This book is intended to provide a guide to the universe of data content produced by the global capital markets on a daily basis. Commonly referred to as “market data”, the universe of content is very wide and the type of information correspondingly diverse. Jargon and acronyms are very common. As a result, users of marker data typically face difficulty in applying the content in analysis and business applications. This guide provides an independent framework for understanding this diversity and streamlining the process of referring to content and how it relates to today’s business environment.
The book achieves this goal by providing a consistent frame of reference for users of market data. As such, it is built around the concept of a data model – a single, coherent view of the capital markets independent of any one source, such as an exchange. In particular it delineates clearly between the actual data content and how it is delivered (i.e., realtime data streams versus reference data). It shows how the data relates across the universe of securities (i.e., stocks, bonds, derivatives etc.). In this way it provides a logical framework for understanding how new content can be added over time as the business develops.
1. Uniqueness – this is the first comprehensive catalog and taxonomy to be made available for a business audience
2. Industry Acceptance – the framework described in this book is implemented as a relational data model in the industry today and used by blue chip multinational firms
3. Comprehensiveness – there are no arbitrary distinctions made based on asset class or data type (the legacy approach). The model presented in this book is fully cross asset and makes no distinction between data types (i.e., realtime versus historical/reference data) or sources
4. Independence – the framework is an independent, objective ov
*First and only single, comprehensive desk reference to market data produced by the global capital markets on a daily basis
*Provides a comprehensive catalog of the market data and a common structure for navigating the complex content and interrelationships
*Provides a common taxonomy and naming conventions that handles the highly varied, geographically and language dependent nature of the content
Business analysts employed in the financial services industry internationally; Software application developers in financial institutions and in Software firms providing financial applications and solutions; Consultants providing services to the financial services industry.
Table of Contents
Introduction; Conceptual Framework, Reference Data; Business Data; Static Data; Appendix.
"Next to people, data is one of the most important assets of a firm. And in the world of banking and finance, knowing how to manage this important asset, understanding its complexities and behaviors, is critical to a firm's efficient operation.
Marc Alvarez explores this topic by breaking down the elements of Market Data into simple language. He demystifies this complex subject through easy to understand explanations and clear illustrations.
Whether you are new to this subject, or a seasoned data veteran, Market Data Explained does just that - it provides a comprehensive guide to understanding Market Data and its components, how they are related, and how they fuel the engines of today's financial institutions."
---John A. Bottega - Chief Data Officer - Citigroup Corporate and Investment Bank
“Capital markets can be complex and confusing. No less so the data that describe them. Alvarez’s guide sheds considerable light on the subject. He explains the overall structure of market data and guides our understanding of the details. I particularly liked the figures, as they cut to the essence of some complicated ideas.”
-- Tom Redman, The Data Doc, Navesink Consulting Group
So again, this is more than a primer, even though it sets out to define the market data industry's framework from the bottom up. In this, it performs a much-needed service, since even the most seasoned of practitioners seem to get their proverbial data-definition knickers in a twist or else suffer from Humpty-Dumpty syndrome ("reference data shall mean whatever I choose it to mean..." and so on.).
A serious read, then, that we'd recommend to all-comers, new and old.-Market Data Insight, October 2006