Electronic Trading Alert System for Erroneous Trade Detection
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Solution Overview
Problem
Electronic trading systems face challenges in identifying and mitigating erroneous trades that can significantly impact market integrity and stability, particularly due to subjective definitions of 'erroneous prices' and the inability to scale with increasing market complexity and volatility.
Innovation Solution
An alert system that monitors trades and compares them to a theoretically derived 'no-bust range' of prices, using input devices, determination logic, and evaluation logic to notify exchanges of potentially erroneous trades outside this range, thereby minimizing harmful effects on the market.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a narrow timeframe is established for trade cancellation requests, then the speed of error resolution is improved, but the reliability of error mitigation deteriorates because erroneous trades outside this timeframe cannot be corrected
Solution Approach 1:
The system performs preliminary action by establishing a theoretical no-bust range before trades occur, using historical volatility data to pre-calculate acceptable price ranges. This allows the system to proactively identify and flag potentially erroneous trades before they cause market harm, rather than relying on post-trade cancellation requests within arbitrary timeframes.
Solution Approach 2:
The system implements continuous feedback by monitoring trades in real-time against the theoretical no-bust range and automatically generating alerts when trades fall outside acceptable parameters. This feedback loop enables ongoing reliability of error mitigation without being constrained by fixed time windows, as the system continuously assesses trade validity.
2Measurement precision
If a theoretical no-bust range is established using historical volatility data, then the objectivity of error identification is improved, but the adaptability to unusual market events deteriorates because the range may not account for black swan events
Solution Approach 1:
The system applies dynamics by making the theoretical no-bust range adjustable and reconfigurable. While the base range is derived from historical volatility for objectivity, the system allows dynamic modification of parameters and ranges in response to changing market conditions, unusual events, or regulatory requirements, thus balancing objectivity with adaptability.
Solution Approach 2:
The system utilizes parameter changes by allowing the volatility period, confidence levels, and range multipliers to be modified based on market conditions. This enables the theoretical no-bust range to adapt to unusual market events while maintaining its objective foundation, as parameters can be adjusted without fundamentally changing the methodology.
3Difficulty of detecting and measuring
If automated monitoring of all trades is implemented, then the detection capability of erroneous trades is improved, but the device complexity increases due to the need for real-time data processing and range calculations
Solution Approach 1:
The system extracts only the essential elements needed for error detection by focusing monitoring efforts specifically on trades that fall outside the theoretical no-bust range, rather than attempting to analyze every aspect of every trade. This selective approach maintains high detection capability while reducing overall system complexity by concentrating resources on anomalous trades.
Solution Approach 2:
The system uses copying by creating a theoretical model (theoretical no-bust range) that replicates normal market behavior based on historical data. This model serves as a reference copy against which actual trades are compared, simplifying the detection process by eliminating the need for complex real-time analysis of every trade's fundamental validity.
4Adaptability or versatility
If the theoretical no-bust range is made flexible to accommodate different market conditions, then the adaptability to various markets is improved, but the measurement precision of error identification deteriorates due to subjectivity in range definition
Solution Approach 1:
The system achieves universality by creating a theoretical no-bust range methodology that can be applied across different markets, products, and time periods while maintaining consistent objective criteria. The same volatility-based calculation method serves multiple functions across diverse trading environments, providing adaptability without sacrificing measurement precision through subjective judgments.
Data Source
AI summary
An alert system that notifies an Exchange's staff of a trade that appears to be outside of an expected market range of prices includes an input device, determination logic, evaluation logic, and alert logic. The determination logic derives a theoretical no-bust range of prices based on data received from the input device. The theoretical no-bust range of prices are prices above and below a synthesized market price, within which an erroneous trade cannot be cancelled. The evaluation logic monitors trades and compares those trades to the theoretical no-bust range of prices. The alert logic notifies the Exchange's staff when the evaluation logic identifies a potentially erroneous trade that lies outside the theoretical no-bust range of prices. A method of notifying the Exchange of a trade that potentially lies outside of an expected range of prices includes monitoring an input range of prices and deriving the theoretical no-bust range of prices. The method then compares transactions prices to the theoretical no-bust range of prices and notifies the Exchange when a potentially erroneous trade can be cancelled.