Trade Matching Platform Implied Spread Detection
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Solution Overview
Problem
Existing financial trading systems face inefficiencies in processing and matching implied spread orders, leading to increased processing resources consumption and reduced market liquidity due to the complexity of identifying and processing potential implied spreads within electronic trade systems.
Innovation Solution
The implementation of enhanced request for quotes (eRFQs) and new enhanced orders that include a CCP attribute, allowing for the determination of implied orders through a request for quote processor module and implied spread determination module, which focuses calculations to identify potential implied orders and facilitate matching across multiple clearing houses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the system processes all potential implied spread orders through complex calculations to identify matching opportunities, then market liquidity and trading efficiency are improved, but processing resource consumption increases significantly
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing implied spread relationships between financial instruments before actual trading occurs. The implied spread determination module pre-processes potential matching opportunities and stores them in a database, so that when orders arrive, the system only needs to query pre-computed results rather than performing complex calculations in real-time, thereby improving trading efficiency while reducing processing resource consumption during peak trading periods
Solution Approach 2:
The system segments the implied spread determination process into distinct modules: the implied spread determination module separately identifies potential implied spreads, the electronic match engine separately processes order matching, and the clearing house selection module separately determines optimal clearing houses. This segmentation allows each module to specialize in specific tasks and process only relevant data, reducing overall processing resource consumption while maintaining high trading efficiency
2Use of energy by moving object
If the system uses simplified methods to quickly process orders, then processing resource consumption is reduced, but the ability to accurately identify implied spread opportunities deteriorates
Solution Approach 1:
The system performs preliminary calculations to determine implied spreads between financial instruments in advance and stores these relationships in a database. When processing actual orders, the system queries pre-computed implied spread data rather than performing complex real-time calculations, thereby maintaining high identification accuracy while significantly reducing processing resource consumption during trading operations
Solution Approach 2:
The implied spread determination module acts as an intermediary between raw market data and the order matching system. It receives market data, calculates implied spreads using established financial models, and provides processed implications to the electronic match engine. This intermediary layer ensures accurate identification of trading opportunities while allowing the rest of the system to operate with reduced computational burden
3Productivity
If the system processes RFQs diligently to ensure accurate pricing, then market liquidity is improved, but the time required to respond to RFQs increases
Solution Approach 1:
The system performs preliminary actions by pre-determining implied spreads and storing them in a database before RFQs arrive. When an RFQ is received, the system quickly queries pre-computed implied spread data and generates responses based on this pre-analyzed information, thereby maintaining accurate pricing while significantly reducing RFQ response time and improving market liquidity
Solution Approach 2:
The implied spread determination module operates autonomously to identify and calculate implied spreads without requiring manual intervention or complex real-time analysis for each RFQ. The system serves itself by maintaining an updated database of implied relationships that automatically responds to market conditions, enabling rapid RFQ response times while ensuring accurate pricing through pre-established mathematical relationships
Data Source
AI summary
The disclosure describes systems and methods for using enhanced RFQs and incoming enhanced orders to assist in detecting implied orders using an implied spread determination module. In one example, a system includes a processor and memory storing a search list and computer-executable instructions, where the instructions determine whether the financial instrument associated with an eRFQ or new enhanced order is on the search list, and then determine if an implied order exists in combination with that financial instrument and CCP attribute designations. In some embodiments, a timer may be used to track a predetermined amount of time to spend towards determining if implied orders exist for a particular financial instrument at particular clearing houses.