Trade Message Fee Stamping for Real-Time Exchange Fee Calculation
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Solution Overview
Problem
Existing electronic trading systems face challenges in accurately and efficiently calculating and collecting fees for trades due to complex, resource-intensive post-trade processing, leading to processing bottlenecks, inaccuracies, and excessive resource usage.
Innovation Solution
An electronic trading exchange apparatus with a memory and processor architecture that updates client fee instructions in real time, generating trade messages with embedded fee instructions to calculate fees without additional information, reducing resource usage and latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex post-trade processing is used to determine fees based on multiple fee schedules and client information schedules, then fee calculation accuracy is improved, but processing time and resource consumption increase significantly
Solution Approach 1:
The system performs preliminary actions by maintaining real-time client information schedules and fee schedules in memory before trade execution. When a trade is executed, the matching engine immediately has access to the current fee rate and client category without needing to perform complex lookups later, enabling instant fee determination at the time of trade execution
Solution Approach 2:
The matching engine performs self-service by autonomously determining fees for executed trades using the client information schedule and fee schedule stored in its memory. The engine independently calculates fees without requiring external intervention or complex post-trade processing, thereby reducing processing time and eliminating bottlenecks
2Measurement precision
If multiple fee schedules and client information schedules are maintained for different trader categories and time periods, then fee calculation accuracy is improved, but memory resources and processing complexity increase
Solution Approach 1:
The matching engine serves multiple functions by simultaneously maintaining client information schedules, fee schedules, and executing trade matching with real-time fee determination. This multi-functional approach consolidates what would otherwise require separate systems for schedule management and trade processing, reducing overall system complexity while maintaining accuracy
Solution Approach 2:
The system dynamically changes parameters by updating client information schedules in real-time based on trading volume and trader category. Fee rates are adjusted according to current market conditions and client performance metrics, allowing the system to adapt to changing parameters without requiring complex reconfiguration or multiple static schedules
3Measurement precision
If real-time updates of client information are performed based on external trading data, then fee calculation accuracy is improved, but bandwidth resources and processing load increase
Solution Approach 1:
The system extracts only the essential information needed for fee calculation from external trading data sources. Rather than processing complete trade datasets, the matching engine selectively extracts relevant client identification, trading volume, and category information, thereby reducing bandwidth consumption and processing load while maintaining fee calculation accuracy
Data Source
AI summary
System, method, and apparatus may determine exchange and clearinghouse fees for a client to an executed trade based on client fee instructions indicating real time fee rates in a trade message generated by an electronic trading exchange that executes the trade, without any additional information other than information in the trade message.