Conditional Orders for Exchange Trading Systems
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Solution Overview
Problem
In electronic financial exchanges, market participants face challenges with inflexible order execution and increased losses due to rapidly changing market conditions, leading to a need for greater control and flexibility over orders and reduced network congestion.
Innovation Solution
Implementing a conditional order system in an exchange computer system that allows market participants to set preferred quantities or prices for financial instruments, enabling trades to be executed in series or all at once, with invitations generated for matching orders, and a scorecard system to monitor participant performance and enforce accountability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If firm orders are used for instant execution, then trade speed is improved, but flexibility and control over orders deteriorate
Solution Approach 1:
The system transforms static firm orders into dynamic conditional orders that can adapt to changing market conditions. Orders automatically adjust based on predefined conditions such as price levels, time thresholds, or market events, allowing participants to maintain both execution speed and flexibility simultaneously.
Solution Approach 2:
The patent introduces multiple configurable parameters for conditional orders including trigger prices, time thresholds, quantity adjustments, and price modifications. These parameters allow participants to define precise execution criteria that balance speed requirements with flexibility needs, enabling orders to execute instantly when conditions are met while maintaining control over execution terms.
2Device complexity
If fixed orders are placed in rapidly changing markets, then order simplicity is improved, but loss reduction capability deteriorates
Solution Approach 1:
Participants pre-configure conditional orders with loss protection parameters before market movements occur. The system monitors market conditions and automatically executes protective actions when predefined triggers are met, such as stopping losses when prices reach adverse levels or adjusting quantities when market volatility thresholds are exceeded.
Solution Approach 2:
The system continuously monitors market conditions and order performance, providing real-time feedback to participants about approaching trigger conditions. This feedback mechanism allows participants to review and adjust their conditional order parameters before execution, ensuring that loss protection measures remain appropriate for current market conditions while maintaining relatively simple order structures.
3Measurement precision
If conditional order monitoring is implemented, then trade accuracy is improved, but network traffic and system complexity increase
Solution Approach 1:
The conditional order monitoring system is divided into distributed components that process different aspects of order matching independently. Local nodes perform preliminary filtering and condition checking, transmitting only relevant match candidates to central matching engines. This segmentation reduces network traffic while maintaining high matching accuracy through distributed intelligence.
Solution Approach 2:
The system performs preliminary condition checking and pre-matching operations before full order execution. Conditional orders are pre-validated against market data and opposing orders in advance, so that when triggers occur, only verified match candidates require network transmission. This preliminary processing significantly reduces network traffic volume while maintaining precise order matching through advance validation.
Data Source
AI summary
An exchange computer system enhanced with the ability to implement conditional orders is described. Conditional orders can be received from two or more user devices networked with the exchange computer system. The exchange computer system can identify a potential match between the received conditional orders, and can send invitations to trade to each of the user devices from which the potentially matching conditional orders were received. Each invitation can include, for example, a request to generate and send a new firm order corresponding to the respective user's conditional order. If each of the users transmit new firm orders or otherwise confirm willingness to trade based on information provided in the invitations, the exchange computer system can then process and execute a trade based on the new firm orders.