How Active Fixed Income Managers Really Perform: The Case for Systematic Investing
You know those fund managers who claim they’re beating the market with skill? Richardson basically pulls back the curtain in Chapter 4 and says: most of them are just loading up on credit risk. That’s not alpha. That’s beta wearing a fancy suit.
This chapter is a reality check for anyone paying active management fees in fixed income. And the data is pretty hard to argue with.
What Active Bond Managers Actually Do
Before getting into the numbers, Richardson lays out five ways active fixed income managers try to earn their keep:
Avoiding bad selling practices. Bonds constantly enter and leave indices. Smart managers don’t sell just because an index rule forces them to. They hold shorter-dated bonds others dump. They hang onto “fallen angels” (bonds downgraded from investment grade to high yield) when everyone else panic-sells at depressed prices.
Asset allocation decisions. This means timing the market. Tilting toward certain sectors, adjusting duration, moving between geographies. Richardson reminds us (with a brutal chart) that professional forecasters are terrible at predicting interest rates. The average error in their one-year-forward yield forecasts is about 1%. Given duration of around 8, that’s roughly -8% annualized returns if you traded on those forecasts. Humbling is the word he uses.
Out-of-benchmark tilts. Loading up on stuff not well-represented in the benchmark. High-yield corporate bonds, bank loans, emerging market debt, collateralized debt obligations. Sounds like diversification, right? But here’s the thing. Richardson shows these out-of-benchmark sectors are all highly correlated with each other (correlations of 0.80 to 0.86). They’re basically all just credit risk in different packaging.
Liquidity provision. Being the one who provides liquidity instead of demanding it. This actually generates real returns, especially in corporate bonds where trading is expensive.
Security selection. Picking individual bonds that will outperform. This is what the rest of the book focuses on.
Most managers talk about all five. But when you look at the actual returns, one pattern dominates everything else.
Core Plus US Aggregate Funds: The Credit Beta Machine
Richardson analyzes 142 Core Plus funds from the eVestment database (covering 97% of the $1.7 trillion in this category). He runs regressions on their returns against traditional risk premia like the term premium, credit premium, and emerging market factors.
The headline numbers look great. Average active return of 1.18% per year. Average Sharpe ratio of 0.54. Impressive on paper.
But then you look under the hood.
The average correlation between these funds’ active returns and the credit premium is 0.72. That’s not a small number. That’s a massive tilt toward credit risk.
When Richardson strips out the passive beta exposure, that 1.18% active return shrinks to just 0.41% of actual alpha. That’s a 65% reduction. Most of what looked like skill was just taking on more credit risk than the benchmark.
Global Aggregate Funds: Same Story, Different Geography
For global aggregate funds (94 funds, $355 billion), the pattern repeats with some variation.
Average active return: 0.77% per year. Average Sharpe ratio: 0.26. The credit premium correlation is lower at 0.29, but these managers also pick up emerging market and volatility premiums.
After removing beta exposures, alpha drops from 0.77% to 0.57%. A 25% reduction. Better than Core Plus, but the passive beta story still holds.
Unconstrained Bond Funds: Where Beta Dressing Is Most Extreme
This is where it gets really interesting. Unconstrained bond funds (103 funds, $450 billion) are marketed as the “go anywhere” strategies. No benchmark constraints. Pure skill.
The raw numbers are eye-catching. Average active return of 4.09% per year with a Sharpe ratio of 0.74. Sounds amazing.
But the credit premium correlation is 0.63. These “unconstrained” managers are actually very constrained. They’re constrained by their love of credit risk.
After stripping out beta exposures, that 4.09% collapses to just 0.57% of alpha. An 85% reduction. Richardson calls this category out directly: “This is one category of active fixed income management in which the repackaging of beta as alpha is both very large and very pervasive.”
Let that sink in. You’re paying active management fees for a fund that could be roughly replicated by a few passive credit exposures.
Emerging Market Bond Funds
For EM bond managers (117 funds, $355 billion), the active return averages 1.04% with a Sharpe ratio of 0.29.
After removing traditional risk premia, alpha drops to 0.54%. A reduction of just over 50%. The beta capture is less extreme here, but still meaningful.
Credit Long/Short Hedge Funds: Even the “Sophisticated” Guys
Now for the hedge funds. Richardson looks at 51 live credit long/short funds from the HFR database. These are the sophisticated players. And returns are net of fees (unlike the previous categories which were gross of fees).
Average excess return: 8.66% per year. Average Sharpe ratio: 1.09. Truly impressive. But there’s survivorship bias here since these are all still-living funds.
The correlation between these hedge funds and the credit premium? 0.66 on average. The median is even higher at 0.79. The scatter plot Richardson shows has a full-sample correlation of 0.83 between average credit hedge fund returns and US high-yield credit excess returns.
After removing beta, alpha falls from 8.66% to 3.85%. A 55% reduction. And Richardson asks the question everyone should be asking: is that worth a 2/20 fee structure?
He also makes an important timing point. Most of these funds have track records averaging about 10 years, corresponding roughly to the 2010-2020 period. During that window, the credit premium delivered a 0.54 Sharpe ratio. These managers happened to be long credit during a great period for credit. Lucky timing isn’t skill.
The Big Picture
Here’s the pattern across every single category Richardson examines:
| Fund Category | Active Return | Alpha After Removing Beta | Reduction |
|---|---|---|---|
| Core Plus (US Agg) | 1.18% | 0.41% | 65% |
| Global Aggregate | 0.77% | 0.57% | 25% |
| Unconstrained Bond | 4.09% | 0.57% | 85% |
| Emerging Market | 1.04% | 0.54% | ~50% |
| Credit Long/Short | 8.66% | 3.85% | 55% |
The message is consistent. Active fixed income managers are reaching for yield through credit exposure. Asset owners know about this behavior but probably underestimate how widespread it is and how much it inflates reported performance.
Why This Matters for Systematic Investing
Richardson sets up the rest of the book with a challenge. Can systematic approaches do better? Specifically, can they:
- Generate excess returns over the benchmark
- Do so with low correlations to traditional risk premia (especially credit)
If systematic investing can deliver both, it would be genuinely valuable to asset owners. Not because it replaces credit exposure (investors can get that cheaply through passive products), but because it provides something actually different. Real alpha that diversifies away from the credit beta everyone else is already loading up on.
The next chapters will focus on security selection within rate-sensitive bonds, credit-sensitive bonds, and emerging market bonds. That’s where the real test begins.
Previous: Tactical Asset Allocation in Fixed Income
Next: Selecting Rate-Sensitive Bond Securities
Book: “Systematic Fixed Income: An Investor’s Guide” by Scott A. Richardson, Ph.D. Published by John Wiley & Sons, 2022. ISBN: 9781119900139.