Match Engine Implied Order Identification
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Solution Overview
Problem
Electronic trading systems face inefficiencies in identifying and calculating implied orders due to the large number of potential order combinations, leading to limitations in determining all possible or best possible implied markets, especially when order combinations involve more than a few orders.
Innovation Solution
Implementing a distributed computing system with a Match Engine that uses a Match Engine Core and Implicator to identify implied opportunities and calculate implied orders, leveraging parallel processing and graph theory-based methods to accelerate calculations and reduce computational load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the trading system calculates all possible implied order combinations to identify best implied markets, then the completeness and accuracy of implied opportunities improves, but the computational time and processing load increases significantly
Solution Approach 1:
The patent segments the computational process by separating the identification of implied opportunities from the calculation of all possible combinations. The system identifies a subset of relevant implied opportunities based on initial criteria, then performs detailed calculations only on those segments, avoiding the need to process all possible order combinations while maintaining completeness of meaningful opportunities.
Solution Approach 2:
The system performs partial action by calculating implied opportunities for only the most relevant order combinations rather than all possible combinations. It uses heuristics and filtering to perform sufficient calculations to identify all meaningful implied opportunities without the excessive computational burden of exhaustive analysis, achieving practical completeness with reduced effort.
2Productivity
If the system identifies implied opportunities based on multiple real orders, then the market liquidity and transaction volume increases, but the complexity of order matching and calculation increases
Solution Approach 1:
The patent segments the order matching process by first identifying pairs of real orders that can form implied opportunities, then separately processing the calculation and matching of those implied opportunities. This segmentation reduces the overall complexity by breaking down the multi-order matching problem into manageable pairwise comparisons followed by implied opportunity processing.
Solution Approach 2:
The system dynamically adjusts the implied opportunity identification process based on market conditions and order book state. It activates implied opportunity calculations selectively rather than continuously, and adjusts the depth of analysis based on liquidity needs and computational resources, making the complexity adaptive rather than static.
Data Source
AI summary
An electronic trading system utilizes a Match Engine that receives orders, stores them internally, calculates tradable combinations and advertises the availability of real and implied orders in the form of market data. New tradable items defined as combinations of other tradable items may be included in the calculation of tradable combinations. The disclosed embodiments relate to detection of market conditions where identification of implied opportunities may, for example, subvert real orders resulting in undesirable effects. Under circumstances where such undesirable effects are likely to occur, identification of implied opportunities may be delayed thereby allowing market forces to attempt to resolve the aberrant market conditions and avoid the undesirable effects.