Investors and policymakers hardly need reminding that macro shocks, both positive and negative, are hitting the global economy with growing frequency and force. Recent shocks have come from the supply side, most prominently from energy shortfalls and tariffs, but also the demand side—including the historic AI capex boom and fiscal loosening. Our conviction is that the global economy has entered a new structural regime, defined by recurring shocks from both supply and demand, and in which point forecasts offer a false sense of precision.
- On its own, each shock can reset growth and inflation forecasts;
- Together, they create a world in which multiple macro regimes can plausibly emerge, overlap, and switch abruptly;
- This is why we adopted a probabilistic, scenario-based approach five years ago;
- We conclude that investors and policymakers will likely follow suit, if they haven't already.
Macro and Market Forecasting Amid a Structural Break
Our approach to scenario analysis reflects the unfolding reality that the global economy is undergoing a structural break. The old anchors of the “Great Moderation”—fiscal discipline, central bank independence, global supply chains, and geopolitical convergence—are giving way.
In their place, a new set of forces—economic warfare, fiscal dominance, supply chain insecurity, the rise of industrial policy, and a race to the commanding heights of foundational technologies—is reshaping supply and demand. The result is a wider range of growth and inflation outcomes, more frequent regime switches, and less confidence in any single point forecast. Indeed, we estimate that the variance of growth and inflation outcomes in advanced economies over the past decade is nearly three times higher than the preceding 50 years.2
Central bankers are already conceding that point forecasts are insufficient to meet this moment. The European Central Bank has started publishing scenario analyses alongside its baseline projections, and the Bank of England has signaled a similar direction of travel.3, 4
Newly confirmed Federal Reserve Chairman Kevin Warsh reinforced his skepticism towards point forecasts by declining to submit a "dot plot" forecast at the June FOMC meeting, his first as Fed Chair.
PGIM’s Approach: Probabilistic, Scenario-Based Forecasting
Recognizing this shift, we revamped our forecasting framework in 2022 around probabilistic assessments of macro regimes that could plausibly unfold over the next year. As a starting point, we assess the relative likelihood of growth and inflation combinations that markets could price. The mapping exercise is designed to help us, and our clients, imagine macro scenarios with distinct market outcomes, while explicitly laying out the assumptions and risks attached to each. We then derive expected returns for various asset classes in each scenario.
For example, our "overheating" modal case (40% probability) for the U.S. economy projects materially above-trend growth (2.5%+) and "sticky high" inflation above 3%+ for the next 12 months (see our Mid-Year Outlook). We also make probabilistic assessments of macro scenarios that are distinct from our modal case, including recession, stagflation, and a productivity boom. Using multiple linear regression models, we then translate the macroeconomic assumptions for each scenario into expected returns for a range of assets, as well as a probability-weighted average.
To assess credit spreads, we map the macro to the market using these models to generate a spread level under each scenario. We then use this spread to calculate carry and spread returns as well as to calibrate an estimate of credit migration.
We extend the analysis by deriving the market-implied probability distribution for a range of assets using futures, options, and other derivatives. After all, market prices are nothing more than a weighted synthesis of probabilistic expectations formed by millions of market participants. This step allows us to compare the market’s probabilities to our own views; notable differences mean that we have identified a market opportunity.
For example, our modal case for the U.S. economy underpins the Fed forecast we released in mid-June for three 25 bp rate hikes in 2026. Exhibit 1 shows that, as of mid-July, our view on the probability of a Fed funds rate that surpassed 4.0% by year end (55%) exceeded market expectations (39%), which we derive from three-month SOFR futures contracts that expire at the end of 2026.
Exhibit 1
Our probabilistic view of a Fed funds rate that surpasses 4% exceeded the market's implied expectation as of mid-July
Exhibit 2 demonstrates the mapping of our probabilistic macro assessments to the U.S. 10-year Treasury yield and to U.S. high yield spreads. As of mid-July, the probability weighting of our scenario distribution indicated an asymmetric outlook towards wider high yield spreads, but a more balanced view of government bond yields. At the time, high yield spreads traded at a historically tight level of about 275 bps, while the steady increase in the U.S. 10-year yield lifted it to the 4.50% area.
This assessment underpinned our constructive view on U.S. Treasuries in the belly of the yield curve given the attractive carry/roll conditions, as well as the carry-oriented focus in leveraged finance, with a heightened emphasis on issue selection.
Exhibit 2
Scenarios Indicate an Asymmetric Spread View, More Balanced Rate View
Another recent application is to the market for Brent crude oil amid the conflict in the Middle East (Exhibit 3).5 As of late July, Brent futures had priced in a benign modal case (~60% probability) where crude prices fall below $80/barrel by late December and relatively limited upside risks (only a 15% implied probability of Brent prices above $100 / barrel by late December).
Our probabilistic assessment was markedly different. Anticipating a lingering risk premium due to the risk of re-escalation, as well as tight inventories, we assigned the price range of $80-$100 / barrel as our modal scenario (50% probability), with balanced risks on both sides—pointing to significant upside potential in commodity-linked assets.
Exhibit 3
We maintain a $80-$100/barrel price range on Brent crude, which remains above market expectations
Conclusion
Investors are now operating in a world in which shocks to the supply side and demand side of the economy are more likely to arrive together or in rapid succession, making point forecasting an exercise in false precision. That is the premise of our scenario-based forecasting process.
By spelling out the logic, evidence, and vulnerabilities behind each plausible macro scenario in our probability distribution, we can compare our macro views with those embedded in various asset classes, such as credit, rates, equities, and commodities. Investment opportunities emerge when our assessment of the modal case—and the balance of risks around it—differ from what markets are discounting.
The same framework also gives portfolio managers a practical tool to stress-test exposures across a wide range of macro paths. Our north star is not to predict the future with spurious conviction; it is to ask better “what if?” questions, to be surprised less often, and to turn regime change from a source of vulnerability into a source of investment alpha.
1 Transcript of Chairman Warsh’s Press Conference, June 17, 2026.
2 Our estimate is based on the z-score of U.S. real GDP and core CPI from 1965 through 2025.
3 European Central Bank, Monetary Policy Decisions, March 19, 2026.
4 “Forecasting for Monetary Policy Making and Communication at the Bank of England: A Review,” April 12, 2024.
5 For oil probability density function (PDF), we use the Breeden–Litzenberger method to generate risk neutral probability distributions by taking the second derivative of call prices across strikes. We then segment this PDF into ranges to compare to our probabilities.
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