Private-Attribute Order Matching in a Unified Two-Sided List
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Solution Overview
Problem
Existing computing systems struggle to efficiently match data transaction requests with different attributes in a unified manner, particularly when there are imbalances in the types of requests, leading to inefficiencies and limitations in processing and matching capabilities.
Innovation Solution
A computer system maintains a single two-sided order list that includes different data transaction request types, such as midpoint and discretion orders, which have private attributes, allowing for unified processing and matching while maintaining privacy of certain transaction details.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If separate processes are used to handle different data transaction request types, then the matching process for each type can be simplified and the system is easier to expand, but there is no possibility of matching between different types of data transaction requests
Solution Approach 1:
The patent applies universality by creating a unified matching process that can handle multiple types of data transaction requests (market orders, limit orders, discretionary orders, midpoint orders) within a single process. The matching engine is designed to universally process different request types by evaluating them against a common set of criteria including price, time, and private attributes, enabling cross-type matching while maintaining ease of expansion through a modular architecture that can accommodate new request types.
2Adaptability or versatility
If a unified process is used to handle different data transaction request types, then matching between different types becomes possible, but the complexity of the matching process increases
Solution Approach 1:
The patent applies segmentation by dividing the unified matching process into distinct evaluation stages: public attribute matching (price, time) followed by private attribute evaluation. The matching engine segments the complexity by first performing rapid public attribute filtering, then applying more complex private attribute logic only to candidates that pass the initial filter. This segmented approach enables cross-type matching while managing complexity through hierarchical processing.
Solution Approach 2:
The patent applies local quality by allowing different matching criteria to apply to different parts of the request evaluation process. Public attributes use standard matching rules, while private attributes use specialized evaluation logic. Each data transaction request type can have localized matching preferences applied selectively, such as discretionary orders using custom matching criteria while limit orders use price-time priority, reducing overall complexity through targeted application of different rules.
3Measurement precision
If private attributes are revealed during matching, then more accurate matching can be achieved, but the privacy of transaction details is compromised
Solution Approach 1:
The patent applies the intermediary principle by introducing a confidential evaluation mechanism that acts as a mediator between public matching criteria and private attributes. The matching engine evaluates private attributes (such as discretionary price ranges or client-specific preferences) without exposing them to other participants. The intermediary process compares private attributes only against the submitting request's criteria, maintaining accuracy while preserving privacy through controlled, confidential evaluation.
Solution Approach 2:
The patent applies extraction by separating private attribute evaluation from the public matching process. Private attributes are extracted and evaluated in a confidential sub-process that does not expose the actual attribute values to other market participants. The extraction mechanism allows the system to use private information for matching decisions while removing it from the public domain, achieving accurate matching without compromising transaction privacy.
Data Source
AI summary
A computer system is provided that includes a paired list of data transaction requests on which a matching process is performed. There are multiple different types of data transaction requests that are stored in the paired list including data transaction requests with midpoint attributes and data transaction requests with discretion attributes. The computer system may determine how the multiple different types of data transaction requests may be match against each other. Two matching processes can be used to determine if a match exists between the first and second sides of the paired list. Matches that are determined at private values are not disseminated to third-parties via public market data feeds.