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Investment Tactics

The Role of Fixed Income As Central Banks Pivot

Jason Brady, CFA
President and CEO
5 May 2022
13 min read

The Fed’s shift to fighting inflation triggered a liquidity regime change. As a result, asset allocators face increased uncertainty from a variety of sources.

In this paper we will examine the current investment and monetary policy environment and discuss the use, and misuse, of asset allocation correlation matrices to determine effective portfolios. We will discuss the role of market liquidity, both within the context of historically easy monetary accommodation, along with the reduced broker/dealer role as a result of bank regulation which discourages balance sheet risk-taking. We will provide evidence that as the liquidity regime evolves, inter-asset correlations are also likely to change, creating greater uncertainty and increasing the importance of tail-risk management. Additionally, we will discuss the larger tool kit and a potential for an opportunistic overlay that investors may employ for superior long-term returns.

Recession or Inflation: What Keeps You up at Night?

A recent strategic discussion amongst my fellow investors at Thornburg Investment Management occasioned an interesting and topical question: “What are we worried more about: recession or inflation?” This comes as a number of market commentators and economists begin to forecast a recession starting sometime in the next 1-2 years. At the same time, the U.S. is experiencing inflationary pressures that are worse than any time in the past 40 years. I would argue of course that the answer to the query is: “Both.” Not simply because of current conditions, but rather because the debate is parallel to the Federal Reserve’s internal discussions and to the various roles that individual asset classes play in the asset allocator playbook.

For the Fed, their mandate for price stability and full employment speaks to the dangers of running the economy either too hot (sparking inflation) or too cold (sparking recession). It’s a delicate balance, and one that today is increasingly unlikely to be executed successfully in my opinion. As for the role of various asset classes, starting with the basic 60/40 allocation of stocks and bonds, it’s generally assumed that stocks will work well in a growth environment (thus potentially countering inflation) and bonds will protect in a downturn (as ballast for recession). All these typical assumptions and roles have been turned on their head in the last year, so it’s worth going back and exploring some underlying principles to understand how investors should position themselves going forward.

The Fed Moves the Goalposts

Let’s begin with the role of monetary policy and specifically that of the Federal Reserve. The Fed’s policy has been evolving over the last several years, most notably with the adoption of the “Average Inflation Targeting” framework at the Jackson Hole conference in 2020. The Fed learned from the post-Global Financial Crisis (GFC) recovery that lower unemployment was not necessarily accompanied by higher price pressures. The so-called “Philips Curve” that describes that relationship was therefore flat. As such, the Fed believed the economy could tolerate a low rate of unemployment without creating inflation. Therefore, as the U.S. economy began to recover following the spring 2020 lockdowns, the Fed left policy rates unchanged at the zero bound, while executing on an unprecedented amount of Quantitative Easing. This was in addition to a very robust fiscal response which was largely absent during the GFC.

By explicitly waiting until inflation was notably above the 2% target, the Fed hoped to communicate that deflation was less likely and underscored the central bank’s commitment to overshoot in order for the average level of inflation to remain at 2% target. They succeeded in that inflation did rise, and quite dramatically as we progressed through 2021. While initially attributed to COVID-related supply shocks including chip shortages and shipping issues, eventually the Fed was forced to admit that inflation was not “transitory”. The delay in action to combat rising inflation was a direct result of their change in reaction function as specified at Jackson Hole in 2020. That is, moving from policy decisions that focused on anticipating future economic outcomes to one that was “data dependent”. This virtually assured that the Fed was going to fall behind the curve, and we are seeing this dynamic play out presently. The market has reacted accordingly, pushing Treasury yields sharply higher and pricing in (as of this writing) multiple 50 basis point rate hikes in 2022. In this environment, it’s clear that fixed income has not provided any sort of ballast to portfolios on a year-to-date and 1-year basis.

Inflation-Adjusted Fed Funds Rate at Historic Lows

Source: Deutsche Bank, Bloomberg

The Role of Fixed Income in Portfolios

Why do investors buy bonds? Historically their rationale has come down to 1) income return and 2) portfolio insurance. In most traditional asset allocation models, bonds provide a notably lower return than equities, along with a lower volatility profile. Typically, investors will require a higher risk-adjusted return (Sharpe ratio) for equities vs. bonds, though in practice outcomes are highly dependent on the data sample. Historically, high quality fixed income has been able to fulfill both roles.

10-Year Real Rates And Inflation

Source: Bloomberg

As the Fed’s monetary policy continued to spend the “Volcker dividend,” rates steadily declined over the past 40 years. As such, the playbook of ever-lower rates that every central bank has followed has been successful so far. Post the GFC, central banks, upon reaching the zero lower bound, began to execute on quantitative easing in order to provide further accommodation. While the scars of the GFC were still fresh, this added liquidity to the marketplace and spending power to various governments. But this came at a cost: investors could not rely on both safety and a decent real income return from high-quality fixed income. This dynamic reached a crescendo during the Covid crisis. While many recognized the challenge of buying fixed income securities at levels well below the rates of inflation, the adaptive nature of investors and their resulting flawed expectations for future strong returns maintained flows into fixed income through 2021. As the vaccine-based recovery from Covid continued, and the aforementioned Fed reaction function shift allowed for a build up in inflationary pressures, investors have been confronted with the challenge that fixed income as an asset class has provided negative real (and now nominal) returns while not providing the much relied-upon negative correlation with riskier assets.

What’s Correlation Got to Do With It?

While a detailed discussion of the math behind correlation matrices is beyond the scope of this paper (see Mariani 2022 and Alfelt 2021 for more detailed overviews)[1], it’s important to at least set the stage for reviewing the basic principles of asset allocation. As investors I would argue we need to consider three main variables: Expected Return, Variance (or volatility), and Correlation (or how assets move in relation to one another). While the math here is theoretically simple, any number of assets greater than a few produces a complexity that is unwieldy. (As Engle and Colacito, 2006 put it: “One difficulty in running the analysis on 34 assets is choosing an appropriate vector of expected returns, because the approach followed in the bivariate examples would clearly result in an unbearable number of possible combinations.”)[2] While there have been many attempts over the decades to tame this mathematical complexity, as a practitioner I certainly want to understand the theory simply as a framework. Even investors who feel they have a good handle on the likelihood of future expected returns and future volatility are left with the “simple” challenge of figuring out the co-movement (correlation) between assets.

One significant issue in even the simple portfolio of large-cap stocks and “risk-free” bonds is that the correlation between these two building block assets is not constant. Over the last several years, investors have moved from a regime where in the shorter-term (monthly periods) these assets have moved either in the opposite direction or with no relation (negative to zero correlation), to a world where these assets have begun to move in tandem. While there have been periods, such as 2019, where this has been a good thing, the market upsets of late 2018 and early 2022 point to a much different dynamic than has existed for the past generation.

When the Model Goes Haywire

While the literature (examined by Engle and Colacito, 2006)[3] indicates that investors’ return and variance estimates are much more important than correlation, it also points to the significantly increased importance of correlation in volatile or stressed periods. This is intuitive for market participants: If I can accurately say the stock market will go up by 10%, and with a certain amount of volatility, I’d rather have that knowledge than how that might relate to another asset class in my portfolio. Still, if I have wide uncertainty around all of these statistics, I’d like to at least be able to depend on some element of diversification within my asset allocation. The bad news is that our historical dependence on diversification is changing rapidly, and as we are witnessing in markets, not for the better. This is broadly a result of changes in market liquidity as a result of global central bank action. In other words, the removal of central bank liquidity represents regime change. And now that the markets have adjusted, that normalization is pushing us back to a world where negative asset correlations are possible in a tail risk scenario.

Correlation Between Stocks and 10-Year Treasury

Source: JP Morgan. Stocks represented by the S&P 500 Index

As an example of the challenges in creating correlation matrices, JP Morgan’s 2022 assumptions for U.S. Long Duration Bonds was 2.3%, with an annualized volatility of 9.5%. In contrast, their assumption for Large Cap US Stocks was 4.1%, with a volatility of 15.0%. Crucially, their assumption of the correlation between these two asset classes was 0.02. This is to say, they expect virtually no correlation between Large Cap Equities and High-Quality Fixed Income. Certainly, this is not to pick on JP Morgan. Indeed, many other asset allocation correlation matrices look similar, and the exercise of creating these matrices indicates hope that our asset allocation conundrum can be tackled with “mathiness.”  Of course, selecting a forward-looking starting point matters more as a function of valuation and potential future return, than one that is focused fully on the rearview mirror. With US interest rates at levels close to, or below, the lowest that they have ever been, it’s unlikely that investors were likely to see positive returns, especially in the case that the Fed ended up too successful in generating inflation.

Inter-Asset Correlation Matrix

U.S.
Large Cap
U.S.
Small Cap
EAFE
Equity
EM
Equity
World
Gov’t Bonds
U.S. Inv. Grade
Corp. Bonds
U.S.
High Yield Bonds
EM
Sov. Debt
Private
Equity
Direct
Lending
U.S. Large Cap
U.S. Small Cap 0.91
EAFE Equity 0.88 0.79
EM Equity 0.76 0.70 0.87
World
Gov’t Bonds
0.12 0.03 0.28 0.31
U.S. Inv Grade
Corp. Bonds
0.33 0.25 0.42 0.45 0.53
U.S. High Yield
Bonds
0.71 0.68 0.75 0.74 0.17 0.58
EM Sov. Debt 0.53 0.45 0.64 0.67 0.47 0.77 0.72
Private Equity 0.80 0.76 0.81 0.82 -0.01 0.30 0.72 0.58
Direct Lending 0.63 0.54 0.59 0.60 -0.20 0.20 0.72 0.50 0.75
Source: J.P. Morgan Asset Management, as of 9/30/2021

Previous Assumptions Cannot Be Relied Upon

The importance of the change in the Fed’s reaction function should not be understated, for several reasons. First, Fed’s leadership position as a global arbiter of liquidity means a clustering behavior is likely to occur among global central banks. Second, central bank liquidity has become a significant determinant of both global asset prices and covariance. Lastly, the Fed’s shift to outright inflation fighting mode is a dynamic we have not seen for several decades and therefore investors must grapple with its direct and indirect effects. All of this warrants an examination of how the current regime change can and should affect asset allocation assumptions.

Risk models for our fixed income portfolios showed that duration was a countervailing (risk reduction) force relative to credit pre-pandemic. More recent output shows a reversal of that dynamic, with price moves from credit spread widening and interest rate increases occurring more often at the same time. The below is an output for a moderate duration, multi-sector portfolio from the end of 2019 through the first quarter of 2022. The data shows that pre-Covid, and into the early parts of the pandemic, rates and credit offset one another. More recently this is much less true, partly due to credit decaying as a factor.

Representative Fixed Income Portfolio Risk Contributors

Source: FactSet

In essence, we have moved from a regime where low yields underpinned risky asset prices to one where rising yields are a threat to those same assets. This is partly due to simple substitution math: Higher risk-free returns, all else equal, are more interesting vs. risky asset returns at the same level. When the price of something goes down, investors should be more interested. A subset of this argument has also been underpinning global risky asset prices: Very low yields are a support for risky assets as financing is easy and there is no return available elsewhere.

This backdrop creates acute uncertainty for asset allocators as all three predicted variables: return, volatility, and correlation, are all changing rapidly. Many papers have detailed the rapid changes in asset allocation models and correlations in times of stress. The real question is, what do investors do now?

The Painful Transition

For investors, then, this is something of a normalization process, albeit painful, but only for now. With a terrible year of bond price depreciation, investors may have the first opportunity in some time to buy fixed income at a level that doesn’t ensure negative real returns, while also potentially providing downside protection in a negative risk asset tail event. Though we believe that real rates could rise to 1-2% in the US, and as much as 1% in Europe, as a component to asset allocation there is again some value for investors that are looking for insurance, or ballast for their portfolios.

It has often been the concern of allocators and other market participants that an expectation for higher rates will mean decreased flows and interest in high-quality fixed income. In 2018, the last time that rates rose significantly, there was a call for a “rotation” out of high-quality bonds and into riskier assets like global public and private equity due to investors’ loss experience. Instead what occurred was a rotation into fixed income as yields rose. Not only were typical yield-starved investors such as insurance companies and retirees interested in a suddenly higher rate of return for little risk, but many pension plans were able to immunize their liabilities after years of being underfunded. We expect a similar dynamic to occur. I often ask sophisticated investors what their asset allocation would look like in a world with 4% real yields on risk free assets, as we saw in the end of the 1990s. Without hesitation they would significantly increase their allocation to such assets, increase their Sharpe ratio, and massively decrease their headaches.

Flexibility Is Key in This Environment

In addition to the ballast argument, there is also better opportunity for attractive entry points in the riskier areas of the market. It is undoubtedly the case that in the last 15 years the market has seen a notably higher incidence of flash crashes and liquidity events.

Volatility Is Trending Up and Occurring More Frequently

Source: Bloomberg.

This, of course, is highlighted by the downturn in March of 2020, in which the market experienced heavy outflows in fixed income. In fact, flows were 18 times worse in the worst week of March 2020 than in the worst week of October of 2008. The European Financial Crisis, the energy credit market melt-down, even flash crashes in large liquid markets like US Treasuries and oil indicate that the depth of markets is akin to a kiddie-pool. The major cause of this trend is likely to be the combination of very low rates since the GFC and the reduction in intermediary involvement due to significant banking regulation. This regulation has driven lending to be largely dominated by non-bank participants. These participants hold liability structures that are shorter-term, thus allowing for quicker outflows, and marked-to-market on a regular basis. This drives more severe negative overshoots, especially in riskier parts of the credit markets. Recent episodes and examples are many, and now occur at least once every 3-4 years.

Because there is less market liquidity in the system, and more lending happening through non-bank participants, investors have more investment choice but also the likelihood of high volatility, or more precisely, volatility of volatility. Though credit markets have not dislocated in 2022 year-to-date, both cracks and opportunities are beginning to appear. Examples include a growing market for consumer Asset-Backed Securities, Global Debt, and selective areas of Corporate Debt. It is critical to have a perspective that looks across these kinds of opportunities, as liquidity pressures can roll across markets at different times. When the difficult market arrives, it’s too late to do extensive credit work across a wide variety of markets and at the same time be able to construct or trade an entire portfolio, which makes that credit work through a cycle critical. The pace of change requires expansive thinking, strong portfolio construction, and nimbleness.

Locked up capital in private debt investments will not be nimble enough to take advantage of these situations, and because they are sold on the basis of yield, will have reached for risk in good times and be stuck slogging through challenges in uglier times. With a backdrop of explosive market growth, well over $1 trillion total market with $192bln raised in 2021[4] and poor credit quality (19% of deals over 7x leverage according to Proskauer Rose)[5], we believe private credit is not set up for success.

The liquidity regime change, caused recently by a massive global central bank pivot away from providing downside protection at all costs towards fighting inflation, has reintroduced the argument for high quality fixed income to provide ballast for portfolios. At the same time, the removal of market liquidity from intermediaries (banks) along with the significant transfer of risk from bank balance sheets to mark-to-market ones will continue to drive jump function (i.e., sudden moves higher) volatility in all markets, including fixed income. Asset allocators have more tools at their disposal today than perhaps at any other time, but also more uncertainty in all three of the key inputs to the trade: expected return, volatility, and correlation. We live in interesting times.

[1] Mariani, Francesca, “A tail-revisited Markowitz mean-variance approach and a portfolio network centrality.” Computational Management Science, January 2022. Alfelt, Gustav, “Modeling the covariance matrix of financial asset returns.” Stockholm University 2021.

[2] Engle, Robert and Colacito, Riccardo, “Testing and Valuing Dynamic Correlations for Asset Allocation.”web-static.stern.nyu.edu/rengle/EngleColacito.pdf.

[3] Engle, Robert and Colacito, Riccardo, “Testing and Valuing Dynamic Correlations for Asset Allocation.”web-static.stern.nyu.edu/rengle/EngleColacito.pdf.

[4] “Private markets rally to new heights.” McKinsey Global Private Markets Review 2022.

[5] Proskauer Rose

References

“2022 Long-Term  Capital Market Assumptions.” Portfolio Insights, J.P. Morgan Asset Management, 2022.

Engle, Robert, and Riccardo Colacito. Testing and Valuing Dynamic Correlations for Asset Allocation. Journal of Business & Economic Statistics, 2006, https://web-static.stern.nyu.edu/rengle/EngleColacito.pdf.

Loretan, Mico, and William English. “The Fed – Evaluating Correlation Breakdowns during Periods of Market Volatility.” Board of Governors of the Federal Reserve System, International Finance Discussion Papers, 25 Feb. 2021, https://www.federalreserve.gov/econres/ifdp/evaluating-correlation-breakdowns-during-periods-of-market-volatility.htm.

Musmeci, Nicoló, et al. “Interplay between Past Market Correlation Structure Changes and Future Volatility Outbursts | Scientific Reports.” Nature, Springer Nature, 18 Nov. 2016, https://www.nature.com/articles/srep36320.

“The Co-Movement of U.S. Equity Returns with the Developed and Emerging Markets of Australasia and Asia International Journal of Business and Social Research.” International Journal of Business and Social Research, Jan. 2015, https://thejournalofbusiness.org/index.php/site/article/view/503.

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