What are the key pain points associated with fixed income markets specifically?
Fixed income encompasses a complex set of financial instruments with great breadth, depth and diversity. When you look at how this asset class is moving into the automated trading space, there is a high degree of fragmentation. While almost 50% of corporate bonds are trading electronically, other areas of the asset class are still marked by manual workflows and are at the more initial stages of automation.
Fixed income also has a high degree of diversity within the sub-asset classes, which are each marked by unique characteristics and challenges. Speaking of fixed income as one asset class almost does not do justice to the complexities that are faced in the space.
However, some areas of fixed income are growing very fast. If we look at the rise of ETFs, these vehicles are providing bond fund managers much more flexibility to be able to access and work in the space. Pricing data has also become much more available for investors to jump in and out of corporate bond positions. Players in the space are working to keep up with these changes, while also maintaining the legacy systems and complex workflows that are in place.
What role does real-time data play in helping combat these issues?
Real-time data enables more automated signals in fixed income – especially critical is API access to multiple signals simultaneously. Looking at the growth in the primary issuance space, where we see year-on-year volumes growing rapidly, the timelines on the first day of issuance are really condensing. This compression has made the space much more efficient, but it has also raised the stakes, making data accuracy and integrity key.
To address this, Bloomberg’s New Issues Feed provides real-time updates on all of the different stages of bond issuance as they happen programmatically to enable users to make decisions in real-time, accurately and with confidence. Being able to do this in a cost-effective way across different asset classes – such as corporate bonds, treasuries and loans – solves historic workflow pain points around data integrity and operational risk which were previously addressed with ‘dummy instruments.’ Firms previously needed to manage a huge clean up exercise as well to maintain the integrity of their data and make sure that they were confident with any trades that were executed in this space. With real-time data, firms can ensure data integrity in compressed timelines in ways they weren’t able to before.
What are the key factors driving this compression of the fixed income trade lifecycle?
The increased number of players in fixed income is driving greater automation and the use of API trading. The SEC’s approved rule changes to require most fixed income and municipal trades to be reported within one minute of execution, tightening the current 15-minute reporting standard, is also an evolutionary change for anybody in this space.
In light of these shifts, industry participants would be wise to reassess the entire workflow as it relates to fixed income, identifying all manual and back-office processes and working to automate them as much as possible to drive faster decision-making. Real-time data consumed via API can provide a consistent view of multiple data points concurrently. As an example, in the New Issues workflow, if a bond is announced and a firm has interest, they can programmatically subscribe to an intraday pricing service like IBVAL and receive a price indicator for that bond within 15 minutes. This allows for much more confidence in the trading decision. Real-time solutions provide the API framework to tie together all parts of the fixed income trade lifecycle – from new issuance into trading, back into execution, and finally for reporting back to relevant agencies – eliminating fragmentation between different stages of a trade.
How can those in the market adapt to more in a much shorter period of time?
Taking pricing data as an example, historically this type of data consisted largely of voice transactions. But today, we see a lot of clients using Bloomberg’s MSG1 tool, which brings together IB, email and pricing information and provides a real-time feed of this data across a customer’s firm to give group-wide internal transparency on where the pricing is. This can then be aligned with broker pricing and data from reporting feeds to provide even greater value.
Broadly, industry participants must be able to bring together disparate pieces of information, whether that’s a model price like IBVAL, a price indicator price (PIP), pricing internal to a firm, or trade reporting feeds like MSRB or SDR. Then, eliminating manual consolidation and reconciliation of these prices and enabling programmatic processing is essential for efficiently operating within today’s increasingly compressed fixed income trade lifecycle.