Automated Market Reference Price Calculation System
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Solution Overview
Problem
Current methods for determining over-the-counter market closing reference prices lack transparency, accountability, and automation, leading to material discrepancies in fixed income securities valuations, which hinder investment viability and market growth.
Innovation Solution
The system and method for determining market reference prices involve data validation, eligibility criteria based on tracking error and price volatility, and automation of data processing to ensure reliable and transparent composite pricing, incorporating multiple data sources and regulatory-reported trade data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual data processing and eligibility determination methods are used, then human judgment and flexibility are maintained, but material discrepancies in valuations occur and investment viability is hindered
Solution Approach 1:
The system enables self-service automation where the computer system automatically performs data validation, eligibility determination, and composite price calculation without requiring human intervention. The system self-manages the entire pricing process from receiving bid/ask data to generating the closing reference price, eliminating manual processing errors while maintaining reliability through automated consistency checks and regulatory-compliant methodologies.
2Reliability
If automated data processing is implemented, then consistency and transparency are improved, but system complexity increases
Solution Approach 1:
The automated system is segmented into distinct functional modules: a data receiving module that collects bid/ask data from multiple submitters, a validation module that checks data quality against predefined criteria, an eligibility determination module that assesses submitter credentials and performance, and a composite price calculation module that generates the closing reference price. This modular segmentation manages system complexity by organizing functions into independent, testable units while maintaining overall data consistency and transparency.
3Measurement precision
If multiple eligibility criteria are applied to filter submitters, then data quality is improved, but processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-establishing eligibility criteria and performance thresholds before the closing reference price calculation process begins. Submitter credentials, historical performance data, and validation rules are pre-configured and stored in the system. During the actual pricing process, the system quickly matches incoming bid/ask data against these pre-defined criteria rather than evaluating each data point from scratch, thereby maintaining high data quality while reducing processing time.
Data Source
AI summary
Improved methods and systems are disclosed for processing data records. A method includes receiving data records from a plurality of sources for a plurality of submitters and adjusting the data records by adding fields to the records. The added fields may provide normalized data. The method may also include parsing the added fields to identify a data window within the data records with at least a threshold of data for a subset of the plurality of submitters, determining data statistics of the data for each submitter for the determined data window, and appending flags to the records according to the data statistics.