Elusive Alpha in Fixed Income

Instead of delivering alpha, historical data shows that the performance of core and core plus fixed income managers is simply a function of having more risk versus the benchmark over time.

Most people believe that active fixed income managers are better at delivering alpha than equity managers. The data says otherwise.

Yes, the average fixed income manager in the core space delivers excess return but that excess return consists largely of beta. Alpha and excess return are often confused but what you want from a manager is return due to that manager’s idiosyncratic skill – that’s the alpha. That’s special and worth a premium. The beta is the manager’s exposure to the market. That’s not so special.

With more beta comes more market risk, and your fixed income bucket begins to look a lot less like a risk diversifier. Allocation cost/benefit equations shift as you weigh the risk/reward and fee structure of beta in other asset classes.

We believe that it pays to understand the composition of your return, if only to price that return correctly. We also believe that some managers are better at delivering alpha. It pays to find those managers.

First, Let's Define the Market

The Universe

• In Core Fixed Income, the market is the benchmark: the US Bloomberg Aggregate (the Agg) that includes ~27 trillion dollars of investment grade (BBB or higher rated) bonds, issued in the US that meet some size and maturity constraints.

• The Agg can be broken down largely into three sectors: US Treasuries, Corporate Bonds and Securitized Bonds (almost entirely mortgage-backed securities issued by Fannie Mae, Freddie Mac and Ginnie Mae).

The Potential Outcomes

• Owning Treasuries gets you yield and upside in risk-off environments (with the exception of periods where higher rates become the risk-off driver — see 2022)

• Owning Corporates gets you more yield than Treasuries but introduces credit risk. On a sector level the credit risk is minimal – default rates in the investment grade corporate space are close to nothing, but it’s still worth something versus Treasuries.

• Owning Mortgages gets you more yield than Treasuries but introduces convexity risk, which is similar to the risk of being short volatility.

Typical Core Fixed Income Investment Approaches

Core managers have an abundance of options for alpha generation:

• Sector rotation: Overweighting and underweighting Treasuries, corporates and / or MBS.

• Yield curve and interest rate exposure: Modifying duration to be long or short versus the Agg and modifying weights to different parts of the interest rate curve.

• Security selection: Overweighting and underweighting specific securities within each sector (extensively referred to as a bottom up approach and one of the most common alpha advantages cited by Core managers).

• Out of benchmark exposure: Allocating to securities that are not included in the Agg, such as high yield.
  

Excess Return is Not all Equal

A Modern Approach to Investing

Deconstructing active Core Fixed Income excess return into its components can be done a number of ways. For an approach that dissects the risk premia inherent in a core manager’s excess return, see AQR’s The Illusion of Active Fixed Income Alpha.

Essentially AQR uses a linear regression methodology to attribute returns across traditional risk premia. Once the risk premia are stripped out there’s not much left. For the period 1997-2018, out of the 50bps annualized excess return of AQR’s Bloomberg US Aggregate manager cohort, only 10 bps remain as alpha. The paper concludes that passive exposures to traditional risk premia – primarily credit risk and volatility risk – explain a majority of core fixed income manager active returns.

We took another approach and looked at the excess returns generated by Core Fixed Income managers versus the excess returns generated by the underlying benchmark (the Agg), in both the Core and Core Plus Fixed Income space.

We were simply looking to see if managers’ outperformance tracked the benchmark’s

outperformance.

When the risky parts of the Agg (mortgages and corporates) drove the Agg’s

outperformance versus risk-free Treasuries did managers follow suit? In other words,

were their excess returns driven by risk exposure? The answer is yes (Exhibit 1).

EXHIBIT 1. Here’s your Beta!

Average core and core plus manager excess returns over the Agg vs. the Agg’s excess returns over Treasuries

Source: eVestment, Bloomberg and Thresher Fixed. For illustrative purposes only. Average core and core plus managers represent all managers with return data in eVestment beginning January 2006 and with a preferred benchmark of the Bloomberg U.S. Aggregate Index.

Traditional Core Managers are Actively and Consistently Overweight Risk

At a high level, Exhibit 1 shows that when the benchmark generates negative or positive returns versus Treasuries, the average active manager generates negative or positive returns versus the benchmark.

Instead of delivering alpha, Exhibit 1 indicates that the performance of these managers is simply a function of having more risk versus the benchmark over time.

In other words, it doesn’t really matter what core managers say or do, the evidence shows they are running strategies that are riskier than the Agg. It all looks the same at a high level, whether the strategy is bottom up with teams of credit analysts, or macro driven with an economist edge, or structurally skewed towards corporate debt or mortgage debt, or favored by The Street in new issue allocations, or lucky at betting on rates or the yield curve.

The bottom line is that when risk is in favor, these strategies outperform. And when risk is out of favor, these strategies underperform.

Excess Return Beta

The correlation of excess returns of managers to the excess returns of the Agg is clearly visible in Exhibit 1. To the naked eye, it looks like lots of beta, not much alpha.

To quantify the relationship, we calculated an excess return beta for the Core and Core Plus

managers and used it to estimate a true alpha for each manager, and in turn the average manager (Exhibit 2).

EXHIBIT 2. Traditional Managers’ Excess Return Streams Closely Follow the Agg’s

Performance versus Treasuries

What we found for the period 01/31/2006 to 12/31/2023:

Source: eVestment, Bloomberg and Thresher Fixed. For illustrative purposes only. Average core and core plus managers represent all managers with return data in eVestment beginning January 2006 and with a preferred benchmark of the Bloomberg U.S. Aggregate Index.

The results in Exhibit 2 have several implications for asset allocators:

1. The correlation of excess returns of managers to the excess return of the Agg is high. Ideally, this should be close to zero. A skilled manager’s idiosyncratic return, or alpha, should be independent of which way the market (the Agg) is moving. As an allocator you want the market risk and return of the Agg plus the added value of bottom-up security selection (or whatever idiosyncratic skill your managers have). In reality, there will often be some positive correlation as some idiosyncratic skills tend to correlate with the Agg’s excess returns.

2. The average manager has an Excess Return Beta significantly higher than 1. This indicates the average Core and Core Plus manager is running more risk than the benchmark.

3. Average managers deliver little in the way of Alpha. For Core managers only 14% of excess return is alpha. 7 bps – that’s it. The rest of the excess return bucket flows from beta.

4. Alpha generation is better in the Core Plus space and that is not entirely surprising. Core Plus managers have more risk buckets (i.e., high yield) and hence, more places to add alpha.

So, there it is. Lots of beta, not much alpha for the average manager.

A Path to Alpha

Our view at Thresher is that we can deliver excess returns that consist almost entirely of alpha. We believe that optimizing sector allocation is a more effective way to generate alpha. Spend less time and resources on evaluating idiosyncratic investment grade credit risk and more time and resources on signals that systematically identify when to take less or more risk at the aggregate portfolio level (Exhibit 3).

EXHIBIT 3. A Modern Approach to Fixed Income

To extend the analysis in Exhibit 2, we include the top quartile managers in the Core space and hypothetical returns of a signals-based systematic Core model for the same period (Exhibit 4). The primary systematic methodology is a value-based reallocation across the large components of the Agg (Treasuries, Corporates and Mortgages). As the data shows, these backtested results suggest you can run Agg money with a negative excess return correlation and generate real alpha.

EXHIBIT 4. A Systematic Framework has the Potential to Deliver True Alpha

For the period 01/31/2006 to 12/31/2023

Source: eVestment, Bloomberg and Thresher Fixed. For illustrative purposes only. Top quartile core and core plus managers represent all managers with return data in eVestment beginning January 2006 and with a preferred benchmark of the Bloomberg U.S. Aggregate Index. PAST PERFORMANCE IS NOT INDICATIVE OF FUTURE RESULTS OR A GUARANTEE OF FUTURE RETURNS. Please see disclosures for additional notes on back-tested returns.

A Systematic Approach Enables True Alpha Generation

As we’ve demonstrated, most traditional fixed income managers are delivering beta —

not alpha. For asset allocators, this means fixed income may not play the diversification role many investors need and expect. Return streams from traditional strategies are likely to be highly correlated to the benchmark’s performance versus Treasuries.

Our approach to generating alpha relies on a systematic framework that combines our human expertise with rigorous quantitative analysis. Fast emerging technologies and access to better data allows us to deploy resources efficiently and address the shortcomings of traditional methods by focusing on the primary drivers of alpha, asset allocation being foremost.

By leveraging these advancements, we believe asset managers can:

1. Efficiently integrate fundamental and quantitative methodologies, moving beyond the piecemeal approaches that have led to high excess return betas.

2. Systematically estimate the likely trajectory of risk assets, potentially reducing the overexposure to risk we’ve observed in traditional managers.

3. Identify key risk factors driving asset volatility over time, enabling more precise risk management than the blanket overweighting of risk seen in conventional strategies.

4. Incorporate multiple inputs to gain a comprehensive understanding of the relationship between market factors and asset prices, potentially uncovering alpha opportunities that traditional bottom-up approaches might miss.

5. Employ quantitative dislocation methodologies to identify mis-priced assets without relying heavily on credit analysts, addressing the limitations of traditional security selection we’ve discussed.

6. Create bespoke solutions for clients that meet risk and return needs cost-effectively, offering an alternative to the one-size-fits-all risk overweighting we’ve observed.

The Implications

These advancements have profound implications. The traditional approach of employing large teams of individual research analysts as the primary pathway to generate alpha now seems inefficient compared to the potential of data-driven, AI-enhanced strategies.

Our Approach

We’ve harnessed these technologies to transform our decades of fixed income expertise into a systematic, repeatable process designed to generate true alpha over time. This approach aims to deliver the kind of uncorrelated excess returns that our analysis shows are rare among traditional managers. We believe this represents the future of fixed income investing — one where alpha, not beta, drives outperformance.

Download PDF

Disclosures

THIS DOCUMENT IS FOR INFORMATIONAL PURPOSES ONLY AND SHOULD NOT BE RELIED UPON AS INVESTMENT ADVICE. This document has been prepared by THRESHER FIXED and is not intended to be (and may not be relied on in any manner as) legal, tax, investment, accounting or other advice or as an offer to sell or a solicitation of an offer to buy any securities of any investment product or any investment advisory service.

THIS DOCUMENT IS NOT A RECOMMENDATION FOR ANY SECURITY OR INVESTMENT. References to any portfolio investment are intended to illustrate the application of THRESHER FIXED’s investment process only and should not be used as the basis for making any decision about purchasing, holding or selling any securities. Nothing herein should be interpreted or used in any manner as investment advice. The information provided about these portfolio investments is intended to be illustrative and it is not intended to be used as an indication of the current or future performance of THRESHER FIXED’s portfolio investments.

DO NOT RELY ON ANY OPINIONS, PREDICTIONS, PROJECTIONS OR FORWARD-LOOKING STATEMENTS CONTAINED HEREIN. Certain information contained in this document constitutes “forward-looking statements” that are inherently unreliable and actual events or results may differ materially from those reflected or contemplated herein. THRESHER FIXED does not make any assurance as to the accuracy of those predictions or forward-looking statements. THRESHER FIXED expressly disclaims any obligation or undertaking to update or revise any such forward-looking statements. The views and opinions expressed herein are those of THRESHER FIXED as of the date hereof and are subject to change based on prevailing market and economic conditions and will not be updated or supplemented.

EXTERNAL SOURCES. Certain information contained herein has been obtained from third-party sources. Although THRESHER FIXED believes the information from such sources to be reliable, THRESHER FIXED makes no representation as to its accuracy or completeness.

A Note on Back-Tested Performance

The framework discussed in this document is hypothetical and does not represent the investment performance or the actual accounts of any investors or any funds. The securities in the hypothetical portfolios were selected with the full benefit of hindsight, after their performance over the period shown was known. The results achieved in our simulations do not guarantee future investment results. The model performance information in this document is based on the back-tested performance of hypothetical investments over the time periods indicated. “Back-testing” is a process of objectively simulating historical investment returns by applying a set of rules for buying and selling securities, and other assets, backward in time, testing those rules, and hypothetically investing in the securities and other assets that are chosen. Back-testing is designed to allow investors to understand and evaluate certain strategies by seeing how they would have performed hypothetically during certain time periods.It is possible that the markets will perform better or worse than shown in the projections; that the actual results of an investor who invests in the manner these projections suggest will be better or worse than the projections; and that an investor may lose money by investing in the manner the projections suggest. Although the information contained herein has been obtained from sources believed to be reliable, its accuracy and completeness cannot be guaranteed. While back-testing results reflect rigorous application of the investment strategy selected, back-tested results have certain limitations and should not be considered indicative of future results. In particular, they do not reflect actual trading in an account, so there is no guarantee that an actual account would have achieved these results shown. Back-tested results assume that asset allocations change in response to changes in the model for each strategy and that transaction costs are equal to assumed transaction costs for the period.