Securities Master Design for Reliable Trading Data
Summary
The document explains the role of a securities master: a shared system for collecting, storing, cleaning, validating, and distributing instrument, pricing, fundamental, and transaction data. It describes a range of instruments and downstream uses including trading, risk management, settlement, compliance, and client operations. For historical prices, it outlines core entities such as exchanges, vendors, instruments, prices, corporate actions, and exchange holidays, and recommends combining data vendors when their symbol handling differs.
It compares flat files, document stores, and relational databases, describing trade-offs in queryability, time-series suitability, performance, and customization. Data quality checks must account for corporate action errors, price spikes, faulty OHLC aggregation, and missing observations; spike alerts require thresholds that balance missed anomalies against false positives. The article also advocates automating data workflows and using validation rules and audit trails. It is an architectural overview rather than a detailed implementation guide, and its broad big-data discussion gives few concrete design specifications or measured performance results.
Key ideas
- A securities master provides consistent instrument and market data to trading and other institutional functions.
- Historical data models can separate exchanges, vendors, instruments, prices, corporate actions, and holidays.
- Flat files, document stores, and relational databases differ in query support, time-series fit, and operational complexity.
- Price data requires checks for corporate action errors, spikes, aggregation problems, and missing values.
- Validation rules, audit trails, and automated data workflows support data integrity and reliable research.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.