Trade Compression Using Position Constraints to Cut Order Volume
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Solution Overview
Problem
High volumes of financial instruments traded at electronic exchanges strain computational resources and increase operational and counterparty risk due to rapid market changes and algorithmic trading, necessitating improved order processing efficiency and risk reduction.
Innovation Solution
An exchange computer system employs a compression service that utilizes position and constraint data to generate compressed data, optimizing position sizes and executing trades to cancel out long and short positions, thereby reducing order volumes and risk exposures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If high volumes of orders are processed through electronic exchanges, then trading volume and market liquidity are improved, but computational resource strain and processing speed deteriorate
Solution Approach 1:
The patent combines multiple offsetting orders from different market participants into a single compressed order. By merging long and short positions that offset each other, the system reduces the total number of orders that need to be processed while maintaining the same economic exposure and market liquidity, thereby easing computational strain without sacrificing trading volume.
Solution Approach 2:
The system identifies and eliminates redundant offsetting orders through compression. By discarding duplicate long and short positions that net to zero or near-zero exposure, the patent recovers computational resources that would otherwise be wasted processing unnecessary orders, while preserving the essential trading activity through the compressed representation.
2Speed
If algorithmic trading is used to react rapidly to market changes, then trading responsiveness is improved, but computational resource consumption and system strain increase
Solution Approach 1:
The compression service performs preliminary compression of orders before they enter the main matching engine. By pre-processing and consolidating offsetting positions in advance, the system reduces the computational burden on the real-time matching engine, allowing algorithmic traders to execute rapidly without overwhelming the system's computational resources.
Solution Approach 2:
The patent introduces a compression service as an intermediary layer between order submission and the matching engine. This mediator consolidates and simplifies orders before they reach the core processing system, reducing computational resource consumption while maintaining the speed and responsiveness of algorithmic trading through efficient preprocessing.
3Adaptability or versatility
If more orders are processed to maintain market liquidity, then market participation is improved, but operational risk and counterparty risk increase
Solution Approach 1:
By merging offsetting positions from multiple market participants into compressed orders, the system reduces the number of individual counterparties and transactions that need to be managed. This consolidation maintains market participation and liquidity while reducing operational complexity and counterparty risk exposures, as fewer distinct positions need to be tracked and settled.
Solution Approach 2:
The compression service discards redundant offsetting positions that create unnecessary risk exposures. By eliminating duplicate long and short positions that net to zero, the system reduces operational and counterparty risk while preserving the essential market participation and liquidity through the compressed, netted positions.
Data Source
AI summary
A method is provided for compressing data in an exchange computer system. The method includes receiving position data indicative of a position held with respect to a financial instrument by an exchange participant from among a plurality of exchange participants, and receiving constraint data indicative of one or more constraints on compression defined by the exchange participant. The exchange computer system compresses data based on the position data and the constraint data, resulting in, for each of the plurality of exchange participants, a new allocation of position sizes relative to positions held prior to compression. The new allocation of position sizes is such that a set of long positions held by the plurality of exchange participants with respect to the financial instrument are cancelled out by a set of short positions held by the plurality of exchange participants with respect to the financial instrument.