About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Solid Reference Data a Prerequisite For Liquidity Management Success

Subscribe to our newsletter

If you thought the heady world of automated trading, dark pools and liquidity fragmentation under MiFID and RegNMS had little effect on the humble reference data function, then you thought wrong, it seems. A recent research note from analyst Tabb Group identifies a growing need for sell side firms to establish comprehensive liquidity management functions, and warns that not having the requisite integrated, enterprise wide reference data infrastructure in place could represent a real spanner in the works.

According to the paper, Liquidity Management: Pushing Automated Trading Beyond Agency Brokerage, although order management and execution management systems are important components in the electronic trading process, they do not address the way brokers interact with order flow, how sell side traders decide to leverage capital or how firms develop consistent valuation and trading strategies across non-exchange traded products. This creates the need for liquidity management.

“A solid reference data infrastruc-ture is important as a firm begins to centralize its execution model,” the paper continues. “If the firm does not have tight control over its reference data, as it begins to combine order flow from different channels or trade products across asset classes, its ability to link, price and accurately trade these products will be impaired.” For example, it says, when trading the capital structure of a corporation, a firm needs to understand the relation-ship and pricing between equity, equity options, corporate bonds and credit default swaps, so it can properly value and trade these products.
The Tabb research note contends that “while firms traditionally have a good grasp of their market data”, their reference data infrastructure “is a bit more problematic”. “The challenge lies in obtaining the vast selection of reference data for over-the-counter and non-exchange-traded products, as there are few centralized authorities that provide a comprehensive selection of this information.” The challenge is compounded by the fact that as soon as a good centralized reference data source is developed, the investment bank will develop new and more complex products that “were not envisioned when developing the original model”.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: How to organise, integrate and structure data for successful AI

Artificial intelligence (AI) is increasingly being rolled out across financial institutions, being put to work in applications that are transforming everything from back-office data management to front-office trading platforms. The potential for AI to bring further cost-savings and operational gains are limited only by the imaginations of individual organisations. What they all require to achieve...

BLOG

Centralised Data Management Key to AI Success: Webinar Review

The absence of a centralised data management strategy for artificial intelligence is the biggest hurdle to integrating data from different sources for use with the technology. That was the finding of a survey of capital markets participants at a recent A-Team LIVE webinar “How to Organise, Integrate, and Structure Data for Successful AI”. While expert...

EVENT

TradingTech Summit New York

Our TradingTech Briefing in New York is aimed at senior-level decision makers in trading technology, electronic execution, trading architecture and offers a day packed with insight from practitioners and from innovative suppliers happy to share their experiences in dealing with the enterprise challenges facing our marketplace.

GUIDE

Regulatory Data Handbook 2025 – Thirteenth Edition

Welcome to the thirteenth edition of A-Team Group’s Regulatory Data Handbook, a unique and practical guide to capital markets regulation, regulatory change, and the data and data management requirements of compliance across Europe, the UK, US and Asia-Pacific. This year’s edition lands at a moment of accelerating regulatory divergence and intensifying data focused supervision. Inside,...