Approximate Computing Engine for Real-Time Financial Portfolio Evaluation
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Solution Overview
Problem
Current computer-networked environments for financial markets fail to provide real-time evaluation of financial portfolio performance, leading to inaccuracies in reflecting current market conditions.
Innovation Solution
Implementing an approximate computing engine and immutable logs within a persistent relational database to process and store financial transaction data, enabling real-time processing and accurate evaluation of portfolio holdings by maintaining a consistent state of data across the network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional computer-networked systems are used to store and process financial transaction data, then data storage and basic processing capabilities are provided, but real-time evaluation of financial portfolio performance cannot be achieved and the value does not reflect current market conditions
Solution Approach 1:
The patent pre-computes and stores intermediate results (such as portfolio values at different time points) in the database before they are actually needed for evaluation. When a user queries for current portfolio value, the system can retrieve pre-computed values and only perform minimal additional calculations, significantly reducing real-time processing time while maintaining accuracy.
Solution Approach 2:
The patent divides the financial portfolio evaluation into multiple discrete time points and stores results for each time point separately in the database. This segmentation allows the system to answer queries about specific time periods efficiently without reprocessing the entire historical data, enabling fast real-time evaluations while maintaining precise historical accuracy.
2Productivity
If real-time processing of financial performance information is implemented, then current market conditions are reflected accurately, but system complexity and computational requirements increase
Solution Approach 1:
The database system automatically performs computations and maintains its own state without requiring external intervention. When new financial transaction data is inserted, the database automatically updates portfolio values, generates intermediate results, and maintains consistency across all time points. This self-service capability eliminates the need for complex external processing systems while achieving real-time evaluation.
Solution Approach 2:
The patent combines data storage, intermediate result computation, and query processing into a single integrated database system. By merging these functions that would traditionally require separate complex systems, the patent reduces overall system complexity while maintaining high processing speed for real-time portfolio evaluation.
3Loss of time
If fast processing of financial performance information is achieved through prediction, then real-time evaluation is enabled, but precision accuracy may be compromised
Solution Approach 1:
The system pre-computes and stores accurate portfolio values at multiple time points in advance. When a user needs current or historical portfolio information, the system retrieves these pre-computed accurate values directly from the database rather than performing predictions or approximations, ensuring both speed and precision are maintained simultaneously.
Data Source
AI summary
Various embodiments are generally directed to techniques for accurate evaluation of a financial portfolio. Techniques described herein may include an apparatus comprising: a processing circuit; and an approximate computing engine, executed on the processing circuit, operative to process data items corresponding to prices of funds, compute a Net Asset Value (NAV) based on the data items, determine a precision associated with the Net Asset Value (NAV), and based upon a precision metric, determine whether to use the Net Asset Value (NAV) in a business decision. Other embodiments are described.