Footnotes:

1 Source: National Center for Education Statistics, March 2026
2 Source: US Bureau of Economic Analysis, March 2026
3 Source: American Automobile Association, May 18, 2026, based on $4.50 per gallon gasoline and a 14-gallon tank.
4 Source: Bloomberg, L.P., May 18, 2026, based on the 5-year US Treasury inflation breakeven. A breakeven inflation rate is a market-derived estimate of future inflation, calculated by comparing the yield on a standard government bond (nominal) to the yield on a Treasury Inflation-Protected Security (TIPS) of the same maturity.
5 Source: Bloomberg, L.P., May 18, 2026. Alan Greenspan became Fed Chair on Aug. 11, 1987, based on the one-day return of the S&P 500 Index on Oct. 19, 1987.
6 Source: Bloomberg, L.P., May 18, 2026. Jerome Powell - Feb. 5, 2018, Janet Yellen - Feb. 3, 2014, Ben Bernanke - Feb. 1, 2006, Alan Greenspan - Aug. 11, 1987, Paul Volcker - Aug. 6, 1979, and G. William Miller - March 8, 1978.
7 Source: Bloomberg, L.P., May 18, 2026, based on the option-adjusted spread of the Bloomberg US Corporate High Yield Bond Index, which measures the US dollar-denominated, high yield, fixed-rate corporate bond market.
8 Source: Board of Governors of the Federal Reserve System, March 2026, based on the annual percent change of Nonfinancial Corporate Business Debt Securities and Loans.
9 Source: US Bureau of Labor Statistics, April 2026
10 Source: Bloomberg, L.P., May 18, 2026, based on the 3-year and 5-year US Treasury inflation breakeven. A breakeven inflation rate is a market-derived estimate of future inflation, calculated by comparing the yield on a standard government bond (nominal) to the yield on a Treasury inflation-protected security (TIPS) of the same maturity.
11 Source: Bloomberg, L.P., March 31, 2026, based on the earnings per share (EPS) growth of the companies in the S&P 500 Index.
12 Source: Bloomberg, L.P., March 31, 2026, based on the earnings per share (EPS) growth of the companies in the S&P 500 Index.

Copyright © Invesco

Yes, we have been there before, only to be disappointed. But the market smells a real settlement to open Hormuz, and WTI oil briefly dipped below 90 for the first time in weeks. If an opening occurs, expect the market to continue its march upward, as the momentum trade gathers strength.

Even before this potential breakthrough the market has concluded enough replacement supply has found its way into global markets to prevent an outright economic shock. Unconfirmed reports that select supertankers are transiting the Straits after paying fees to Iran, combined with Saudi pipeline flows estimated near 7 million barrels per day, suggest the effective supply disruption may be smaller than headline fears implied. The global economy has tolerated current oil prices, which now seem set to fall.

The underlying U.S. economy remains resilient despite elevated geopolitical uncertainty. NVIDIA earnings last week were solid, not euphoric, but the broader economic data continue to point toward ongoing expansion. The Atlanta Fed GDPNow estimate climbed back into the 4% range and weekly unemployment claims remain contained. Even some of the more cautious forecasters have revised growth expectations higher. Walmart’s weaker guidance last week was one of the few softer datapoints, but broader spending data shows consumer strength, not retrenchment.

The most important development may be occurring beneath the surface in liquidity conditions. Weekly deposit data surged again, and excess deposits relative to prior trend growth have now risen roughly two percentage points over the last three months. Annualized, that implies liquidity growth exceeding 8%. That is not trivial. It strongly suggests the financial system is accommodating increased borrowing and spending tied to higher energy costs and further inflation. This materially shifts the balance of risks for monetary policy. Earlier in the year, the debate centered around when the Fed would ease. Increasingly, the evidence points toward policy needing to remain restrictive for longer, and perhaps even maintain a tightening bias.

The confirmation and swearing-in of Kevin Warsh as Fed Chair adds another layer of uncertainty. President Trump refrained from publicly pressuring Warsh to cut rates immediately, instead saying only that he should “do what you have to do.” Markets have gradually become more skeptical about the likelihood of near-term rate cuts. The rise in the 10-year Treasury yield earlier this week reflected that adjustment. Futures markets are pricing at least one hike, but as I have often emphasized, Fed futures frequently underestimate the persistence of inflationary pressures during periods of excess liquidity.

Warsh himself may alter the Fed’s communication framework. There is growing speculation he could eliminate explicit forward policy “bias” language altogether, preferring a more flexible and data-dependent posture. His first major comments ahead of the June FOMC quiet period will therefore be extraordinarily important for markets trying to assess whether the Fed remains mildly restrictive or is preparing to harden its stance further.

This week’s data calendar will provide several important tests. We will receive M2 money supply data, the Case-Shiller home price index, and the PCE inflation report. Although backward-looking, April inflation data will help determine how much of the recent increase in oil and gasoline prices is bleeding into broader core inflation measures. That transmission effect remains critical for the Fed outlook.

At the same time, enthusiasm surrounding AI, hyperscalers and potential blockbuster IPOs such as OpenAI and SpaceX continue to fuel speculative appetite. These could become some of the largest financial events of the year. The excitement itself is evidence that monetary conditions are not truly tight. We are not witnessing the extreme speculative excesses of 1999, but chip stocks and AI-related equities are increasingly pricing in extraordinary growth assumptions far into the future. Investors need to recognize that these valuations remain highly sensitive to technological competition.

Still, I continue to resist broad claims that the Magnificent 7 are universally overvalued. This remains a historically unique group of companies with unprecedented cash generation, scale and strategic positioning within the AI buildout. Their dominance complicates traditional growth market cycles. The bigger macro story remains that liquidity is still abundant, and economic growth remains surprisingly firm. The Fed may find itself unable to ease policy nearly as quickly as markets had hoped only a few months ago, but earnings momentum is offsetting the lack of Fed easing.

Copyright © WisdomTree

You don’t have to go very far to find lots of negative commentary in the popular press about the current state of the US economy.  High gas prices (due to a “war of choice”) are squeezing consumers’ budgets, and so the economy is headed for a ditch.  Many economists look back at history and blame lots of recessions on oil prices alone.

In terms of the official inflation reports, the popular narrative has a point.  Over time, inflation is a monetary phenomenon, but in the very short term an oil price spike can change measured inflation because consumers (and businesses) dip into savings temporarily to spend more and the basket of goods and services used to measure inflation doesn’t immediately change.

As a result, the Consumer Price Index is up 3.8% from a year ago, which is well above the Federal Reserve’s 2.0% target.  This will likely keep the Fed from cutting short-term interest rates for at least the next few months.  However, an oil price shock is typically a temporary issue.  And the impact on the economy has been muted.  After adjusting for inflation – things appear not much different than before the war with Iran started.

While events in the Middle East are dramatic, we look at broader macro trends. To us, it’s surprising the economy has not paid more of a price for the reversal of massive COVID stimulus.  Deficits have been relatively stable and the money supply has slowed dramatically.  If the economy slowed, it would be because of this, not an oil price supply shock.

We also think US stocks are overvalued, although saying that repeatedly doesn’t mean they will fall, no matter what our official forecast is.  We are math and model driven, we are not traders and we have no way to judge pure momentum trades.

We also don’t think we’re on the verge of a 1980s-90s style economic boom, in spite of advances in Artificial Intelligence and technological innovation more generally.

The size of government is substantially larger than it has been anytime during the age of the Internet.  For the past 20-25 years average real growth in the US has been just about 2% per year.  This is less than half the growth the US experienced in the 20 years post-WWII, and it is happening in spite of incredible new technologies that should raise productivity.  More resources being allocated by politicians rather than market forces always slows growth.

So, while we see what some might call malaise because government is such a drain on the economy, the evidence of the economy being on the verge of a recession simply isn’t there, at least not yet.  We appear to still be in the Plow Horse economy phase, where our thoroughbred technological race horse must carry an overweight bloated jockey.

Real GDP grew at a 2.0% annual rate in the first quarter, and we think is growing at about a 3.0% annual rate so far in the second quarter.  The Atlanta Federal Reserve Bank’s GDP Now Model is even more optimistic for Q2, now projecting growth at a 4.3% rate.

In the meantime, initial claims for jobless benefits have averaged a very low 203,000 the last four weeks, lower than they were a year ago, six months ago, and three months ago.  Yes, job growth has slowed, but we think this is largely related to the shift to roughly net zero immigration over the past year or so.

Manufacturing production is up 1.2% from a year ago, which is not great, but not a sign of recession, either.  For comparison, manufacturing was down at a 0.4% annual rate in the ten years that ended in April 2025.

We get a report on April durable goods orders on Thursday and expect a big number, led by more aircraft orders.  Yes, aircraft orders are volatile from month to month, but airlines ordering more planes suggest they see through the fog of the recent conflict and all is not gloomy ahead.

Yes, much of recent economic growth is being led by AI and data centers, so a case can be made that economic growth is not very broad.  But at least the limited boom in AI and data centers is coming primarily from market forces, not government-directed malinvestment like housing in the early 2000s, or government-sponsored “green energy” of recent years.

All is not well with the US economy, but the narrative of doom and gloom is being oversold as well.

Brian S. Wesbury – Chief Economist
Robert Stein, CFA – Deputy Chief Economist

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Copyright © First Trust Portfolios

Most have likely come across the concept of the K-shaped economy – given our industry does love to put letter shapes on things. In this case the K denotes a split in the U.S. consumer, with some doing really well (the upward sloped arm of the K) and some doing really poorly (the downward sloping arm of the K). Folks who own assets, stocks, property, businesses, are doing fabulously well. Markets near all-time highs and up a lot, the Bloomberg World Equity index has annualized 21% over the past three years. This has a tremendous wealth effect on consumers, but really just those with enough net worth invested in assets.

On the flip side, those that don’t own a lot of assets are dealing with wages that are growing but barely as much as inflation. Inflation, still high, is a tax on consumption so anyone who spends more on consumables is impacted more. If you are a big saver, its impact is not as strong. Add to this gasoline prices of $5 a gallon, up over 50% since the start of the year (U.S. average). Interest costs remain high and show little sign of coming down given the recent uptick in inflation. And most would agree, policy in the U.S. over the past bit has certainly been skewed to benefiting the wealthy vs. the less wealthy.

The K-shaped mood is certainly evident in consumer sentiment surveys. The University of Michigan Consumer Sentiment Index (in the chart above) asks consumers about a number of things with the attempt to garner their willingness to buy stuff. It covers aspects like personal finances, general business conditions, what the markets are doing and prices. In May, it reached its lowest level since the survey inception in the late 1970s! So based on this survey, consumers are more in the dumps than during COVID, the financial crisis, or the high inflation period in the late 1970s / early 80s. Are things really that bad?

Historically, changing consumer sentiment has correlated with moves in the stock market. It’s hard to say whether a happier spendy consumer makes the stock market go up or the market going up makes consumers happy. A bit of a chicken-and-egg issue. Today though, markets are at new highs and the consumer is catatonic. This is very odd but there are some factors contributing to this divergence:

1. Surveys – The efficacy of surveys has been on the decline over the past few years. Polls fall into this grouping as well. It seems respondents often answer one way and behave differently. And the response is more often negative, even if many consumers are clearly still spending.
2. Composition – The market is asset weighted, meaning the attitude of the wealthy has a much bigger market impact than the attitude of those less wealthy. The S&P 500 is certainly not an equal democracy. However, factor #1 may be more significant because if you break down the consumer sentiment by income, the wealthy are in a marginally better mood than the lower income cohorts, but not by much. Maybe everyone is grumpy.

Survey nuances aside, folks are not happy or confident. Inflation, gas and interest rates are a tough combo right now. Plus, job growth has been very lacklustre. A lot of moving parts in labour from participation rates, demographics, immigration and maybe AI. This does appear to be making unemployment trends higher at the ‘new entrant’ cohort, while remaining low and stable at more tenured employees. This may also be contributing to the recent uptick in productivity, maybe AI or less new entrants. Sorry new entrants, despite your eagerness you just aren’t productive for some time.

Fortunately, the upper arm of the K simply matters much more for not just the stock markets but for the economy.  So, while the lower arm of the K is struggling, the upper arm is spending, travelling, doing enough to keep total consumer spending growing. To be fair, the economy has always been K shaped, this isn’t new. Perhaps the spread is just getting wider.

Watch the Rich

With lower income cohorts struggling and higher income cohorts doing well, we should keep an eye on the spending habits of the higher income folks. Because fair or not, they have an outsized influence on the broader economy. So how does one gauge their mood and spending habits?

We have come up with four metrics, two on the services and two on goods. Travel is also a discretionary component of spending and tilted towards higher income consumers. Of course, business travel skews this data. Pricing is also a challenge, as we can see a big upswings in airfare spending recently but is this simply the result of rising ticket prices due to higher oil prices?  We will opt to track number of passengers moving through TSA security checkpoints.

Most high-end restaurants are private, so kind of hard to get a feel for volumes. However, we believe the trend in sit-down restaurants may provide some insight. Perhaps more across the income cohorts, the decision to eat out vs. eat at home or quick serve is certainly a discretionary spending decision influenced by your personal financial situation. After creating a composite of 11 publicly traded sit-down restaurant chains, we compiled the average same-store-sales over time.

The goods related spending indicators are cosmetics and luxury. While we can debate whether skin care is discretionary or not, it is a category dominated by higher income cohorts and historically has proven very cyclical. Measuring luxury spending involves mostly European companies. We created a composite of seven global luxury brand companies covering a diverse range from purses to fashion to watches.

Broadly speaking the trends are decent based on these metrics. Not improving but not rolling over either. We will take this as the upper arm of the K is still spending.

Final Thoughts

The consumer drives the global economy. In fact, the U.S. consumer alone accounts for about 18% of the global economy. No denying the lower income U.S. consumer is in a tough spot, but the higher end continues to spend, hence the K shaped economy. But don’t fret the K at this point, we would only become worried if evidence arose the wealthy are starting to dial back. If, or when, that happens, look out because there is not much support further down the income spectrum.

— Craig Basinger at Purpose Investments.

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Copyright © Purpose Investments

Sources: Charts are sourced to Bloomberg L.P.

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After three decades of watching market cycles play out from both sides of the trade, I’ve come to a simple conclusion: Wall Street’s love of simple rules is one of the most dangerous aspects of investing. When stocks fall 10%, it’s just a “correction.” However, if they decline 20%, it’s a “bear market.” Simple, clean, repeatable, and printed on every financial media graphic from here to Tokyo. The problem is that the definitions of a correction and bear market have not been updated since Alan Shaw developed them at Smith Barney in the 1960s. Moreover, the market those definitions were designed to describe no longer exists.

Currently, the S&P 500 index is roughly 83% above its long-term trend line, with the Shiller CAPE (cyclically adjusted price-to-earnings ratio) hovering near 40. That valuation level was only exceeded once in the history of American financial markets. The Fed’s balance sheet, still at $6.7 trillion, is more than eight times its pre-2008 level. Under these conditions, the old bear-market definition no longer measures what it was built to measure. A 20% decline from here doesn’t signal either a regime or price trend change. In other words, it would be only a “correction” within an ongoing bullish trend. That understanding is key to today’s discussion.

The Current Bear Market Definition Is Arbitrary

As noted, the “20% rule” traces to Alan Shaw, a technical analyst at Smith Barney in the mid-20th century. His framework was simple. Anything up to 10% was noise. A decline of 10% to 20% was a correction. Anything beyond 20% was a bear market. Shaw’s colleague Louise Yamada, who took over Smith Barney’s technical analysis practice in 2000, later described its staying power with characteristic directness: “It’s just so easy and simple to remember.”

Shaw’s framework made sense in its time. Markets in those decades lived much closer to a gravitational center of fair value. When prices fell by 20%, they often broke the market’s longer-term trend. A decline of that magnitude carried real information. It told you that selling pressure had overwhelmed buying, the market’s price trend had reversed, and the market’s direction of travel had changed from up to down. That’s precisely what the bear market definition was supposed to capture. A change in regime, not just a number.

The question is: after a 17-year-long bull market that stretched prices well beyond long-term trends, is Mr. Shaw’s measure still valid?

To answer that question, let’s clarify the premise.

• A bull market is when the market price is trending higher over a long-term period.
• A bear market is when the previous advance breaks, and prices begin to trend lower.

The chart below provides a visual of the distinction. When you look at price “trends,” the difference becomes both apparent and useful.

The distinction is essential.

• “Corrections” generally occur over short time frames, do not break the prevailing trend in prices, and are quickly resolved by markets reversing to new highs.
• “Bear Markets” tend to be longer-term affairs in which prices grind sideways or lower over several months as valuations revert.

What a Real Bear Market Actually Looks Like

The two genuine bear markets of this century make the definition’s original intent clear. Between March 2000 and October 2002, the S&P 500 lost nearly 49% of its value. It didn’t recover to its prior peak until 2007. Seven years lost. The bullish trend didn’t pause; it broke, and investors who sat through it got years of negative real returns with no policy rescue from Washington or the Fed.

The 2008 crisis was worse. From October 2007 to March 2009, the S&P fell about 57%. It didn’t return to its prior highs until early 2013. The price structure didn’t just dip below an arbitrary threshold. It collapsed, stayed down for years, and required one of the most aggressive monetary policy responses in the Fed’s history to eventually stabilize. That’s a bear market in the original sense of the word. A sustained, structural reversal of the prior bullish trend.

Now compare that to 2022. The S&P peaked on January 3 of that year, fell 25.4% to its October trough, and technically satisfied every condition of a bear market under the standard definition. By July 2023, every point of that decline had been recovered. By early 2024, the index was making new all-time highs. The 2022 decline was painful, but it did not reverse the underlying trend. Yes, prices fell, but found support well above any reasonable measure of long-term fair value, and resumed their climb. Putting the 2022 episode in the same category as 2000 or 2008 doesn’t just mislead investors; it tells the story exactly backward.

How the Fed Rewired the Market

To understand why the bear market definition needs to be revised, you have to reckon honestly with what the Federal Reserve has done to the market’s structural foundation. Before the 2008 financial crisis, the Fed’s balance sheet sat at roughly $800 billion. Modest. Stable. Largely inconsequential to equity prices on any given day.

Then came the crisis. The Fed launched three rounds of quantitative easing between 2009 and 2014, pushing its balance sheet to roughly $4.5 trillion. It tried to normalize beginning in 2018, then COVID hit. In two years, the balance sheet more than doubled again, from $4.3 trillion to nearly $9 trillion. As of April, 2026, it still sits at $6.7 trillion, even after years of several years of quantitative tightening.

That liquidity didn’t evaporate. It repriced every financial asset upward. It suppressed yields, starved investors of income alternatives, and effectively forced capital into equities regardless of underlying valuation. The market didn’t reach these levels because corporate America suddenly became dramatically more profitable. It reached them because the price of money was artificially held low for over a decade, which changed the math in every valuation model investors use. The result is a market structure with no historical precedent for its distance from the long-term trend.

What the P/Es Actually Tell You

The more bearish crowd consistently points to the Shiller CAPE ratio as a measure of impending doom. However, investors should understand that the CAPE ratio measures the market’s current price relative to 10 years of inflation-adjusted earnings. At 40, investors are currently paying 40 times that earnings figure for every dollar of S&P 500 exposure. That’s a lot by any historical measure, considering the historical median is 16x. The bear’s argument, and rightly so, is that the market has traded above 40 on the CAPE ratio only once before in its history, and that was at the dot-com peak. We know how that ended.

But this is important, as we have discussed many times, the problem is that valuation measures are just that – a measure of current valuation. More importantly, when valuations are excessive, it is a better measure of “investor psychology” and the manifestation of the “greater fool theory.”

Notably, valuation models are not, and were never meant to be, “market timing indicators.” There are many articles penned suggesting that if a measure of valuation (P/E, P/S, P/B, etc.) reaches some specific level, it means that:

1. The market is about to crash, and
2. Investors should be in 100% cash.

Such is incorrect.

What valuations provide is a reasonable estimate of long-term investment returns. It is logical that if you overpay for a stream of future cash flows today, your future return will be low. We can see this evidence by comparing the 10-year total return of a $1000 investment in the stock market to Shiller’s CAPE ratio, as noted above.

However, here’s where it gets interesting. Even if you don’t use the long-term median as your target, the math of mean reversion is sobering at any reasonable level. At the time of this writing, we can map each scenario from the S&P close of 7,399 (May 10, 2026), and the picture becomes clear.

Notice what that table shows. A 20% decline from current levels leaves the market at roughly 32x cyclically adjusted earnings. That’s twice the historical median. The market doesn’t even begin to approach a valuation floor that has historically supported the start of a new secular bull market until you’re down 50% to 60% from here.

That’s not a prediction; that’s arithmetic, and the difference between a correction and a bear market in today’s financial markets.

The recovery math compounds the problem. A 30% loss requires a 43% gain just to break even, before accounting for the time lost while recovering. A 50% loss demands a full 100% return to get back to where you started. For investors in or near retirement, that’s not a temporary setback. That’s a structural threat to financial security.

“A 20% decline from a market that’s 83% above trend doesn’t reach trend. It barely dents the excess. The old bear market definition was built for a different world, and that world no longer exists.”

Two Halves To A Full Cycle

I wrote about this in August 2020, right after the COVID crash had recovered, and everyone was declaring it the shortest bear market in history. My argument then was the same one I’m making now: March 2020 was a correction, not a bear market, because it never broke the long-term bullish price trend that started in 2009. The same is true of 2022. And of the Iran-related correction we saw in early 2026. Those were all pressure releases within an ongoing bull market. None of them completed the cycle.

Because that’s the part Wall Street glosses over. Every bull market is only half of a full market cycle. The second half, the bear, is when the excesses accumulated during the upswing, the overvaluation, the leverage, the speculative positioning, get wrung out through a sustained decline that resets prices back toward fundamental value. That process has played out after every major bull market in the historical record. From the 1929 collapse to the 1970s grind, the dot-com bust, and the financial crisis. None of them was optional; they were just the structural corrections of prior excesses.

The bull market that started at S&P 683 in March 2009 is now 17 years old. It’s the longest on record and has been sustained by:

• Three rounds of QE,
• A zero-interest rate policy for most of a decade,
• $5 trillion in pandemic stimulus, and
• A generational AI investment cycle that’s still in its early innings.

All of that is real. But none of it changes the underlying valuation math, and eventually, prices will reflect fundamentals. They always do. The problem for investors, however, isn’t whether a real bear market will happen; it’s when, and more practically, whether your portfolio is built to survive the transition.

As noted, the 2020 and 2022 declines share one critical feature: both recovered before prices touched the long-term trend line shown above. They were corrections in an ongoing bullish trend, and both required a significant Fed or fiscal response to stabilize. A genuine bear market, one that resets valuations toward historical norms, would require neither a quick recovery nor a policy rescue. It would require a decline large enough to reach that trend line.

The bottom line is that the 20% threshold isn’t wrong. It’s just not calibrated for a market that’s trading 83% above its long-term trend. In a world where markets lived near fair value, a 20% decline carried information about the trend. Today, it carries sentiment information. That’s a meaningful difference, and it changes how you should think about both potential corrections and portfolio risk.

Stop anchoring your risk budget to the 20% number.

The relevant question isn’t “how far has this fallen?” It’s “how far is this from where prices would need to be for the bull market trend to genuinely reverse?”

Right now, that gap is enormous. A real bear market, in the structural sense, would likely need to be a 30% to 50% decline, and possibly deeper, before prices would reach the kind of valuation support that has historically ended bear markets and started new secular bulls.

That doesn’t mean panic. It means position sizing, risk management, and stop-loss disciplines need to account for a potential drawdown far larger than the 20% threshold Wall Street treats as the danger zone.

We continue to suggest that investors maintain appropriate hedges, keep risk allocations proportional to their time horizon and income needs, and resist the “buy the dip” impulse when the dip doesn’t actually bring you closer to value.

Make no mistake, the trend is still up. The AI investment cycle is real, earnings are growing, and the tape remains technically constructive at current levels. But the distance between current prices and genuine long-term fair value is wider today than at any point outside the dot-com peak. That’s not a reason to be out of the market. It is a reason to know exactly what you own, why you own it, and what your exit plan looks like if the second half of this cycle finally arrives.

Copyright © RIA

Listen on The Move

Larry Swedroe has spent 30 years proving the market will almost always beat you — and in this episode, he explains why that's about to become even more true.

In this episode of Raise Your Average, hosts Pierre Daillie and Mike Philbrick sit down with legendary evidence-based investing author and outsourced CIO Larry Swedroe for a wide-ranging masterclass on where markets are heading and what investors must do to survive them. Swedroe breaks down how AI is accelerating market efficiency rather than unlocking alpha, why the 60/40 portfolio carries far more equity risk than most investors realize, and why true hyper-diversification — across private credit, reinsurance, return stacking, and long-short factor strategies — is the only credible response to a world where correlation assumptions break at exactly the wrong moment. He confronts the behavioral mistakes social media is making worse, challenges advisors to stress-test risk tolerance with real dollar numbers, and argues the future of wealth management belongs to those who master alternatives.

⏱ Chapters

00:00 — Cold Open: AI and the Adaptive Markets Hypothesis
02:00 — Welcome to Larry Swedroe
03:00 — Post-Retirement Life: Consulting, Writing, and Giving Back
09:00 — AI and Market Efficiency: Does Technology Create or Destroy Alpha?
11:00 — Factor Model History: CAPM, Fama-French, and Shrinking Active Alpha
14:00 — Warren Buffett's Disappearing Alpha
21:00 — The Danger of AI Data Mining and False Correlations
23:00 — What Makes a Factor Worth Owning: Persistent, Pervasive, Robust
28:00 — Leverage Aversion: When a Little Is Good and a Lot Is Dangerous
30:00 — Private Credit and the Case for Senior Secured Loans
31:00 — Return Stacking and Portable Alpha
34:00 — Hyper-Diversification: Why Your 60/40 Is Really 90/10 in Risk Terms
39:00 — The 40-Year Period Growth Stocks Underperformed Long Treasuries
40:00 — Reinsurance and AQR Style Premium: Self-Healing Assets and Impatience
45:00 — The Real Definition of Diversification: Something Is Always Hurting
47:00 — Good Advisors Are People Managers, Not Money Managers
54:00 — Stress-Testing Risk Tolerance with Real Dollar Numbers
56:00 — Monte Carlo and the True Cost of Avoiding Alternatives
59:00 — Trend Following: Clustered Returns and Why You Buy Insurance at a Cost
01:05:00 — Behavioral Mistakes in the Age of Social Media
01:07:00 — Information vs. Value-Relevant Information: Why Reddit Won't Make You Rich
01:11:00 — The Future of Advisory Practice: Wealth Management and the Next Decade

🔍 Keywords

Larry Swedroe, evidence-based investing, factor investing, market efficiency, AI and investing, adaptive markets hypothesis, 60/40 portfolio risk, hyper-diversification, return stacking, portable alpha, private credit, reinsurance investing, AQR style premium, trend following, CTA funds, managed futures, behavioral finance, investment mistakes, recency bias, Monte Carlo simulation, retirement planning, alternatives allocation, illiquidity premium, wealth management, outsourced CIO, Raise Your Average podcast, Pierre Daillie, Mike Philbrick, Fama French, Warren Buffett alpha, value investing, momentum investing, long short strategies, sequence of returns risk, tail risk

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Yes, this time is different, but not because inflation itself is unprecedented. What has fundamentally changed is the macroeconomic starting point. Unlike the post-Global Financial Crisis period, when persistent disinflation and repeated downside surprises dominated policy decisions, the economy today is operating in a world where structural disinflation is no longer the default backdrop. That shift has important implications for monetary policy and, ultimately, for markets.

In the decade leading up to the pandemic, the Federal Reserve (Fed) adopted a deliberately patient approach to inflation, allowing price pressures to overshoot the target for extended periods before responding. That framework was a rational response to nearly twenty years of disinflationary forces ranging from globalization to technological change that continually pushed inflation below target. However, that same framework proved ill-suited for the post-pandemic recovery. With hindsight, the Fed should have begun tightening policy earlier as inflation emerged in 2021. But even if the Fed had increased rates immediately as it should have, it is highly unlikely that they would have been able to prevent the increase in inflation and contain Americans as they rushed to “living la vida loca” after years of sheltering in place and postponed consumption. In that environment, it is difficult to imagine an interest-rate level capable of meaningfully restraining spending without causing severe collateral damage to growth and employment. Policy was behind the curve, but the curve itself was unusually steep.

Standard policy benchmarks reinforce this point. Taylor Rule estimates suggest that monetary policy during the recovery was materially more accommodative than warranted, with implied policy rates at times approaching double digits (see graph below). Even under more conservative assumptions, prescribed rates were well above the levels actually in place, underscoring how far policy lagged shifting inflation dynamics. By the time liftoff finally began in early 2022, inflation had already surged close to 8% year over year, forcing the Fed into a far sharper tightening cycle than markets had anticipated.

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Fast forward to today, and the policy landscape looks very different. The Fed is no longer constrained by the zero lower bound, and global disinflation can no longer be taken for granted. While fiscal expansion remains an upside risk to prices, the more immediate concern is that inflation has lost its pre-pandemic anchoring. Even setting aside tariffs and recent oil price increases tied to geopolitical tensions with Iran, inflation is no longer gravitating back toward the stable sub-2% environment that characterized the prior cycle. That reality sharply reduces the Fed’s room for patience.

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Recent CPI, PPI, ISM price indices, and import price reports underscore this point. While April’s CPI included some one-off distortions – most notably in shelter costs linked to last year’s government shutdown – broader price pressures were evident across multiple categories. The PPI data are even more concerning, suggesting pipeline pressures that could bleed into consumer prices over the coming quarters. ISM prices indices, which are important forward-looking indicators, reached three-year highs in April, showing that input prices are affecting both manufacturing and service industries. Lastly, import prices experienced their largest monthly increase since March 2022, the period immediately following the onset of the Russia–Ukraine conflict. These reports do not demand an immediate rate hike, but they materially raise the odds that the policy discussion shifts from when cuts begin to whether further tightening may be required.

From a market perspective, this matters less for the next meeting and more for the trajectory of expectations. The longer inflation remains above target, the harder it becomes for the Fed to credibly signal an easing cycle, particularly in an environment characterized by expansionary fiscal policy, resilient growth, a gradual recovery in labor markets and sustained capital investment tied to artificial intelligence. Add continued energy price risks to that mix, and the bias of policy risk tilts meaningfully in one direction.

Bottom line

The rate conversation is set to intensify over the coming months. Markets are once again being forced to confront a world in which policy rates may stay higher for longer – or even move higher – rather than glide lower as soon as growth moderates. The arrival of a new Fed chair this month adds another layer of uncertainty, as shifts in leadership can influence both communication and policy direction. Taken together, the policy outlook is becoming more uncertain with fewer clear signals on the path forward.

Copyright © Raymond James

Much has already been written about capital spending, but it’s worth lingering here a bit longer - if only to look at it from a slightly different angle. Rather than focusing on company‑level disclosures or the now‑familiar technology capex narrative, consider capital spending from an economic vantage point: manufacturers’ durable goods orders. It’s a narrower slice of the economy - firms that actually make things - and the data can be lumpy, which is why economists often focus on “core” durable goods, stripping out volatile defense and aircraft orders. Still, when manufacturers are stepping up orders for long‑lived equipment, it’s one of the cleanest real‑time signals we have of a capital spending rebound. And that is exactly what the data are showing today.

The recent acceleration has pushed year‑over‑year growth into the top quintile of its historical range. If your instinct is that more spending on equipment should pressure profits or slow hiring, history consistently argues the opposite. Periods of stronger capital investment have been associated with more hiring over the subsequent year and more durable earnings growth. It turns out capital spending is not just a reflection of growth - companies tend to invest when they have the cash - but a creator of it as well. Holding “all else equal” is harder than it sounds, and this is a good example of why.

That brings us to the next issue: diffusion. With the headlines dominated by AI and hyperscaler investment, it would be reasonable to assume this rebound is purely a technology story. But the data push back on that narrative as well. Of the seven major categories within durable goods orders, only two are directly technology‑related - and six are currently accelerating. The lone laggard is transportation, a category that is famously volatile. In other words, this capital spending rebound extends well beyond tech alone. That breadth matters.

Earnings growth is far more likely to be sustained when spending revives across industries, not just within a narrow slice of the market. Recall that median earnings growth for the S&P 500 has only recently emerged from nearly three years of contraction. The early signs suggest that this inflection is real - and increasingly durable. And when earnings growth broadens and persists, it continues to provide fundamental support for the secular bull market. The headlines may focus on where capex started, but the more important story is where it’s spreading.

This information is provided for educational purposes only and is not a recommendation or an offer or solicitation to buy or sell any security or for any investment advisory service. The views expressed are as of the date indicated, based on the information available at that time, and may change based on market or other conditions. Opinions discussed are those of the individual contributor, are subject to change, and do not necessarily represent the views of Fidelity. Fidelity does not assume any duty to update any of the information.

Copyright © Fidelity Investments

The stagflation narrative dominating financial social media isn’t completely wrong. That’s what makes it so dangerous. After more than 30 years of managing client portfolios through actual inflationary cycles, not watching them on YouTube, I’ve learned that the most damaging investment advice isn’t built on outright lies. It’s built on partial truths, stretched past the point where the data still holds.

If you haven’t read Commodity Supercycle: The Enemy Of The Bull Thesis (Part 1), it is an important primer to today’s discussion.

Let’s dig in.

The doomers have legitimate inputs. Supply chains are genuinely under pressure, and the dollar currently faces real structural headwinds. Central banks have been buying gold at a historic pace. Equity valuations in certain segments are stretched, and every one of those observations is defensible. However, the leap from those observations to “sell everything, go all-in on commodities, bonds are dead forever, the great reset is here,” is where the analysis ends and the storytelling begins.

I want to do two things here. First, I’ll score the stagflation narrative claim-by-claim. We will give credit where it’s earned and expose where the logic collapses. I’ll lay out what a sound investment framework actually looks like when the data, not the narrative, drives the decision. Moreover, why the boom-bust nature of commodity markets and the AI-driven capex cycle both fundamentally change where allocations belong.

The Stagflation Narrative Spreading Across Social Media

Spend an hour on X, and you’ll encounter some version of the same script.

• The Federal Reserve has destroyed the currency.
• The 1970s are back, only worse.
• Commodities are going to surge for the next decade.
• Gold is the only real money.
• Bonds are a guaranteed way to lose purchasing power.
• Anyone still holding a diversified portfolio is either naive or not paying attention.

The 1970s comparison is the narrative’s analytical spine. Commodity prices surged for the better part of a decade while equities went nowhere in real terms. Gold went from $35 an ounce to over $800, and the people who held hard assets looked prescient for years. It’s a compelling story, with the added appeal of casting the narrator as the maverick who sees what the establishment refuses to acknowledge.

Here’s the problem.

The 1970s worked the way they did because of structural economic conditions that no longer exist. Both the boom-bust nature of commodity cycles and the emergence of the AI-driven capex boom create dynamics that the doomer framework fails to incorporate.

Before I take this apart, I want to be clear about something. The inputs behind the stagflation narrative deserve serious consideration. As such, dismissing them entirely would be just as intellectually sloppy as swallowing them whole.

As I laid out in Part 1 of this series, supply inelasticity is real. More than a decade of ESG-driven capital discipline, underinvestment in exploration, and production curtailment has left several commodity markets unable to respond quickly when demand rises. That constraint doesn’t vanish because we want it to. It gives the commodity cycle real legs, supporting the bull thesis for select commodities over a meaningful but finite window.

The dollar does face genuine headwinds. Structural fiscal deficits, a Federal Reserve with a long track record of accommodation, and geopolitical pressure on the reserve currency system are all real concerns. JPMorgan projects gold at $5,000 per ounce in 2026, as central bank accumulation runs at roughly 585 tonnes per quarter. There are also pockets of equity valuations that are stretched enough to carry real multiple-compression risk if earnings disappoint.

So the inputs are legitimate. Therefore, there is a version of the commodity trade, sized correctly and timed with discipline, that makes sense right now. The doomer narrative isn’t wrong about the forces in play. It’s wrong about what those forces mean, how long they last, and how to construct a portfolio around them.

Where the Narrative Falls Apart

The entire doomer framework rests on one foundational assumption: the 1970s stagflation cycle will repeat itself. Therefore, a 1970s portfolio, heavy on commodities, short on bonds, light on equities, will produce 1970s results. Unfortunately, that assumption doesn’t survive contact with the structural differences between the two economies.

The U.S. economy in the 1970s was built on manufacturing, which accounted for roughly 25% to 28% of GDP. Most crucially, it had a large unionized workforce with cost-of-living clauses written directly into labor contracts. When commodity prices rose, wages rose automatically. In other words, rising costs triggered wage increases, which sustained purchasing power, which kept spending alive even as prices climbed. That feedback loop extended the cycle for years.

The U.S. economy today is roughly 70% to 75% services, and manufacturing accounts for approximately 11% of GDP. The COLA-adjusted workforce is gone. Therefore, when commodity prices rise today, the increase doesn’t trigger wage catch-up. Instead, it functions as a direct tax on purchasing power, and consumers absorb it immediately. What took years to produce meaningful demand destruction in the 1970s now shows up in six to twelve months.

“The 1970s cycle ran on wage indexing. Without it, commodity inflation becomes a demand tax, and demand destruction arrives fast. That is the analytical flaw at the core of the doomer stagflation narrative.”

The Inflation Sequence

The doomer version of the stagflation narrative treats the inflation phase as permanent. It isn’t. It’s a phase inside a sequence, and the sequence has a specific ending that the all-in commodity thesis is completely unprepared for.

1. Commodity prices rise. Input costs surge.
2. Consumers carrying record debt loads pull back.
3. Business investment contracts.
4. Growth slows.
5. The Fed pivots.
6. Rate cuts follow.
7. Bond prices rise.

In other words, the same event that terminates the commodity rally launches the bond recovery.

We saw this exact sequence in compressed form between 2022 and 2024. Commodities surged amid the Russia-Ukraine shock and pandemic-related supply chain disruptions. Bonds had their worst calendar year in modern history. The doomers called it permanent. Then growth wobbled, the Fed pivoted, and by 2024 intermediate Treasuries had recovered sharply while commodity prices corrected from their peaks. The people who abandoned bonds entirely after 2022 missed a significant rally and held concentrated commodity exposure through the drawdown.

The doomer stagflation narrative is built to profit from Phases 1 and 2, but it has no plan, framework, or exit discipline for Phases 3 through 6. That is where the damage happens.

The Gold Logic and the Bond Mistake

Gold deserves a real discussion, because this is where the doomer stagflation narrative contains its most glaring internal contradiction. Own gold, the argument goes, because the dollar is collapsing and you need to escape a failing monetary system.

Gold is priced in dollars and traded in dollar-denominated markets. Its entire value proposition is measured against the purchasing power of the US dollar. When someone argues that the dollar is collapsing and the solution is a dollar-denominated asset, the argument refutes itself. Central banks buying gold aren’t abandoning the monetary system; they’re diversifying their reserve compositions within it. The Chinese People’s Bank is reducing its concentration in dollar-denominated Treasuries, specifically, but that is a rotation within the system, not an escape from it.

Gold earns a real place in a sound portfolio as a hedge against policy error, inflation (which is what the debasement argument refers to), and geopolitical stress. A 5% weighting of a portfolio allocated to gold, sized appropriately for its volatility, is a defensible position backed by institutional demand data. 50% of a portfolio concentrated in gold because the financial system is “about to collapse” is speculation with an apocalyptic narrative.

The bond mistake is where the most retail damage has been done. The doomers drew a permanent conclusion from 2022’s historically bad bond year. What they missed is that the inflation phase that crushed bonds in 2022 is the same mechanism that eventually forces the Fed to cut rates, which drives bond prices higher. Walking away after the loss and missing the recovery is the most expensive way to be partially right.

I’ve been doing this long enough to know that the most dangerous market narratives are the ones that are right about enough to feel credible all the way through. The stagflation narrative qualifies. Here is every major doomer claim, scored against what the data actually shows.

High Prices Cure High Prices

There’s a mechanism the doomer stagflation narrative never seriously models, and it’s the most reliable force in commodity markets: high prices cure high prices. When commodity prices rise far enough, they do three things simultaneously.

• They incentivize new supply investment
• Activate marginal producers who couldn’t profitably operate at lower price levels (increasing supply)
• And they accelerate demand substitution as consumers and businesses find alternatives.

The ESG and underinvestment thesis that Part 1 establishes is real and important, as it delays the supply response and extends the cycle beyond what a typical demand shock would produce. But it doesn’t eliminate the supply response. It sets the clock to a longer timer. The critical insight for portfolio construction is that the timer runs at different speeds for different commodities, and that determines how much of each you should own and how tightly you need to manage the exit.

The 2011 oil market is the canonical example, as West Texas Intermediate Crude traded around $100 per barrel for three consecutive years. During that stretch, the price level didn’t feel unsustainable to the doomers of that era, either, and peak oil narratives were everywhere. Then, oil producers, directly incentivized by those high prices, flooded the market with supply. By early 2016, WTI was trading at $26. The doomers who held concentrated energy positions through that collapse, because the “structural case was intact,” experienced the full arithmetic of boom-bust without a framework for managing it.

CONSISTENCY WITH PART 1  The ESG and underinvestment constraints that Part 1 identifies extend the supply response timeline, but they don’t eliminate it. Gold has the longest clock. Energy has the shortest. That difference in supply response curves should directly determine relative position sizes and exit discipline.

Investment Strategy For Today’s Environment

The doomer stagflation narrative misses a second major dynamic entirely: the AI-driven capital expenditure cycle running through the U.S. economy creates a domestic earnings multiplier that didn’t exist in prior stagflation episodes. Microsoft, Oracle, Google, Amazon, and Meta alone are spending hundreds of billions on AI infrastructure that will approach $1.1 trillion by 2027. That capital flows directly into semiconductors, power infrastructure, and data center supply chains, which in turn creates a domestic growth differential with no comparable international analog.

That “multiplier effect” is critical to this story as discussed previously in “The Deficit Narrative May Find Its Cure In AI.”

The American Society of Civil Engineers (ASCE) estimates that every $1 billion in infrastructure investment creates 13,000 jobs and adds $3 billion to GDP over a decade. Therefore, if the U.S. invests $1.8 trillion in AI infrastructure by 2030—plausible given the $500 billion energy need, $300 billion for data centers (150 new centers at $2 billion each), and $200 billion for chip production—GDP could rise by $5 trillion over 10 years, or roughly $300 billion annually. However, that $1.8 trillion is only the beginning. McKinsey & Company expects spending to reach $6 trillion by 2030, just 5 years from now, equating to $18 trillion in economic growth.

That effect was already evident in the Q1-2026 GDP report, where nearly 75% of the 2% annualized growth rate was attributable to business investment in data centers. Currently, the U.S. is projected to grow at roughly 1.8% to 2% in 2026, while Europe struggles to hold 0.5% to 0.8%, and China manages a structural property and debt overhang. That earnings growth differential is real and durable throughout the buildout. The previous case for rotating toward international equities on valuation grounds has also weakened considerably. While European equities ran hard in 2024 and Indian equities now trade at multiples rivaling those of U.S. mid-caps, the broad international valuation discount has compressed.

That said, the AI capex argument carries two important constraints.

• First, the earnings are highly concentrated in roughly 8 to 12 companies. The rest of the S&P 500 still faces the same multiple compression risk in a stagflationary environment described in the article. Therefore, owning the broad index is not the same trade as owning the direct beneficiaries.
• Second, the capex cycle carries borrowed-demand risk, as these companies pull years of infrastructure investment into a compressed window. When capex growth plateaus, the GDP contribution reverses. The 1990s telecom buildout produced genuine earnings growth in infrastructure, yet ended in a brutal equity cycle when spending decelerated.

The framework that holds together across all of these dynamics, the commodity boom-bust cycle, the structural compression of demand destruction, the AI capex differential, and the bond recovery sequence, requires four separate allocation legs, each sized for its own cycle duration and exit trigger.

THE REVISED FRAMEWORK  The doomer stagflation narrative gets the commodity direction right for the first leg and wrong about the duration, the differentiation by commodity, the bond thesis, and the domestic equity landscape transformed by the AI capex cycle. Own what the data supports. Exit on the supply response clock, not the narrative.

Conclusion

Fear is a durable marketing strategy. The stagflation narrative will keep finding new audiences because it wraps legitimate macro concerns inside an emotionally satisfying story, a villain, a hero, and a clear trade. The people selling it know that partial truths are more persuasive than outright falsehoods. They also know that by the time the cycle turns and the narrative fails, their followers will attribute the losses to bad luck rather than bad analysis.

I’ve watched this play out repeatedly in commodity markets, from the commodity supercycle of 2007 to 2009 to the metals boom of the early 2000s to the oil market in 2011 to 2014. Every time, the same pattern: a legitimate supply constraint, a genuine price move, a narrative that extrapolated the trend into permanence, and then the eventual supply response that high prices had been quietly incentivizing all along. The cycle doesn’t announce its end. It just ends.

The commodity cycle developing now is real, and the AI-driven domestic growth differential is real. However, the bond recovery that follows demand destruction is also real. A portfolio that acknowledges all three, with targeted U.S. growth exposure in the AI infrastructure beneficiaries, U.S. value for the commodity cycle with a domestic earnings anchor, commodity and gold exposure sized by supply response clock rather than apocalyptic conviction, and intermediate bonds providing ballast, is built to survive the full sequence.

That’s the difference between investing in a cycle and betting on a narrative.

SOURCES

1.  J.P. Morgan Global Research, “A New High? Gold Price Predictions,” 2026. jpmorgan.com/insights/global-research/commodities/gold-prices

2.  Bureau of Economic Analysis, Historical GDP by Industry; Federal Reserve Bank of St. Louis (FRED), Manufacturing Value-Added as a Share of GDP, 1960–1980. fred.stlouisfed.org

3.  Bureau of Economic Analysis, GDP by Industry, 2024. bea.gov

4.  Federal Reserve Bank of New York, Center for Microeconomic Data, Household Debt and Credit Report, Q4 2024. newyorkfed.org

5.  Bloomberg, U.S. Aggregate Bond Index total returns, calendar year 2022.

6.  London Bullion Market Association (LBMA), Gold Price data, 2024–2025. lbma.org.uk

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