Systematic Fixed Income Portfolios: Real Results for IG, HY, and Credit Long/Short
Book: Systematic Fixed Income: An Investor’s Guide Author: Scott A. Richardson, Ph.D. ISBN: 9781119900139 Publisher: John Wiley & Sons, 2022
This is the chapter we’ve been building toward. All those signals, all that portfolio construction talk, all the liquidity analysis. Now Richardson puts it together and shows what systematic fixed income portfolios actually look like in practice.
And the results are pretty striking.
The Setup
Every portfolio examined here is hypothetical but representative of what a well-built systematic process could deliver. Returns are gross of management fees but include transaction cost estimates. Richardson looks at the same categories from Chapter 4 where he analyzed active manager performance. The key question throughout: can a systematic approach beat the benchmark without just loading up on credit beta?
Systematic IG Corporate Bonds
A systematic global IG corporate bond portfolio benchmarked to something like the Bloomberg Global Aggregate Corporate Index. Target active risk: about 1% tracking error.
The portfolio uses the full toolkit: carry, defensive, momentum, value, and sentiment signals. It selects attractive issuers within peer groups and attractive issues within issuers. And it carefully manages beta exposure across countries, currencies, ratings, industries, and maturities through completion trades.
So how did it do? Richardson shows a scatter plot of the portfolio’s excess returns against the credit premium. There’s basically no relationship. The R-squared is just 0.54%, and the slope coefficient is slightly negative (not significant). The annualized intercept is 0.97%, with residual volatility of 1.29%. That gives an information ratio of 0.75.
At 100 basis points of active risk, that translates to 75 basis points of alpha. And the information ratio (0.75) is nearly identical to the Sharpe ratio (0.71). That means the excess returns are coming from security selection, not from sneaking in credit beta. This is exactly what you want from a systematic approach.
Long Duration IG Corporate Bonds
Pension plans love long-duration corporate bonds. They need them to match their liability cash flows. A systematic process can easily adapt to focus on USD bonds with 10+ years to maturity.
The universe is smaller but still over 3,000 bonds. Target active risk is a bit higher at 1.5%. The results follow the same pattern: no meaningful correlation with the credit premium (R-squared of 1.13%), and an information ratio of 0.73. At 150 basis points of active risk, that’s about 110 basis points of alpha.
Again, the IR roughly matches the Sharpe ratio (0.69), confirming the alpha is genuine security selection, not disguised beta.
Systematic HY Corporate Bonds
High yield is where things get more interesting because the asset class is riskier and less liquid. Active risk runs around 2%.
The systematic HY portfolio shows a small positive association with the credit premium, but it’s not statistically significant (t-stat of 1.79, R-squared of 1.26%). The information ratio comes in at 0.88, which is even better than IG. At 200 basis points of active risk, that’s 176 basis points of alpha.
The IR (0.88) and Sharpe ratio (0.91) are closely aligned. So even in high yield, where most active managers are basically selling credit beta as alpha, a systematic approach can deliver actual security selection returns.
Credit Long/Short: Where It Gets Really Interesting
A credit long/short strategy uses CDS contracts and cash instruments to go both long and short individual credits. It can also trade aggregate credit at the index level and across the capital structure. The active risk here is much larger: 6-8% annualized.
Richardson shows an information ratio of 1.27 for the systematic credit long/short portfolio. At 700 basis points of active risk, that’s 889 basis points of alpha. The Sharpe ratio is 1.30, very close to the IR, confirming minimal beta contamination.
Here’s the thing that really matters. Remember those 51 credit long/short hedge funds from Chapter 4? They had an average Sharpe ratio of 1.09 with about 9% active risk. Sounds good, right? But more than half of their excess returns came from passive beta exposure to the credit premium. They were basically charging hedge fund fees for credit beta.
The systematic approach generates similar total returns at similar risk levels but preserves its alpha after controlling for beta. That’s a huge difference. One is genuinely skilled investing. The other is an expensive way to get market exposure.
The US Aggregate Strategy
Richardson also mentions a systematic approach to the broader US aggregate space. The Core Plus US aggregate managers from Chapter 4 had a Sharpe ratio of about 0.34 with modest excess returns. But most of their outperformance came from out-of-benchmark tilts into credit and other spread sectors, basically taking more risk than the benchmark.
A systematic approach to this space can select bonds across the full aggregate universe (government, corporate, securitized) while maintaining proper risk neutrality. The alpha comes from picking better bonds within each sector, not from overweighting riskier sectors.
Why the Alpha Is Real
Across all these portfolios, there’s a consistent pattern. The information ratio is always close to the Sharpe ratio. That happens because:
Signals are built to be neutral to market risk premia. The carry signal, for example, isn’t just “buy the highest-yielding bonds.” It’s designed to isolate the component of carry that isn’t compensation for default risk or duration risk.
The optimizer enforces neutrality. Constraints on sector, rating, maturity, and country exposure, plus beta completion trades, ensure the portfolio doesn’t drift into systematic beta bets.
The result is a portfolio that genuinely looks different from both the benchmark and from discretionary managers. It’s not correlated with the credit premium in a meaningful way. And that makes it a powerful diversifier for asset owners who already have credit beta through their existing fixed income allocation.
What This Means for Investors
If you’re an asset owner allocating to fixed income, these numbers tell a clear story:
- Systematic approaches can generate meaningful alpha (0.75 to 1.27 IRs across categories)
- That alpha is largely uncorrelated with traditional risk premia
- The approaches scale well across IG, HY, long duration, and long/short formats
- Most discretionary managers in these categories are delivering beta dressed up as alpha
Richardson doesn’t claim these are guaranteed results. They’re based on backtested hypothetical portfolios from 2000-2020. But the logic is sound: broad, diversified signal sets applied systematically with disciplined portfolio construction can extract returns that discretionary processes miss.
The opportunity exists precisely because systematic fixed income is still small. As we learned in Chapter 1, only a tiny fraction of active fixed income is managed systematically. That leaves a lot of room for well-built systematic processes to find opportunities that the market hasn’t fully priced.
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