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The leading knowledge platform for the financial technology industry

A-Team Insight Blogs

Fixed Income with Electronic Trading

In the world of electronic trading, fixed income has seen slow uptake compared to equities and foreign exchange, mainly due to the much more complicated types of underlying financial calculations – which can require many minutes, sometimes even hours of processor time.  This stands in marked contrast to electronic trading of equities or foreign exchange (“FX”), where the amount of calculation is minimal and the prime limiting factor on winning trades is the speed of data movement between applications in the network.

Fixed income securities present a different computing challenge because their pricing models require lots of calculation, including many factors – obviously, the price of the bond, plus the financial health of the issuer (government, corporation) or underlying securities (such as a bundle of mortgages), the latest interest rate announcements, trade balances, GDP projections, fluctuations of the currency the bond is sold in, etc.

But over the last few years, more and more investment banks and other electronic trading concerns have started to re-evaluate the positives and negatives of automated electronic trading for fixed income, especially for certain types, such as Treasuries (up to 80% are currently traded electronically) and mortgage-backed securities (40-50%).

And while it might seem counter-intuitive, low latency messaging is still an important part of the equation.

Consider: what if the application that needs an hour for computing time alone must also retrieve data from many other applications, many many times during that series of calculations, lengthening the overall execution time by minutes, if not hours?  In that case, saving microseconds (or even milliseconds) per data retrieval call can add up very quickly and result in much faster overall execution.

What about other types of applications, that do not rely on a large number of calls to other applications for data?  For these, there is still another consideration: if your competition is using faster messaging middleware than you are, that could mean that your competition is also winning more trades than you are, directly affecting your revenue and bottom line.  You aren’t so much racing the clock as racing every other application receiving the same market data.

And then there are the day-to-day costs of messaging middleware systems.  The state of the art today is peer-to-peer messaging middleware (such as Informatica Ultra Messaging) which runs at the outer limits of your given hardware and software configuration by removing messaging choke points such as brokers and daemons found in older, legacy systems.  So even if we ignore performance for a moment, such a system is usually more reliable (no single points of failure) and cuts down on IT fixed and operational costs.  And when you need more capacity or bandwidth, you just add more resources in the form of servers or an upgraded network, and the software scales right along with it.

So even though calculations chew up most of the resources for fixed income pricing, there are multiple ways that the latency of the messaging middleware system can still be a factor. As with equities and FX, that latency advantage could be the difference between finishing first and winning the trade, or finishing tied for last and losing the trade.

For more about fixed income use cases with electronic trading, Informatica Ultra Messaging invites you to attend a New York City event on June 7, “Low Latency and Beyond: Building a Modern, Reliable, and Ultrafast Messaging Architecture”.  Register here

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