Encrypted Trading Data Query System for Market Knowledge
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Solution Overview
Problem
Existing electronic matching and dealing systems for trading goods, services, and currency fail to effectively manage trading functions with low transaction costs while ensuring full access and knowledge, leading to inefficiencies in buyer/seller transactions.
Innovation Solution
A data processing system with control logic that allows selective access and analysis of trading data, enabling queries for potential matching orders without revealing complete data, thus optimizing trading efficiency and market knowledge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If full access to order data is permitted for all potential buyers and sellers, then market knowledge and price discovery are improved, but transaction costs increase and trading efficiency decreases
Solution Approach 1:
The patent segments order data into multiple levels of accessibility: publicly visible order books, hidden orders, and fully private indications of interest. This segmentation allows the system to provide market knowledge to participants who need it for price discovery while preventing universal access that would increase transaction costs and reduce trading efficiency.
Solution Approach 2:
The patent introduces an intermediary matching engine that selectively reveals order data based on pre-established criteria. This intermediary controls information flow by matching buyers and sellers based on hidden criteria without requiring full data transparency, thereby maintaining market knowledge while reducing transaction costs and improving trading efficiency.
2Measurement precision
If complete order data is revealed to all participants, then price discovery is improved, but transaction costs increase due to information overload and processing requirements
Solution Approach 1:
The patent applies local quality by providing different levels of data visibility to different participants based on their specific needs and the characteristics of their orders. Rather than uniform data disclosure, the system tailors information availability locally to each trading interaction, improving price discovery where needed while avoiding the complexity of universal data revelation.
Solution Approach 2:
The patent implements partial action by revealing only the portion of order data necessary for effective price discovery and matching. Instead of providing complete order data to all participants, the system provides sufficient information for price discovery while avoiding the excessive complexity and transaction costs associated with full data transparency.
3Productivity
If selective data access is implemented to reduce transaction costs, then trading efficiency is improved, but market knowledge and price discovery are reduced
Solution Approach 1:
The patent implements feedback mechanisms where the matching engine continuously learns from trading outcomes and adjusts its data revelation strategy. This feedback loop ensures that selective data access maintains adequate market knowledge and price discovery by adapting information disclosure based on observed market conditions and trading patterns.
Solution Approach 2:
The patent applies preliminary action by pre-establishing matching criteria and data revelation rules before trading occurs. This allows the system to efficiently match orders based on pre-defined parameters without requiring real-time analysis of complete order data, thereby maintaining trading efficiency while preserving sufficient market knowledge through predetermined information disclosure.
Data Source
AI summary
In an embodiment, an apparatus comprises a processor, and a memory that stores a program. The program, when executed by the processor, directs the processor to perform a method including the following steps: receiving an encrypted query, in which the query indicates at least one security, and at least one price; determining whether the encrypted query corresponds to any order in an encrypted data set that represents orders; outputting a response to the query, in which the response indicates whether the encrypted query corresponds to any order in an encrypted data set that represents orders; receiving order data that represents the orders; and encrypting the order data to yield the encrypted data set that represents orders.