Fixed income’s digital revolution has arrived, it’s time to adapt
Systematic fixed income approaches are finally hitting the mainstream. For those starting to incorporate them, it is important to seek managers with a long and proven pedigree.
Barclays research estimates that $90 billion to $140 billion of capital is being managed in systematic credit vehicles and that their popularity has really exploded over the last two years.
My team has been there from the beginning, developing systematic fixed income approaches since 2001. We see many reasons to be excited about the long-awaited technological revolution in bonds.
It has been a long road
Systematic investing in equities has a rich history, intertwined with the frontier of investment thinking.
In the late 1960s and in my hometown of San Francisco, a gentleman called John McQuown engineered the indexing revolution. He collaborated with a lot of the leading lights of academia, such as future Nobel-winning economists like Harry Markowitz, William Sharpe and Eugene Fama (names most of us are familiar with).
In 1973, William (Bill) Fouse and Thomas (Tom) Loeb ran the first equity indexing strategy to make use of quantitative factors. Things then went up a gear in the 1990s when Nobel-winning economist Eugene Fama published his influential three-factor model in 1992.
All the while, the end of the Cold War meant that mathematicians and scientists were less employable for national security purposes, and many turned to a booming Wall Street instead. The word “quant” entered the financial lexicon, and factor-based investing became increasingly common in equities into the 2000s.
Today, there are even online communities about building systematic equity strategies that almost anybody can participate in.
But throughout this period, bond markets remained old-fashioned by comparison. Only in the last 10 years have technological innovations made systematic strategies possible in fixed income.
Liquidity breakthroughs have allowed for systematic bond strategies
The main reason fixed income has been technologically left behind is liquidity. Investors can trade equities at a penny-wide spread, making it easy to set up a model-based approach.
But in bonds, a lot of trading is still done over-the-counter (OTC), which has only become more costly with time due to increased bank regulation since 2008.
For example, in US high yield, two-thirds of bonds are unlikely to trade on a given day and it can take days or even weeks to complete an order. In the US high yield market, our analysis of the eVestment database shows that most passive strategies only tend to hold 60 per cent of available bonds in the index, concentrating on the most liquid issuers.
It took the rise of fixed income ETFs to change the game. Over a decade ago we pioneered 'credit portfolio trading', a separate trading protocol which aims to unlock 'hidden liquidity' within the ETF ecosystem.
Instead of trading bonds one at a time, credit portfolio trading involves trading 'baskets' of bonds, potentially 500 or 1,000 at a time, with ETF dealers rather than traditional brokers. ETF dealers treat the trades as if they are ETFs, because they look and feel similar to the indices they are tracking, but we build in micro, undetectable, underweight and overweight tilts into every basket to match our desired portfolio exposures. It does not involve trading ETFs themselves but working within the underlying ETF ecosystem to transact in a specific way.
We find we can bring US high yield transaction costs from 60bps to 70bps down to 10bps to 20bps, while trading as much as $500 million daily, with execution times from minutes to hours, even for less traded and traditionally illiquid bonds (v days or weeks utilising the more traditional OTC trading approach). We find that we can also execute the exact same basket trade for $5 million or $500 million.
An additional benefit is that this can allow us to receive the 'illiquidity premium' embedded in high yield credit spreads for 'free', given we find we can trade them fluidly and efficiently.
Systematic models offer potential diversification against traditional strategies
We believe systematic approaches can complement and diversify traditional strategies.
Systematic US high strategies, for example, can look very different to traditional portfolios. They can contain up to 90 per cent of the broad US high yield index, whereas traditional active strategies hold just 15 per cent to 30 per cent (based on our analysis of the eVestment database from April 2013 to March 2023).
This is partly liquidity-related, but also a result of manpower restrictions. Hiring skilled credit analysts is expensive and their research takes time. Realistically, even a large credit team is only covering a fraction of the 900 issuers in the US high yield bond universe. They are typically focusing on the largest, most traded issuers, in other words the same names that everyone else is focusing on, as alpha positioning tends to be relatively concentrated.
However, the beauty of computers is that they are tireless, fast and repeatable, so analysing an entire bond universe is no big deal. The trade-off, of course, is that a model cannot offer the in-depth qualitative insights of a knowledgeable credit analyst.
Historically, our systematic US high yield strategy has had an alpha correlation of less than 0.25 with 90 per cent of the fundamental active US high yield manager universe (based on our analysis of the eVestment US high yield fund universe from April 2013 to March 2023) and a negative correlation with 60 per cent of it.
Be prepared for fixed income’s digital revolution
We expect the growth of systematic fixed income strategies to continue. However, we believe investors need to work with those with proven credentials, experience and track record of applying systematic investing to fixed income.
Any model needs to be well-calibrated with a sufficient quality of data. Credit models are not new, albeit infamously difficult to practically implement. For example, Robert Merton’s 'Merton model', designed to pinpoint a company’s default risk, was published back in 1974. But it needs tweaking for use in the real world, so due diligence on managers implementing these processes is essential.
If you have not already, it is time to think about how systematic fixed income might help you better address the challenges you face, potentially be delivering more reliable returns and enhanced liquidity.
Don’t miss out on the digital revolution in bonds.
Paul Benson is head of systematic fixed income at Insight Investment.
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