Fixed income automation is transforming the role of the trader without replacing human ability. A Refinitiv report explores the benefits of AI, cloud computing and big data.
- How firms harness fixed income automation and put their available data to work will be a key determinant in their future success.
- A Refinitiv report points to the creation of a ‘virtuous cycle’ in which better data has facilitated more e-trading, which has in turn created more data.
- Fixed income automation has not been designed to replace humans, but rather to augment their abilities and enable them to become more efficient and effective.
Traditionally, success in fixed income markets was largely determined by trader intelligence and intuition, but the exponential growth of automation has changed the fixed income landscape beyond all recognition.
Machines can now pinpoint potential opportunities within seconds and highlight nuggets of relevant information hidden deep within pools of data.
More and more firms are embracing this technology: A significant 61 percent of market participants say they are either using artificial intellgence today or plan to in the next 12-24 months.
The transformation underway has already begun to alter the role of the trader, but not in terms of replacing human ability.
The trading function of the past has evolved from essentially generating and implementing ideas into interpreting and assessing the potential opportunities discovered by algorithms.
Our latest report concludes that “portfolio managers, traders, salespeople, and research analysts will all feel the shift”.
The value of fixed income data
The past decade has seen significant amounts of both time and money invested into gathering, generating and cleaning up fixed income-related data.
Our research points to the creation of a “virtuous cycle”, in which better data has facilitated more e-trading, which has in turn created more data.
How firms put this data to work will be a key determinant in their future success, and technology is stepping up to the plate to enable market participants to extract maximum value.
Cloud computing has already leveled the playing field by opening up low-cost compute power and data storage to everyone. All market participants can now rapidly prototype new algorithms and investment ideas, and perform deeper analysis of available data.
Advances in deep learning techniques and natural language processing have further unlocked the potential in data that was previously dirty or too unstructured to allow proper analysis.
For example, these technologies allow client preferences to be extracted from phone calls and used to automatically generate future recommendations.
Furthermore, the growing adoption of accessible, user-friendly programming languages like Python has delivered innovation straight to the trading desk.
Municipal bond pricing
These sweeping changes have already solved many of the on-the-ground challenges faced by market participants.
For example, in the municipal bond market about one percent of an estimated one million securities trade with sufficient frequency to enable accurate pricing.
Our report highlights that, in the past, the other 99 percent could only be priced through “educated guessing and basic bond math”.
The good news is that today, readily available data and leading-edge technology mean that nearly every bond in this universe can be priced every few minutes, with clear advantages for all market participants.
Moreover, accurately predicting the risk of default for any given bond has become far easier, as risk analytics can now factor in numerous inputs to form a holistic and accurate picture of risk.
The role of fixed income automation
We expect the transformation of the fixed income space to continue on its exponential trajectory.
If anything, the frenetic pace of innovation is set to accelerate, and this will drive further fixed income automation, in the process contributing to ever-greater levels of market efficiency and transparency.
This is good news for market participants, and should not be viewed as the death knell for the role of humans on the trading desk.
Rather, we should expect ongoing changes to some roles, and a shifting focus.
For example, the industry has already witnessed a steady move away from MBA graduates and towards computer and data scientists. This is nothing new and has been a steady trend over the past 20 years.
Essentially, our latest research seeks to convey an important message: Technology and data have the power to augment and support human ability and should be viewed as powerful tools for future success.