Introduction

The fixed income market has undergone significant structural changes during the past several years. Enhancements in information gathering, data synthesis, data analysis and trade execution continue to happen on an almost daily basis, creating trading and investment opportunities. Despite these advancements, fixed income trading has not reached the level of electronification currently seen in the equity markets. The sheer number of securities (thousands for equities versus millions for fixed income) plus diversity of asset types, security structures, settlement parameters, etc. have hindered progress on this front. As market participants become increasingly adept in processing and applying the vast amount of fixed income market information, that gap with the equity market (and others) is closing.

Fixed income investing has long been a story of price and yield. Forty years ago, it was still commonplace to look up prices/yields on tables or in books. Experienced traders or investors could look at a bond’s characteristics and do a rudimentary dollar duration (DV01) calculation in their head to consider market changes. Over time, those tasks became automated while at the same time bond structures became more complex, adding more variables like adjustable coupons, prepayments, and credit events. However, fixed income investing generally remained a bond-by-bond price/yield story. Investors in other asset classes, such as equities, FX, and futures, consider aggregate metrics, often referred to as technical analysis, to gain some market insight. In fixed income, at least in the United States, market participants looked to the Federal Reserve Board (the “Fed”) as to the future direction of interest rates, using a process that leveraged qualitative analysis as much as it did quantitative data. As the market reacts to the Fed, fund flows, individual credit events and various macroeconomic and geopolitical events, firms continue to search for ways to gain an edge. Though that edge may come in many forms, at ICE we try to provide data and analytics to help firms gain that edge. Firms with exposure to the fixed income market looking for transparency related to pricing, liquidity metrics, execution quality, transaction cost, market depth and market sentiment should think of ICE as a leading provider of this content. Furthermore, the content is made available from a simple, easy to understand single API access point.

The components of ICE’s Trading Analytics have been utilized for years in a variety of front, middle and back-office use cases. These include trading, price verification, business analysis, regulatory and risk management, among others. As market familiarity with the resultant data increased and new Trading Analytics components were added, new use cases have been developed. Given the progression of fixed income markets and the openness to leverage content sets like Trading Analytics, firms on the buy side and sell side are looking to incorporate the data elements into more systematic processes and workflows.

If a survey was conducted to include all the fixed income trading operations from all fixed income market participants, we would expect the results to show some similarities in processes, but each desk would have its own method for analyzing securities, markets, opportunities, etc. The market information employed would have many inconsistencies because different market participants would know different prices, yields and spreads for the same set of securities. The vast number of securities that comprise the fixed income market globally (millions versus thousands of equity securities) creates significant analytical challenges. The lack of centralized fixed income market data, along the lines of the Consolidated Tape in equities, exacerbates the inconsistencies seen in the fixed income market. This is the void that ICE Trading Analytics can help to fill.