Dedicated Trading Buffers for Latency Reduction
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Solution Overview
Problem
High frequency trading systems face latency and usability issues due to the inefficiency of database and interface synchronization, leading to delayed trade execution and increased turnover in trading systems.
Innovation Solution
Implementing a system with multiple dedicated buffers on computing systems to store and process data associated with securities, utilizing at least two processors for parallel computing and efficient memory management, allowing for faster data access and processing, and precomputing information to enhance response time and update speed in a dynamic multi-dimensional event space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional database and interface synchronization is used, then system complexity is reduced, but trading execution speed and latency performance deteriorate
Solution Approach 1:
The system divides the trading platform into separate components: a user interface layer, an order management layer, and a dedicated buffer layer. Each buffer (bid buffer, ask buffer, trade buffer) is independently managed and synchronized only when necessary, rather than requiring full database synchronization for every price update. This segmentation allows the interface to respond quickly to market changes while maintaining data integrity.
Solution Approach 2:
Dedicated buffers act as intermediary structures between the market data feed and the user interface. These buffers temporarily hold price data, bid/ask information, and trade data, allowing the interface to display information rapidly without requiring immediate database commits. The buffers mediate between high-speed market data arrival and the slower database synchronization cycle.
2Loss of information
If traditional database synchronization is used, then data consistency is maintained, but latency in updating interface increases
Solution Approach 1:
The system performs preliminary data preparation by organizing market data into structured buffers before interface display is needed. Bid buffers, ask buffers, and trade buffers pre-process and organize price data, bid-ask spreads, and trade executions in memory-efficient structures. This preliminary organization allows the interface to quickly retrieve and display information without performing complex database queries at the moment of display.
Solution Approach 2:
The system changes the synchronization parameter from frequent full database commits to periodic buffer-to-database transfers. Instead of synchronizing every price tick with the database, the buffers maintain data in memory and synchronize with the database at controlled intervals or when thresholds are reached. This parameter change reduces database I/O overhead while maintaining data consistency through structured transfer protocols.
3Measurement precision
If frequent database updates are performed, then data freshness is improved, but system performance and turnover efficiency deteriorate
Solution Approach 1:
The buffers enable continuous display of fresh market data by maintaining in-memory copies of price information, bid-ask data, and trade executions. The user interface continuously reads from these buffers without interruption, providing real-time updates to traders. Meanwhile, database synchronization occurs continuously but at a lower frequency, transferring bulk data periodically rather than on every price change. This continuous useful action maintains both data freshness and trading efficiency.
Data Source
AI summary
Systems and methods are disclosed to enable a system to address latency and accuracy issues in financial trading. A system with multiple buffers and at least two processors are provided to load data associated with values for securities, a plurality of executable code associated with a plurality of predetermined functions to process the values of the data; and parameter data and datasets associated with output of the individual executable code. The parameter data provides scheduling and mapping for the at least two processors in the computing system to process the values. Datasets are generated for the third buffer area after the processing of the values and results from the datasets are projected in a multi-dimensional event space of a user interface using the datasets with a predetermined granularity so that risk values are provided dynamically with security values from the results.