Stockholm (HedgeNordic) – Systematic trading has historically thrived in the domain of exchange-traded securities such as equities, listed futures, and other highly liquid instruments. These markets, with their deep liquidity, high-quality data, and advanced electronic trading infrastructure, offer fertile ground for systematic models. However, the over-the-counter (OTC) nature of credit instruments, combined with the lack of quality data and transparency, has posed challenges for the adoption of systematic models in credit trading. Michael Hayes, Executive Director, Analytics Research at MSCI, believes that “a systematic revolution is brewing in fixed-income credit, and systematic credit will resemble systematic equity both in approach and in scale in the next five to ten years.”
‘Equification’ of Fixed Income
MSCI has discussed extensively “the equification of fixed income,” reflecting a long-anticipated and slow-to-materialize trend of convergence between equity and fixed income markets, driven by advances in liquidity, electronic trading, and data accessibility. “Early pioneers in systematic credit started investing in the early 2000s, but this revolution has been slow to materialize,” says Hayes. In his role as Analytics Researcher at MSCI, he works with various systematic fixed-income teams across asset managers and hedge funds, helping streamline investment processes and discover new sources of alpha. “The advancements in liquidity and electronic trading, along with the vast amount of readily available data and tools, have dramatically lowered the barriers to entry. The convergence between equity and fixed income is starting to take off and becoming mainstream.”
“The advancements in liquidity and electronic trading, along with the vast amount of readily available data and tools, have dramatically lowered the barriers to entry. The convergence between equity and fixed income is starting to take off and becoming mainstream.”
Michael Hayes, Executive Director, Analytics Research at MSCI
Fully automating a systematic credit strategy was once deemed impossible before the advent of electronic trading in fixed-income markets. “Increased electronic trading has definitely made automation possible,” says Hayes. Although electronic trading has been around for a while, he attributes the slow adoption to inertia. “There are many discretionary portfolio managers in fixed income, but relatively few systematic portfolio managers. This means newcomers have fewer mentors and need to be more entrepreneurial and innovative,” he continues. However, he sees a huge opportunity: “The opportunity will never be larger than it is right now.”
Hayes and his team at MSCI, “synonymous with quantitative equity investing since the 1970s,” have observed a significant influx of equity quants into the fixed-income space, bringing their ideas and toolkits with them. “This is revolutionary because equity and fixed income have historically been so different. But this migration of equity quants into fixed income brings an instant injection of a new perspective to the whole fixed-income world,” notes Hayes. Fixed-income portfolio managers approach factors differently compared to their equity counterparts. “As equity quants move into fixed income, they bring their decades of experience with multi-factor models, which is starting to really change the way that fixed-income portfolios are managed.”
“This is revolutionary because equity and fixed income have historically been so different. But this migration of equity quants into fixed income brings an instant injection of a new perspective to the whole fixed-income world.”
Michael Hayes, Executive Director, Analytics Research at MSCI
While credit and equity markets may be moving towards convergence, Hayes emphasizes that they will never fully converge due to fundamental differences between the two. “The two markets are never going to converge 100 percent, because there are fundamental differences between equity and fixed income,” emphasizes Hayes. “But these equity quants have all the skills required to succeed in systematic credit. They are adept at uncovering alpha, utilizing factor models, optimization techniques, electronic trading, and integrating these elements into a fully automated process,” he argues. Equity quants will continue to revolutionize the systematic credit investment process, according to Hayes.
Buy Versus Build
Many fixed-income managers already integrate systematic approaches into certain parts of their investment processes. With the trend of systematic credit investing gaining momentum, managers grapple with the question of whether to develop in-house capabilities or procure existing building blocks. MSCI has been building equity factor models since the 1970s and fixed-income models since the late 1980s. “We have had a succession of large quantitative research teams building those models initially and then improving them based on their own ideas and based on client feedback.”
“With decades of collective effort from various teams, coupled with ongoing client feedback, MSCI has made substantial investments in our models compared to a fund starting from scratch.”
Michael Hayes, Executive Director, Analytics Research at MSCI
“Some funds however opt to start from scratch, which involves hiring talent similar to what we have at MSCI and building something highly specialized,” explains Hayes. “With decades of collective effort from various teams, coupled with ongoing client feedback, MSCI has made substantial investments in our models compared to a fund starting from scratch,” he elaborates. While he acknowledges that for a highly unique or idiosyncratic investment universe, “off-the-shelf tools may not suffice for managers,” which could justify in-house development, “buying is typically a more cost-effective option” when considering a like-for-like comparison.
Extending MSCI’s Equity Quant Leadership
Hayes views systematic investment strategies as a four-stage process: “First, generate an alpha idea. Second, assemble the data and systems to implement it. Third, backtest the idea, and fourth, run the strategy using the same machinery as in step three.” While MSCI does not provide the idea for alpha generation, “we offer numerous building blocks that can feed into your idea,” says Hayes. These include tools offering insights into issuer curves, liquidity data, Merton implied spreads, equity factor descriptors, and a database linking equity and debt instruments at the issuer level.
MSCI also supports backtesting and implementation with a comprehensive multi-asset class factor model that covers fixed income in detail. “We have an optimizer custom-built for fixed income and a long history of liquidity data covering all transaction cost dimensions,” says Hayes. He also emphasizes MSCI’s strengths in equity factor modeling, which is relevant to systematic credit because of the fundamental connection between equity and credit, as formulated by Merton’s structural credit model. Empirical correlations reveal a connection between credit and equity in the most liquid segments of each market, notes Hayes.
“The wealth of equity data available to MSCI and the industry at large can be leveraged in the systematic credit process. This is the most untapped source of value in the industry.”
Michael Hayes, Executive Director, Analytics Research at MSCI
However, these correlations tend to break down at a more granular level. This phenomenon can be interpreted as either a breakdown of the Merton framework or as market inefficiency. Hayes leans towards the latter interpretation, believing that these markets will increasingly interconnect over time. What this implies is that “the wealth of equity data available to MSCI and the industry at large can be leveraged in the systematic credit process,” presenting a significant, yet largely untapped, source of value.
“This is the most untapped source of value in the industry,” reiterates Hayes. Equity factor descriptors, issuer characteristics, ESG scores, thematic scores, and peer similarity scores – all these elements can be integrated into the credit space, particularly within corporate credit. Moreover, this relationship works both ways, according to Hayes, who points out that this represents “a two-way street, where MSCI also has a wealth of fixed-income data, both at the issuer and the security level.”
