You Already Know Something Is Wrong. Here Is The Math.
Frameworks for Navigating Uncertainty, from Pandemic to Present
Tamika Tyson, Founder & Managing Partner, SCALE
April 2026 | Part 2 of 7 in the Through the Cycle series
In last week's post, I wrote about the biology of panic and why the instinct to move is usually the thing that costs you the most. If you have not read it yet, start there. It is the foundation for everything that follows.
This week, I want to give you the tools. Because understanding that you should not panic is only useful if you have a framework that tells you what to do instead.
Six years ago, I was on a Zoom call with a group of energy professionals and I asked a simple question: What shape will recovery take? That was June 2020. Nobody knew. The pandemic had locked everyone in their homes and broken every model. The professionals on that call did not need reassurance. They needed structure.
I gave them a set of frameworks that day. A way to classify risk events. A way to read where we were in the credit cycle. A way to separate the noise from the signal. Those frameworks held up. Not because they predicted what happened next, but because they gave practitioners a vocabulary for making decisions when the data was ambiguous and the pressure was intense.
Today, in April 2026, the specifics are different but the need is the same. The S&P 500 is down approximately seven percent year-to-date and was recently as much as nine percent off its all-time high. The Iran war reached a ceasefire this month after causing what reports on the IEA’s assessment described as the largest supply disruption in the history of the global oil market. The current tariff regime is generating real recession fears, with probability estimates from major forecasters ranging between 20 and 35 percent. Credit spreads have begun to widen from their January lows but remain near the tightest levels in a generation. The question, again, is not what will happen. The question is whether you have a framework for making decisions regardless of what happens.
Let me walk you through the one I use.
The Cascade That Actually Happened
In 2020, we built a series of scenarios around what a recovery might look like. We discussed V-shaped recoveries and U-shaped ones. We debated L-shaped outcomes. We were trying to predict shape.
What nobody predicted was the actual sequence of events that would unfold. Predictions are often wrong because the world does not move in straight lines.
Here is what actually happened, in order: supply chain seizure. That led to nine-point-one percent inflation. Russia invaded Ukraine. The Federal Reserve embarked on the fastest rate hiking cycle in its history. We got three bank failures in roughly eight weeks. And then we got an AI disruption that nobody was quite ready for, and which is still reshaping how every organization thinks about labor, capital allocation, and competitive advantage.
Each of these events was theoretically possible. Several of them were discussed in scenario planning. But the cascade, the sequence, the specific way each event accelerated the next: that is what made them matter.
This is not a prediction failure. This is a calibration problem. Most professionals entered 2021 thinking they understood the risks. They did not. Not because they were careless, but because scenario planning is hard, and because the intersection of multiple low-probability events creates outcomes that feel impossible until they are not.
The point I want to make is this: the risks that matter most are the ones you can see coming, but that you choose not to prepare for. This takes us directly into taxonomy.
How to Think About Black Swans, Grey Swans, and White Swans
I am going to borrow from the work on swan taxonomy that has been central to my research. There are three categories of outlier events that professionals talk about.
Black swans are theoretically unpredictable. They are outside the range of historical experience. The 2008 financial crisis is often framed as a black swan, though that is debatable. The point is: they feel like they come from nowhere.
White swans are the opposite. They are visible. Their probability might be low, and their impact might be uncertain, but if you have the information and you are looking at the data, you can see them. You can prepare.
Grey swans are the ones that matter. They are in the middle. The data on grey swans is available. Organizations have information about them. But for whatever reason, organizational or behavioral or political, they choose not to prepare. They choose not to act. So when the grey swan events happen, they land like black swans. They feel like surprises.
Here is the uncomfortable truth: most "black swans" that cause serious economic damage are actually grey swans that organizations chose not to prepare for.
Let me give you a specific example. Silicon Valley Bank failed in March 2023. It was not a black swan. SVB's balance sheet showed massive interest rate risk. This was visible in the bank's public filings. The maturity mismatch between their assets and liabilities was substantial. When the Fed raised rates, those assets were suddenly underwater. This was not hidden information. It was not impossible to see.
What was true is that the failure moved fast. Forty-two billion dollars in deposits fled in a single day. The speed was real. But the risk, the underlying risk, was white. It was visible. This is a grey swan event because the market was willing to deny it until the moment it could not.
This matters for how you think about April 2026, because we are currently operating in a credit environment that is pricing as if grey swans do not exist.
Where We Are on the Credit Clock Right Now
I use a leverage cycle framework in my research that I call the Credit Cycle, or the Leverage Clock. It is a twelve-position model that shows you where investors are in the credit cycle and what the risk positioning looks like at each point.
The basic idea is simple: there are times when credit is tight and capital is expensive, and there are times when credit is loose and capital is cheap. These cycles have behavioral patterns. They have warning signs. The clock moves, and if you know where you are on the clock, you know what to watch for.
Let me give you the current readings as of April 2026. Investment-grade credit spreads reached a January low of 71 basis points, among the tightest levels in over two decades, and have since widened. As of April 21, 2026, the ICE BofA US Corporate Index option-adjusted spread stood at 80 basis points. That is still historically tight. The twenty-year average for investment-grade spreads is closer to 150 basis points. Think about that for a moment. Even after widening, we remain near the tightest spreads in a quarter century.
High-yield spreads are at approximately 285 basis points, or 2.85 percent. The twenty-year average for high-yield spreads is 490 basis points, or 4.9 percent. We are pricing high-yield credit as if default risk is substantially lower than the historical average.
And yet, leveraged loan defaults are currently running at approximately 4.8 percent on a trailing twelve-month basis, with Fitch projecting a range of 4.5 to 5 percent for the full year 2026. Earlier Moody's projections of 7.5 to 7.9 percent proved too pessimistic. But here is what that actually tells us: even at 4.8 percent, high-yield spreads at 285 basis points imply the market is pricing in far less default risk than that. The complacency is structural, not corrected. The near-term refinancing wall stands at roughly 94 billion dollars for 2026-2027, but the real pressure is 2028, when approximately 288 billion dollars in leveraged loan maturities come due, with 52 percent of those rated B-minus or lower.
Some will point to the widening from January lows as evidence that the market is correcting. It is not. Moving from 71 to 80 basis points when the twenty-year average is 150 is not a correction. It is an acknowledgment. The distance between where spreads are and where the data suggests they should be, given the Iran energy shock, the tariff environment, and the 2028 refinancing wall, remains large. And default data lags real-world stress by twelve to twenty-four months. The 4.8 percent trailing rate does not yet reflect the disruption that entered the system in March and April 2026. The clock has not reset. It has ticked forward.
Here is the contradiction that matters: the market is pricing credit as if we are in a low-risk environment. The data is saying something else.
This is what happens at specific points on the leverage clock. This is what it looks like when investors have been conditioned by a long period of loose credit to believe that default risk is lower than it actually is. This is what it looks like when spreads have not widened in so long that people forget why spreads exist. They exist because credit losses happen.
We are currently operating in an environment where spreads are not compensating investors for the default risk that is visible in the data. This is the grey swan. This is the thing that is visible, and that the market is choosing not to prepare for.
The Six Lessons From the Actual Crisis
When I looked back on what actually happened from 2020 through 2023, six lessons emerged. They are not theoretical. They are grounded in what actually happened to organizations, to portfolios, to balance sheets.
The first lesson is about speed. The deposit flight from the 2023 bank failures was 42 billion dollars in a single day, at a rate of over one million dollars per second, with another 100 billion queued for the following morning. This matters because it means that liquidity planning, treasury management, and capital allocation decisions that worked fine for decades suddenly did not. The speed of capital movement in a digital age is fundamentally different from the speed of capital movement in a previous era. If you are modeling for historical velocity, you are not modeling for reality.
The second lesson is that correlations break. In a crisis, assets that are theoretically uncorrelated move together. Equities down, credit spreads wider, volatility up, liquidity down. The diversification benefit you were counting on evaporates. This is not theory. This happens every time. And yet, organizations keep assuming that correlation will hold this time, because this time is different.
The third lesson is that grey swans matter more than black swans. The risks that killed organizations from 2020 to 2023 were not unknown. They were known, unpriced, and ignored. This has profound implications for risk management. It means that risk management is less about predicting the impossible and more about forcing yourself to prepare for things you can see but do not want to look at.
The fourth lesson is that liquidity is more universal than people assume. It is not just about banks. When things get tight, liquidity dries up everywhere. Real estate markets freeze. Corporate debt markets seize. Even equities can be hard to sell if the panic is severe enough. The assumption that you can always sell an asset at some price is a dangerous assumption. The assumption that your supposedly liquid assets will remain liquid in a stress scenario is a dangerous assumption.
The fifth lesson is that narrative matters more than data in the short term. The 2023 bank failures happened because of interest rate risk, but they happened in the moment when Twitter, Discord, and a few well-timed pieces of journalism created a narrative about bank risk. The facts do not change the timeline. The narrative does. This is uncomfortable for people who believe in rational markets, but the data does not lie: narrative moved faster than duration risk.
The sixth lesson is about personal discipline. It sounds simple, but it is the hardest one to execute. When credit is loose, when spreads are tight, when everyone is making money, the pressure to deploy capital, to take risk, to match the returns your peers are getting, is immense. The discipline to say no, to say I understand the risk and I am choosing to underweight, to accept lower returns in exchange for better positioning, is the discipline that separates professionals who survive cycles from professionals who get wiped out.
These six lessons are not new. They are reminders. They are what I learned from what actually happened. And they are all relevant right now.
What The Contradiction Is Telling Us
Let me synthesize this for you.
We have credit spreads that, while they have begun to widen from January lows, remain near the tightest levels in 25 years at approximately 80 basis points for investment grade. We have leveraged loan defaults running at approximately 4.8 percent on a trailing basis, with the full scope of tariff and energy disruption not yet reflected in default data. We have a 288 billion dollar refinancing wall approaching in 2028. We have a tariff regime generating genuine recession fears. We have just come through what reports on the IEA’s assessment described as the largest supply disruption in the history of the global oil market.
This is a moment where the market is mispricing risk, and where the mismatch between the market price and the actual risk is about as visible as it gets.
The professionals I talk to understand this. They can see it. But many of them are asking the question that is at the root of the grey swan problem: what do I do about it. How do I underweight risk when everyone else is taking it. How do I say no to yield when my mandate is to generate yield.
These are real questions. They have real costs. The professionals who got this right in 2021 and 2022 did not do it because they were smarter. They did it because they had a framework, they understood where they were on the cycle, and they had the discipline to execute on what the framework told them.
This is the reason I have been working on a deeper series of frameworks around navigating risk through the entire credit cycle, from expansion through contraction and back again. It is the reason I am publishing this series. It is the reason I am willing to say, clearly, that we are at a moment where credit risk is mispriced, where the visible risks are being ignored, and where the professionals who prepare now will have a significant advantage over the professionals who do not.
The Work Ahead
The 2028 refinancing wall is not a forecast. It is a calendar. Two hundred and eighty-eight billion dollars in leveraged loan maturities. Fifty-two percent rated B-minus or lower. These loans will need to refinance into a credit market that has absorbed the largest supply disruption in the history of the global oil market, alongside a tariff regime whose full transmission into default rates has not yet been measured. That is the kind of visible, dateable risk that the frameworks in this series are designed to help you navigate before it arrives on your doorstep.
The question I asked on that Zoom call in 2020 was about shape. The question I am asking now is about preparation. The data is available. The frameworks exist. The credit clock is readable. The grey swans are visible. The only variable left is whether the professionals who can see what is coming choose to act on it before the cycle turns.
In the next post, I am going to take you inside the credit infrastructure itself, because the thing that makes cycles turn is not stocks or sentiment. It is credit. And right now, the credit market is telling a story that most people are not reading carefully enough.
I am currently in conversations with CROs, risk committees, and investment professionals navigating the disconnect between how markets are pricing credit and what the underlying data shows. Reach me directly at tamika@tamikatyson.com.
Sources
S&P 500 year-to-date performance and drawdown data: Wespath Investment Management, Market Performance Summary, April 17, 2026 (S&P 500 YTD return of -6.7%).
Recession probability estimates (20-35% range across major forecasters): RSM US Economic Outlook, April 2026 (30%); New York Federal Reserve Yield Curve Model, April 2026 (18.8%); Wall Street Journal Economic Forecast Survey, January 2026 (27% average).
Investment-grade credit spreads: Bloomberg, "US High-Grade Corporate Bond Spreads Hit Fresh Three Decade Low," January 22, 2026 (71 bps January low); ICE BofA US Corporate Index (BAMLC0A0CM), FRED, Federal Reserve Bank of St. Louis (0.80%, or 80 basis points, as of April 21, 2026); PineBridge Investments, "2026 Investment Grade Credit Outlook," Q1 2026.
High-yield spread data and 20-year historical averages: Bloomberg Terminal, historical OAS data.
Leveraged loan default rate (approximately 4.8% trailing twelve-month, 4.5-5% 2026 forecast): Fitch Ratings, "U.S. Leveraged Loan Default Rate Falls," 2026; PitchBook, "US leveraged loan default rate including LMEs slides to two-year low," 2026. Note: earlier Moody's projections of 7.5-7.9% (Moody's, "US Credit Review and Outlook," 2025) did not materialize at those levels.
Refinancing wall ($94B for 2026-2027): Sikich, Q4 2025 Credit Market Update: Year-End Review and 2026 Outlook. Leveraged loan maturity wall 2028 ($288B, 52% rated B- or lower): PitchBook, "2026 US Leveraged Loan Outlook," 2026.
SVB deposit outflow of $42 billion in a single day: Fortune, "$42 billion in one day: SVB bank run biggest in more than a decade," March 11, 2023; Federal Reserve, "Review of the Federal Reserve's Supervision and Regulation of Silicon Valley Bank," April 2023; FDIC, "Recent Bank Failures and the Federal Regulatory Response," March 2023.
CPI peak of 9.1% (June 2022): U.S. Bureau of Labor Statistics, Consumer Price Index Summary, July 2022.