Putting It All Together: Systematic Fixed Income Portfolios in Action
You made it to the final chapter. Ten chapters of signals, risk models, portfolio construction, trading costs, and sustainability considerations. Now the question is simple: does all of this actually work?
Richardson answers by showing hypothetical results across multiple systematic fixed income portfolios. And the numbers are pretty convincing.
The Setup
These are not backtests cherry-picked to look good. Richardson constructs representative systematic portfolios across several fixed income categories. The same ones we saw traditional managers struggle with back in Chapter 4. Every portfolio uses the full toolkit from the book: carry, defensive, momentum, value, and sentiment signals. Every portfolio uses proper risk management and beta completion. Returns are gross of management fees but include transaction cost estimates.
The key question is not just “can you beat the benchmark?” It is “can you beat the benchmark without just loading up on credit risk?” Because as Chapter 4 showed, that is what most active managers do. They dress up credit beta as alpha and charge fees for it.
Systematic IG Corporate Bonds
First up: investment grade corporate bonds. Richardson benchmarks a systematic global IG portfolio against the Bloomberg/ICE global corporate indices, targeting about 1% tracking error.
The results? An information ratio of 0.75. That means for every 1% of active risk, you get about 75 basis points of alpha. Run it at 100 bps of tracking error and you get 75 bps of excess return.
But here is the part that matters most. The R-squared between the systematic portfolio’s excess returns and the credit premium is just 0.54%. Basically zero. The slope coefficient is slightly negative and not statistically significant. This portfolio is not sneaking in credit beta. The alpha is real, idiosyncratic, security-selection-driven alpha.
Compare that to the Core Plus funds from Chapter 4, where the correlation to the credit premium averaged 0.72. Night and day.
Long Duration IG Corporate Bonds
Pension funds love long duration corporate bonds because they match liability cash flows. Richardson shows the systematic approach works here too.
The information ratio is 0.73 with about 1.5% tracking error. At that risk level, you are looking at roughly 110 basis points of alpha. Again, the R-squared against the credit premium is tiny at 1.13%. The slope coefficient is negative and insignificant.
Long duration bonds are a big market. Over 3,000 bonds in the typical long duration benchmark. Plenty of room for systematic security selection to operate.
High Yield Corporate Bonds
High yield is where things get interesting. This is the asset class most dominated by credit risk, so staying neutral to the credit premium is harder.
The systematic HY portfolio delivers an information ratio of 0.88 with about 2% tracking error. That translates to roughly 176 basis points of alpha. There is a small positive slope against the credit premium (0.0354), but it is not statistically significant (t-stat of 1.79). The R-squared is just 1.26%.
So even in high yield, where credit beta is everywhere, the systematic approach manages to generate returns that are mostly independent of the credit cycle. Traditional HY managers cannot say the same.
Credit Long/Short
Now for the big leagues. Richardson constructs a systematic credit long/short portfolio using CDS contracts and cash instruments across developed markets. This one targets 6-8% of active risk.
The information ratio hits 1.27. At 700 bps of risk, that is 889 basis points of alpha. The Sharpe ratio is 1.30.
And the credit premium exposure? The R-squared is just 0.93%. The slope is positive but statistically insignificant.
Remember those 51 discretionary credit long/short hedge funds from Chapter 4? They had similar Sharpe ratios (1.09 average), but more than half of their excess returns came from passive credit beta. The systematic version preserves almost all of its returns after controlling for traditional risk premia. The discretionary version does not.
That is the difference between real alpha and repackaged beta.
Emerging Market Bonds
The systematic EM portfolio focuses on hard currency bonds from sovereign and quasi-sovereign issuers. It targets about 2% tracking error, which is lower than the typical discretionary EM manager (who runs closer to 3.5%).
Information ratio: 1.02. At 200 bps of risk, that is 204 basis points of alpha. The correlation to the credit premium is essentially zero (0.03). Even after controlling for the full set of EM risk factors (term premium, EM spread, EM corporate, EM FX), the information ratio stays at 0.98.
Global Aggregate
Combine rate-sensitive and credit-sensitive security selection into one portfolio. Benchmark it against the Bloomberg Global Aggregate. Target about 1.5% tracking error.
Information ratio: 0.91. That is 137 basis points of alpha at the target risk level. The credit premium correlation is just 0.11. After adjusting for the full set of risk premia (term, credit, EM, FX, volatility), the information ratio is 0.71.
Unconstrained Bond Portfolio
This is the category where traditional managers embarrass themselves the most. Chapter 4 showed that unconstrained bond funds saw an 85% reduction in returns after stripping out beta. They marketed “go anywhere” flexibility but really just loaded up on credit.
The systematic version is different. Yes, there is some credit premium exposure (R-squared of 6.58%, higher than the other systematic strategies). That is expected because the unconstrained strategy deliberately captures some traditional risk premia. But the alpha still holds up. The information ratio is 1.41 before beta adjustment and 0.91 after the full adjustment.
Compare that to the incumbent unconstrained funds: 4.09% raw returns collapsed to just 0.57% after beta removal. The systematic version keeps most of its returns intact.
The Scoreboard
Here is how all the systematic portfolios stack up:
| Portfolio | Information Ratio | Tracking Error | Alpha (bps) | Credit Premium R-squared |
|---|---|---|---|---|
| IG Corporate | 0.75 | ~1.0% | 75 | 0.54% |
| Long Duration IG | 0.73 | ~1.5% | 110 | 1.13% |
| HY Corporate | 0.88 | ~2.0% | 176 | 1.26% |
| Credit Long/Short | 1.27 | ~7.0% | 889 | 0.93% |
| Emerging Markets | 1.02 | ~2.0% | 204 | 0.12% |
| Global Aggregate | 0.91 | ~1.5% | 137 | 1.23% |
| Unconstrained | 1.41 | ~5.0% | 705 | 6.58% |
Every single portfolio shows strong information ratios. And nearly all of them show near-zero correlation to the credit premium. That is real diversification.
Why This Is a Big Deal
The whole point of the book comes together in this table. Traditional active managers beat benchmarks, sure. But they do it by taking on credit risk that investors could get cheaply through passive products. Systematic approaches beat benchmarks through security selection that is genuinely different from what everyone else is doing.
Richardson also looks at holdings data from 154 HY mutual funds to prove this point from a different angle. He measures how similar each fund’s active positions are to what a systematic process would hold. The average mutual fund has near-zero similarity. The systematic fund is a complete outlier. It is doing something fundamentally different.
Richardson’s Parting Advice
The chapter closes with career advice for anyone considering systematic investing. A few highlights:
Embrace failure. Most investment ideas will not work. That is fine. The danger is when someone pressures you to change the model by a quota. Only add ideas that are conceptually grounded and empirically additive.
Watch for data mining. Keep a graveyard of failed ideas. If you only celebrate wins and bury the losers, you will fool yourself. Track everything you tried, not just what worked.
Manage culture clashes. Systematic teams need both deep asset class knowledge and strong data analytics skills. Rarely found in one person. Hire for both, but set clear expectations.
Communicate well. Discretionary managers can tell stories about each position. Systematic managers have 500 positions driven by four signal categories. Learn to explain your process clearly and provide deep attribution. The best systematic managers will be the ones who can explain what they do to asset owners who are used to narrative-driven investing.
Stay humble. Markets are mostly efficient. Your edge, if you have one, needs constant questioning. And if you truly believe markets are fully efficient, maybe do not work in active management. Put your money in Vanguard and call it a day.
Richardson ends the book with a call to action: systematic fixed income is a tiny fraction of the active bond market today. The data says it deserves to be much larger. It is good for investors. It is good for asset owners. And there is a lot of room to grow.
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Next: Final Thoughts on Systematic Fixed Income
Book: “Systematic Fixed Income: An Investor’s Guide” by Scott A. Richardson, Ph.D. Published by John Wiley & Sons, 2022. ISBN: 9781119900139.