Order Distribution System for Financial Trade Execution
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Solution Overview
Problem
Financial exchanges face challenges in efficiently matching and executing trades across multiple platforms due to varying order fulfillment methods and rates, leading to suboptimal execution of orders.
Innovation Solution
A method involving a computing device that receives order information, analyzes fulfillment rates and methods across multiple exchanges, and distributes sub-orders to optimize execution, facilitating trade execution based on calculated distributions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If orders are distributed across multiple exchanges, then the probability of order fulfillment is improved, but the complexity of order management increases
Solution Approach 1:
The patent segments a single order into multiple sub-orders and distributes them across different exchanges. The computing device divides the original order into portions based on exchange-specific characteristics such as fulfillment rates, pending order quantities, and matching methods, thereby improving overall fulfillment probability while managing complexity through systematic segmentation
Solution Approach 2:
The computing device acts as an intermediary between the trading system and multiple exchanges. It receives order information, analyzes exchange characteristics, determines optimal distribution, and manages the complexity of coordinating across multiple exchanges, thereby shielding the trading system from direct complexity while improving fulfillment reliability
2Measurement precision
If exchange-specific parameters are analyzed in detail, then the precision of order distribution is improved, but the computational complexity increases
Solution Approach 1:
The computing device performs preliminary analysis of exchange characteristics including fulfillment rates, pending order quantities, and matching methods before distributing orders. By pre-processing and storing this exchange-specific information, the system can make precise distribution decisions without performing complex real-time calculations for each order, thereby achieving high precision while managing computational complexity
Solution Approach 2:
The system changes and adjusts distribution parameters based on exchange-specific characteristics such as fulfillment rates, pending order quantities, and matching methods. By dynamically modifying distribution strategies according to these parameters, the system achieves precise order allocation while using standardized computational approaches to manage complexity
Data Source
AI summary
Systems and methods for trading financial instruments through multiple trading intermediaries are described.