Order Queue Position Estimation from Aggregate Market Data
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Solution Overview
Problem
Electronic trading platforms provide limited market data, making it difficult for traders to assess market activity and determine their order position accurately, leading to suboptimal trading decisions.
Innovation Solution
The system estimates a trader's order position in a price order queue by analyzing market updates and displaying this information to help traders make more informed decisions, using graphical and numerical representations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the exchange provides limited aggregate quantity information in the data feed, then the data feed remains simple and easy to process, but the trader cannot accurately assess market activity or determine order position
Solution Approach 1:
The patent segments the aggregate quantity information into individual order components by analyzing changes in aggregate quantities across multiple price levels. The system divides the total market data into discrete order events, tracking each order's entry, modification, and cancellation separately to reconstruct detailed order book information from limited exchange data feeds.
Solution Approach 2:
The patent adds a temporal dimension to the analysis by examining aggregate quantity changes across multiple time points and price levels. By analyzing the sequence and pattern of aggregate quantity changes, the system infers order position information that exists in a different dimensional space than the raw exchange data, effectively extracting hidden information through multi-dimensional analysis.
2Reliability
If the exchange provides only total aggregate quantities at particular prices, then the data feed remains simple to generate, but the trader must guess market activity and cannot make optimal trading decisions
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors aggregate quantity changes and compares them against the reconstructed order book state. By analyzing the feedback from actual market data changes and adjusting the inferred order positions accordingly, the system progressively refines its accuracy in determining order position and market activity, enabling more reliable trading decisions.
Solution Approach 2:
The patent introduces an intermediary computational layer that processes the raw aggregate quantity data from the exchange and transforms it into meaningful order position information. This intermediary system acts as a mediator between the limited exchange data and the trader's decision-making needs, reconstructing detailed market information through algorithmic analysis of aggregate changes.
3Ease of operation
If detailed order book information is provided to traders, then traders can make better informed decisions, but the data feed becomes more complex and resource-intensive
Solution Approach 1:
The patent enables the trading system to self-generate detailed order book information by automatically analyzing aggregate quantity changes and reconstructing individual order data. Rather than requiring the exchange to provide pre-processed detailed information, the system serves itself by deriving the necessary detailed market data from the limited aggregate information provided by the exchange, reducing the burden on exchange infrastructure.
Data Source
AI summary
A system and method for providing order queue position information are disclosed. In this application, market updates are received for a tradeable object from at least one exchange. To the extent that the market updates do not include enough details to compute the queue position of a trader's working orders, estimation may be used. As a result, an order queue is generated to approximate a trader's order position in an exchange price order queue. An interface may be used to display the generated order queue estimation to the trader which provides valuable trading information.