow timing to vary probabilistically rather than being fixed. This dynamic approach captures the uncertainty in when cash flows occur while efficiently calculating expected present values through mathematical integration, maintaining both speed and accuracy
4Device complexity
If prior art methods use single discount rates, then the valuation process is simple, but the accuracy deteriorates when different cash flows have different risks
Solution Approach 1:
The patent applies local quality by allowing different discount rates to be assigned to different cash flows based on their specific risk characteristics. Each cash flow can have its own discount rate while the overall valuation integrates these locally optimized rates, improving accuracy without requiring complete redesign of the valuation framework
Data Source
AI summary
A computer implemented method of valuing and modeling an investment comprising the steps of: providing at least one investment for consideration comprised of at least one future cash flow; creating at least one probability distribution for each future cash flow, by a user, each probability distribution to represent uncertainty of magnitude at at least one particular time to provide at least one magnitude distribution; creating at least one probability distribution for each future cash flow, by a user, each probability distribution to represent uncertainty of timing at at least one particular magnitude to provide at least one timing distribution; combining the magnitude distributions and at least one timing distribution into at least one joint-probability distribution function; and converting at least one joint-probability distribution function to generate a two-dimensional net present value probability distribution.


