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The Basics of Data Analytics for Corporate Debt Markets

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This chapter is from the book
The corporate debt markets are dynamic, not static, and analytics is necessary to see how the markets are changing. Robert S. Kricheff explains the basics of data analytics as related to the corporate debt market in this introduction to his book.

Why Use Analytics?

Using data analytics is absolutely necessary in the modern corporate debt markets; the sheer growth and complexity of the market make it almost impossible to do any major role in these markets without at least some use of analytics. It is required to compete in the modern markets and, with increasing focus on managing risk, it is a necessary tool to manage large trading desks at investment banks and portfolios at money management firms. The corporate debt markets are dynamic, not static, and analytics is necessary to see how the markets are changing.

New entrants into this market should be aware of the basic tools used for analyzing data in the markets, and more seasoned practitioners should also be aware of how others in the markets may be using analytics. Everyone should be looking at new ways to analyze the markets and be looking for ways to use new developments in the market in his or her analytics.

From risk managers, to credit analysts, portfolio managers, investment bankers, capital markets and syndicate personnel as well as traders, salespeople, and asset allocators within the multitrillion dollar international corporate debt market, if you do not use data analytics in your business and investing decisions, you will be at a massive disadvantage.

Typically, numerous programmers, system designers, and managers work on building and maintaining these systems. If they want to excel, they also should have a strong understanding of the unique nature of corporate debt products and the type of analysis that end users want to undertake.

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