Exchange Messaging Policy Using Weighted Message Counts
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Solution Overview
Problem
Inefficient and excessive messaging in financial exchange trading systems can lead to improper price shifting and increased bandwidth requirements, compromising market liquidity and system performance.
Innovation Solution
A mechanism that evaluates message content by grading and applying a weighting factor, determining a weighted message count, and initiating actions if thresholds are met, such as financial penalties or suspending messaging privileges, to discourage excessive messaging while encouraging preferred content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If messages are used to submit bids and offers to maintain market liquidity, then market liquidity is improved, but excessive and inefficient messaging causes improper price shifting and increases bandwidth requirements
Solution Approach 1:
The system changes the parameter of message evaluation by introducing a grading mechanism that assesses message content against predetermined metrics. Messages are weighted based on their quality (e.g., proximity to market price), transforming the binary accept/reject model into a nuanced quality-based filtering system that prevents price manipulation while maintaining legitimate trading activity.
Solution Approach 2:
The system implements feedback by continuously monitoring message content, grading it against established metrics, and adjusting messaging policies based on the results. This closed-loop approach allows the system to respond to messaging patterns in real-time, identifying and penalizing manipulative behavior while encouraging beneficial trading messages.
2Quantity of substance
If messages are used to submit bids and offers to maintain market liquidity, then market liquidity is improved, but excessive messaging slows system performance and increases bandwidth requirements
Solution Approach 1:
The system changes the parameter of message processing by introducing quality-based weighting. Instead of treating all messages equally, the system assigns different weights based on message content quality, allowing the system to prioritize processing and bandwidth allocation to high-quality messages while reducing resources spent on low-quality or manipulative messages.
Solution Approach 2:
The system extracts and separates messages based on their quality and purpose. By grading messages and identifying those that are excessive or manipulative, the system can filter them out from full processing, reducing the overall processing load and bandwidth requirements while maintaining market liquidity through selective message handling.
3Productivity
If a messaging threshold is imposed to reduce excessive messaging, then system performance is improved, but market liquidity may be compromised
Solution Approach 1:
The system changes the parameter of message evaluation from simple quantity counting to quality-based weighting. By introducing grading metrics that assess message content (such as proximity to market price), the system can distinguish between legitimate trading messages and excessive/manipulative messages, allowing threshold enforcement that protects system performance without unnecessarily reducing market liquidity.
Solution Approach 2:
The system applies local quality by evaluating individual message characteristics rather than treating all messages uniformly. Different weights are assigned to different message types and qualities, allowing the system to maintain stricter controls on manipulative messages while being more lenient with beneficial trading messages, thus preserving market liquidity while improving system performance.
Data Source
AI summary
Systems for and methods of evaluating messaging, comprising, receiving, via at least one server device, one or more messages, and said at least one server device processing at least one of the one or more messages by grading content included in said at least one message, applying a weighting factor to said at least one message according to said grading, thereby determining a weighted message count for said at least one message, aggregating the weighted message count for said at least one message, and initiating an action if the aggregated weighted message count meets or exceeds a predetermined count threshold.