SpaceX's June IPO raised $75 billion, resulting in an initial valuation of $1.77 trillion, making it the largest IPO in history. SpaceX, encompassing its launch business, Starlink, and the recently merged xAI, peaked at a $2.5 trillion market cap in its first week of trading, briefly tying it with Amazon as the fifth-largest publicly traded company. After only a month, the enthusiasm is rapidly fading.

Perhaps most amazing of all, the fanfare is occurring despite SpaceX producing a net loss of nearly $5 billion in 2025. Based on its $1.84 trillion market cap, investors are clearly not worried about the present. They are excitedly pricing in astronomical growth for SpaceX.

To evaluate SpaceX from a fundamental perspective, investors need to quantify the implied growth in its valuation and compare it with their own and market forecasts. In this article, we attempt to help them by providing context for their growth expectations, using Amazon’s history as a proxy.

Amazon, like SpaceX, was priced at expensive valuations and ultimately delivered on those expectations. Initial Amazon investors who held through the dot-com crash and years of zero earnings have been rewarded roughly 3,300-fold, amounting to about 32% annualized for nearly three decades.

So, the question we pose: what does the Amazon playbook require of SpaceX?

Amazon

Amazon went public in May 1997 at $18 per share, valuing the online bookseller at $438 million. Revenue that year was $148 million. The market was pricing its shares at a price-to-sales (P/S) multiple of roughly 3x. At the time, the ratio was generous for a money-losing start-up, but defensible given that Amazon was doubling revenue every year. Importantly, those who envisioned that Amazon was much more than an online bookstore and appreciated its growth potential must have thought its price-to-sales ratio was dirt cheap.

What followed was one of the greatest periods of sustained revenue expansion in corporate history. Amazon crossed $19 billion in annual revenue in 2008, only eleven years after going public with $148 million in revenue. In 2025, Amazon generated $716 billion in revenue, putting it on par with Walmart as the highest-revenue company in the US. From its IPO to today, revenue has grown nearly 5,000-fold.

That trajectory is nearly unprecedented. Can SpaceX also fire on all cylinders?

SpaceX Today vs. Amazon Then

As the graph above shows, Amazon generated approximately $19.2 billion in revenue in 2008, nearly identical to SpaceX's $18.7 billion in 2025. In 2008, Amazon's market cap was slightly under $40 billion, implying a P/S multiple slightly above 2x. SpaceX, with a $1.84 trillion market cap and $18.7 billion in sales, trades at a P/S nearing 100x. The market is pricing SpaceX at approximately 50 times the multiple it gave Amazon at the same revenue level.

While the ratio difference sounds extreme, there are reasons to argue SpaceX deserves a premium:

• Its rapidly growing Starlink business generates $4.4 billion in operating income, with revenue compounding at a 50% growth rate. However, as we share in the first graphic below, its revenue growth is slowing, and average revenue per customer is declining.
• The reusable launch business accounts for over 50% of orbital rocket launches, as we share in the second graphic. That said, competition is increasing rapidly, especially from the well-funded Blue Origin, Jeff Bezos' rocket venture.
• There is promise in its AI infrastructure business through the xAI merger, but Anthropic, OpenAI, Gemini, and new open-source models like Kimi-K3 appear to hold a meaningful advantage.

The way to rationalize a near triple-digit P/S multiple is through extraordinary, historically unprecedented growth. So, let's quantify "extraordinary."

SpaceX's Implied Growth Rate

Let's work backward from SpaceX's $1.84 trillion market cap to gauge the growth needed to satisfy the market's implied forecast. To do so, we assume that investors demand a 20% annual return. While lofty, it is roughly a third below the 32% Amazon has delivered since its IPO.

If SpaceX shares compound at 20% per year for the next ten years, its market cap will reach $11.4 trillion by mid-2036, implying a share price near $860, assuming no new equity issuance.

With that proxy $11.4 trillion market cap in hand, the only remaining variable is the P/S multiple investors will pay for a mature SpaceX. That multiple determines the revenue it must produce. Consider two scenarios:

• Scenario one: SpaceX matures like Amazon. Amazon today, after 29 years of dominance across e-commerce and cloud computing, trades at roughly 3.7 times trailing sales. If SpaceX has the same multiple in 2036, it will generate about $3.1 trillion in annual revenue. For context, that approximates the entire GDP of France and roughly a tenth of US GDP. The implied revenue growth rate that clears this hurdle is 67% per year, compounded over ten consecutive years.

• Scenario two: SpaceX retains a higher premium multiple. A more generous P/S assumption eases the required revenue growth, but the implications are still daunting. At a P/S ratio of 20x in ten years, the required 2036 revenue falls to about $570 billion, roughly three-quarters of what Amazon generates today, and a level Amazon needed 27 years to attain. The implied growth rate is substantial at 41% per year for a decade.

To appreciate what a P/S of 20 means, we share the ratio of the 20 largest US stocks below. Broadcom at 29.2 and Nvidia at 24.9 are the only two above 20, and both are growing rapidly with enormous profits.

Amazon's single best ten-year revenue stretch, from 1997 to 2007, produced a 59% compound annual growth rate. But Amazon started with $148 million in sales and was just beginning to expand beyond books. SpaceX began at $18.7 billion, 126 times Amazon's starting point. Growth rates achievable from a small base are significantly easier than from a large one, which is precisely why only a handful of companies have ever sustained 40%+ growth for a full decade.

Time Out: What A P/S Of 20 Implies

It's worth pausing to stress what a P/S ratio of 20 implies. The best way to do so is to share the advice Scott McNealy from Sun Microsystems gave his shareholders in 2002.  

‘At 10 times revenues, to give you a 10-year payback, I have to pay you 100% of revenues for 10 straight years in dividends. That assumes I can get that by my shareholders. That assumes I have zero cost of goods sold, which is very hard for a computer company. That assumes zero expenses, which is really hard with 39,000 employees. That assumes I pay no taxes, which is very hard. And that assumes you pay no taxes on your dividends, which is kind of illegal. And that assumes with zero R&D for the next 10 years, I can maintain the current revenue run rate. Now, having done that, would any of you like to buy my stock at $64? Do you realize how ridiculous those basic assumptions are? You don’t need any transparency. You don’t need any footnotes. What were you thinking?’— Scott McNealy, Business Week, 2002

Elon Musk's Growth Forecast

Elon Musk's forward guidance warrants caution, as it is very aggressive. Days after the IPO, Musk posted the comment below on X.  Growing from $18.7 billion in 2025 to $1 trillion in 2030 is a 53-fold increase in five years, a compound growth rate of roughly 122% per year, more than double Amazon's best-ever pace and from a base thousands of times larger.

Suppose Musk delivers. The shareholder outcome still hinges entirely on the multiple. If the market awards a $1 trillion revenue base Amazon's current 3.7x P/S valuation, SpaceX's 2030 market cap would be roughly $3.7 trillion, about a 17% annualized return from today's price. At 20x, the same revenue produces a $20 trillion valuation and returns near 70% annually.

A 17% to 70% range on identical fundamentals illustrates the difficulty in our analysis: both variables, sales and the multiple, are unknowable, and the multiple alone can swing the outcome from ordinary to absurd.

Wall Street's Wide View

To be clear, SpaceX is unique. Starlink's subscriber economics provide a sustainable revenue base; the launch business has pricing power that thus far has not been challenged, and an xAI integration could, in the most optimistic scenario, open multiple trillion-dollar markets quickly. That said, analysts must carefully discount even the most tremendous forecasts.

To wit, the models from the SpaceX IPO underwriters sit far below those of Elon Musk. Morgan Stanley projects roughly $330 billion in 2030 revenue, and Goldman Sachs sees about $470 billion, both fractions of Musk's $1 trillion.

New Street Research, which initiated coverage with a $165 target, acknowledged the bullish thesis could work but noted investors need a "20 to 25-year time frame" for the math to resolve favorably.

Morningstar, by contrast, set the fair value for SpaceX at $63. As we share below, the $63 to $401 range of analyst price targets reflects the uncertainty surrounding the company’s potential.

Summary

Amazon rewarded patient investors immensely, but it did so from a mere $438 million IPO valuation. Compounding from $1.84 trillion, as SpaceX tries, is harder by orders of magnitude. SpaceX can be a great company and still prove disappointing to its shareholders. To justify today's price, its growth must be historically unprecedented, at a scale no company has ever operated, for longer than any growth cycle has ever lasted.

While that may sound bearish, this analysis doesn’t make SpaceX uninvestable. The stock will cycle through bullish and bearish periods as momentum ebbs and flows along a likely volatile path. Accordingly, traders will find plenty of opportunities on both sides. For those looking to buy and hold, however, the odds seem lofty. But, transcending financial forecasting, Musk has a proven track record of success, so it's too early to count SpaceX out.  

Can SpaceX do what only a very small handful of companies have ever done, or is the market once again pricing in a future that gravity will eventually catch up with?

The post Can SpaceX Fire On All Cylinders? appeared first on RIA.

Alphabet reports earnings after today's close, and Intel follows tomorrow. Together, they provide a first clue as to whether AI-related spending and investment continue at the brisk pace of the prior quarters.

Alphabet represents the demand side for AI models. Google's Cloud backlog nearly doubled sequentially last quarter to a record $462 billion, growing 63% year over year, the fastest pace among major cloud providers. That backlog is one important reason Alphabet and the other hyperscalers continue to allocate hundreds of billions of dollars to build out data centers. The problem, however, with their massive spending is declining free cash flow. Alphabet raised 2026 capex guidance to $180 to $190 billion and told investors 2027 spending will "significantly increase," despite free cash flow declining 47% year over year in the first quarter to just $10.1 billion (shown below). Watch whether Google Cloud's margin expansion continues and for any changes to capex guidance.

Intel represents the supply side of AI investment. Data center and AI revenue grew 22% last quarter as demand for its products increases and chip efficiency improves. Watch revenue and forward guidance for signs on whether AI investments from the largest companies continue to expand rapidly or if declining free cash flow is slowing capex investments.

What To Watch Today

Earnings

Economy

Fed Speakers

None scheduled. The FOMC is in its pre-meeting blackout ahead of the July 28 to 29 meeting, so there are no Fed voices to move the tape this week.

Market Trading Update

In our recent commentary, we walked through the momentum meltdown ripping through the chips and the high-beta names. Today, that story finally has a name. Spencer Jakab of the Wall Street Journal calls it bad breadth, and the label fits.

His metaphor is a duck. On the surface, the market glides along, calm and unbothered. Underneath, investors are paddling furiously. The VIX sits at 17.5, below its long-term average, so the index looks placid. The S&P 500 itself trades near 7,485, a stone's throw from its record, which is exactly the point. The headline masks the wreckage underneath. Look at single-stock volatility and the picture flips. The VIXEQ measure sits above 50, and the gap between the two just hit a record, according to Citadel Securities strategist Scott Rubner. Traders aren't bracing for a crash. They're worried about specific names, mostly the AI momentum crowd.

The simpler tell is cleaner still. BTIG's Jonathan Krinsky counts 52 sessions this year in which the S&P 500 closed one way while most of its members went the other way. That already ties the tumultuous 2000 for the third-highest count this century, and July isn't over. 2026 will almost certainly break the record. You can see the full history in the chart below.

This is Bob Farrell's Rule #7 in real time.

"Markets are strongest when broad and weakest when they narrow to a handful of leaders."

Divergence can mark a healthy leadership handoff. It can also preview trouble. BTIG's own read is the uncomfortable one. When these relationships normalize, it is likely to come from everything catching DOWN to the recent pullback in AI names, not from AI names catching back up to everything else.

The tape underneath supports the worry. Software turned toxic earlier this year. Chips flipped from a market engine to a bear trend inside a few days. The Magnificent Seven are lagging, and Oracle closed at a multiyear low on Monday, down roughly 50% from its early-June high. Tuesday's bounce, with the semis up more than 3%, doesn't erase any of that. Sharp reflexive rallies are a feature of downtrends, not proof of a bottom.

Tonight raises the stakes. With the Fed in blackout into next week's meeting and no marquee data on the tape, the multiple is on its own. Alphabet and Tesla both report after the close, and the estimates below frame the bar. Those two prints will tell us whether the mega-cap bid holds or joins the catch-down.

So we are treating this as a market to rebalance, NOT to chase. In the equity models, we have trimmed the most extended AI and semiconductor winners back toward target weight, lifted quality, and kept dry powder for better entries. Manage risk at the line, and let the breadth confirm the next leg before you commit fresh capital to it.

Nike

Nike has lost roughly 65% of its value since its November 2021 peak. With the stock trading near a decade low, and full-year revenues of $46.4 billion essentially flat on a reported basis, the question is whether Nike stock is an opportunity or a trap. To help answer the question, we provide a SWOT analysis below.

Strengths
Nike remains the world's most recognizable athletic brand with unmatched global distribution. Its dividend has grown an average of 11% annually over the past decade and remains well covered by earnings and cash flow. Nike's new CEO Elliott Hill is trying to execute a turnaround. This includes returning to wholesale and sport-focused marketing. Wholesale revenues grew 4% in Q4, an early signal his efforts may be working.

Weaknesses
Nike Direct revenues fell 7% in Q4 and 9% on a currency-neutral basis. Its gross margin compressed 1.3% to 40.2% in Q3 as discounting to clear excess inventory continues to pressure profitability. Revenue from China remains a persistent drag.

Opportunities
EPS is forecast to grow 60% over the next three years as the turnaround takes effect. The 2026 FIFA World Cup gave Nike a rare global marketing moment with 12 national team sponsorships. The average analyst price target of $59.58 implies nearly 40% upside.

Threats
Newcomers like On Holding and Hoka are taking market share in the premium performance footwear sector. Tariff uncertainty creates ongoing margin risk. Furthermore, there is speculation that Nike could be removed from the Dow Jones Industrial Average, a symbolic blow that would trigger passive fund selling.

At $41, Nike is priced for continued failure. The question is whether Hill's turnaround is fast enough to outrun the competition, which is gaining ground every quarter.

The graph below is from our "soon-to-be-released" SimpleVisor AI.

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Moonshot AI, a Chinese company, just released AI model Kimi K3. Kimi K3 is a 2.8 trillion-parameter open-source AI model that the company claims is the largest ever built. With Kimi K3, Moonshot AI believes it can compete with Claude Opus 4.8 and GPT-5.5 across several benchmarks, trailing the leading systems only marginally. The news is not about Kimi-3's capabilities but what open-source models may do to pricing power for the AI industry.

Open source refers to AI models whose underlying weights, architecture, or training code are made publicly available. Thus, users can download, run, modify, or build on them without paying licensing fees to the developer. This contrasts with closed or proprietary models like ChatGPT or Claude, which are only accessible through a paid API or app, with the underlying weights and training methods kept private.

Research from SemiAnalysis warns that "the rising share" of open-source capability "would fundamentally erode" any moat if the gap continues to close. While pricing may be a concern to the AI model industry, MoonShot AI security issues may be a problem for users. For instance, OpenAI disclosed that a supply chain attack linked to North Korea compromised a developer tool used by MoonShot AI. The Atlantic Council has warned that self-hosted open-weight models "can't be fully tested or inspected," leaving enterprises exposed.

This is precisely why OpenAI's $10 billion custom chip partnership with Broadcom is important. Purpose-built, dedicated hardware lets an AI lab control the full stack, model, silicon, and data pipeline, rather than exposing its customers to whatever an open-weight file contains. For chipmakers and data centers, who wins the model war has little impact, as training the MoonShot AI model consumes enormous compute power.

The graphic below is courtesy of Arena.AI via ZeroHedge.

What To Watch Today

Earnings

Economy

Fed Speakers: None scheduled. The FOMC is in its pre-meeting blackout ahead of the July 28–29 meeting (decision July 29).

Market Trading Update

In yesterday’s report, Michael Lebowitz showed how the cost of borrowing, not the spending itself, has become the real driver of the deficit. Today I want to take that same lens to the corporate side, because borrowing costs are where the AI trade’s biggest risk is now hiding.

Here’s the argument the credit bears are making, and it deserves a fair hearing. Goldman’s derivatives desk, in a widely circulated note from Brian Garrett, argues that the real threat to AI stocks was never in the stock market. It is in the bond market. Hyperscaler spreads have been widening, single-name CDS have been blowing out, and deal concessions are expanding, all while hyperscaler capex has become the single largest source of the global credit impulse. When the market doubts the return on that capex, credit is where it shows up first, and it has led equity drawdowns by two to four weeks in past stress. The strain is already visible in the tape, where implied correlation near 20-year lows tells you the S&P has become a poor proxy for the average stock.

Now here’s the other side, and it matters just as much. The broad credit market is not confirming the warning. The ICE BofA high-yield OAS sits near 270 basis points, within a hair of its multi-decade tights and nowhere near the 3.5% that flags late-cycle stress, let alone the 8% that signals recession. Investment-grade and BBB spreads are near 25-year tight spreads of around 1%. Monday’s tape agreed. The washed-out semiconductors and momentum names caught a bid, the equal-weight index gave a little back, and high-yield credit barely moved. That is NOT what systemic stress looks like.

The positioning data points in the same direction. Goldman’s prime desk shows hedge funds have net sold US technology in six of the past eight weeks, the heaviest stretch in over a decade of their records, cutting tech net exposure to the 2nd percentile of the past year.

The high-beta momentum pair is down 32% from its highs, matching prior washouts. In plain terms, the crowd has already done much of the selling. The stress is idiosyncratic, concentrated in the handful of mega-cap issuers that drive the credit impulse, not systemic. That concentration is the risk. As Howard Marks often noted, the credit cycle turns before the equity cycle, and it turns without asking permission.

For our models, this draws a clean line. In the ETF Sector Rotation and Equity Conservative Growth models, we stay up in quality and hold dry powder, watching two tells into Wednesday night’s Alphabet and Tesla capex referendum: the broad high-yield index and the S&P’s near-term CTA trigger around 7,446. If high-yield breaks above 3.5% and price loses 7,446 on volume, we will start to de-risk. Until then, this is a rotation to manage, not a crisis to flee. Watch credit markets, not the headline. Trade accordingly.

Momentum Mash

The key momentum ETF (MTUM) has underperformed the S&P 500 by 7% over the last 20 days. Other than gold miners, which have given up over 18% to the market, MTUM is the worst short-term performer. The second graphic shows the top ten holdings of the MTUM ETF. As shown, chip companies such as Micron, AMD, Intel, and Broadcom are the most oversold. However, their scores are not very oversold, indicating that they have more room to fall. The spectacular gains these stocks experienced help explain why the scores remain tame despite the sector's rout. It's worth noting that the high-beta ETF (SPHB) holds some of the same stocks as MTUM; thus, it is underperforming, as is MTUM.

Overall market breadth is good, with most sectors clustered within ±25 points of fair value. As the first graphic shows, the rotation is not necessarily value vs growth, as we have typically seen over the last few years; instead, prior underperformers seem to be taking charge.

It's worth noting that emerging markets are underperforming for the same reason as momentum: chip stocks. SK Hynx and Samsung account for nearly 14% of the ETF. It also helps explain why the sector outperformed during the first half of the year.

Why Retail Traders Constantly Underperform Over Time

Decades of data across global markets reach the same verdict: the more frequently retail traders trade, the worse they perform. The infrastructure has never been more inviting. The losses have never been more documented. Here are some key statistics we will dive into further.

Retail traders have never had it so easy. Zero commission platforms, options on your phone, social media feeds full of “10 bagger” tips, and a Reddit thread for every stock in the S&P 500. The infrastructure for frequent trading has never been more frictionless, more democratized, or more psychologically seductive.

And the evidence is overwhelming that it is destroying investor wealth at scale.

The data is not subtle. It is not marginal underperformance that can be dismissed as noise. Across decades of academic research, multiple global markets, and every asset class retail traders favor, from stocks to complex options, the conclusion is remarkably consistent: the more frequently retail traders trade, the worse they perform. Not slightly worse. Dramatically, often catastrophically, worse.

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The national deficit debate usually focuses on entitlement and defense spending. While they have merit, they miss the single largest driver of America's deteriorating fiscal picture. After the pandemic-related deficits, the cost of borrowing itself, not spending, has been the biggest deficit buster.

As shown in the first graph, in 2021, the government paid $482 billion in interest on $28.4 trillion of debt, at an average effective rate of 1.70%. Since then, interest rates have risen appreciably, with the interest on the federal debt for the current fiscal year expected to reach $1.35 trillion, at an average effective rate of approximately 3.44%. Today's average interest rate is more than double the 2021 rate and, importantly, is applied to a rapidly growing stock of debt due to new issuance and the rolling of maturing debt.

The second graph shows the deficit that would have resulted if interest rates hadn’t increased. In that hypothetical scenario, interest expense today would be around $650 billion, roughly half the current figure. The extra $684 billion in annual interest costs is not the result of deficit spending programs or legislative choices. It is purely due to higher interest rates.  The compounding effect on total debt is also significant. Lower interest costs would have produced smaller annual deficits, which means less borrowing accumulating interest of its own. In our scenario, the total federal debt under the 2021 low-rate scenario would be approximately $36.0 trillion, rather than $39.2 trillion, and debt-to-GDP would be 109.4%, rather than 119.2%.  For reference, the debt-to-GDP ratio was 107% before the pandemic-related deficit spending.

The fiscal situation is problematic, and we must urge our politicians to manage spending more effectively. But often forgotten in the debate, the rate environment has made it dramatically more urgent than it would otherwise be.

What To Watch Today

Earnings

Economy

Market Trading Update

This is where the quiet-index story gets interesting for traders. The S&P 500 closed the week at 7,457.69, and that put it right on top of its 50-day moving average near 7,464. Call it dead flat against the line. The index still sits about 6.8% above its rising 200-day average near 6,985, so the primary uptrend remains fully intact, and it is roughly 2% below the June 2 record high of 7,620.

Momentum on the index itself is neutral, not broken. The 14-day RSI reads 48.8, smack in the middle of its range and nowhere near oversold. The MACD is the wrinkle. It just rolled below its signal line for the first time since the April low, and the histogram flipped negative. That is a fresh bearish crossover. One crossover is not a sell signal, but it is exactly the kind of longer-term warning we watch for as a correction builds.

The contrast between the index and the factor is the whole point. The Momentum ETF, MTUM, fell about 6% on the week and printed a 14-day RSI of 41, far weaker than the broad market. The average stock barely flinched. The equal-weight S&P lost less than half a percent and actually tagged a fresh record high midweek, and the Russell 2000 held up better than the Nasdaq. When the cap-weighted index falls, but the median stock does not, the damage is narrow by definition.

So how do you trade it? The 50-day is the line in the sand. Therefore, a decisive hold keeps the burden of proof on the bears, and the first real test on a break sits at the mid-July range low near 7,300. I would not chase the semiconductor and high-beta names lower into a knife that is still falling, and I would not short a market whose average stock is making new highs. This is a spot to rebalance risk, not to place a directional bet. Hold 7,464, and the rotation stays healthy. Lose it on volume, and the correction earns a wider berth.

The Week Ahead

Earnings announcements kick into high gear this week with Alphabet and Tesla both reporting Wednesday evening alongside Philip Morris, Texas Instruments, and IBM's formal Q2 call, a week after its preliminary capex-reprioritization warning rattled the stock. Thursday adds Intel and RTX, while American Express closes the week on Friday.

Economic data is comparatively light. Thursday's initial jobless claims will be watched closely for any confirmation of the labor softening we saw in June payrolls. Friday brings new home sales, a read on how the recent spurt higher in mortgage rates is negatively impacting the housing market.

With the next FOMC decision landing on July 29, the Fed enters its traditional pre-meeting quiet period this week, meaning no speeches to move markets.

Home Affordability: Better Than The Headlines Suggest

Here are the “facts” that the media tells you about home affordability.

Let’s start with a recent survey. Two out of three Americans now say it’s a bad time to buy a house, the most negative reading Gallup has ever recorded.¹ Another study showed that a record 25.2 million adults under 35 are living with their parents.² Scroll any feed, and you’ll hear that home affordability has priced an entire generation out for good. Those are the “facts” according to the media.

However, here’s the problem with that story. When you measure home affordability today against the metric that actually governs the check you write each month, the picture flips. By that measure, buying a home may be easier now than it was for the Boomers and Gen Xers who get blamed for everything.

Let me be clear about what’s real, because I won’t build an argument on a false floor. Since 2019, the median listing price has jumped about 34% to roughly $430,000.³ The payment on a median home went from near $1,700 in early 2020 to about $3,100 by late 2025.⁴ Rates tripled off the 2021 lows. That shock was real, and it landed in five short years.

So the frustration makes sense. What doesn’t hold up is taking a recent, regional price spike and turning it into a permanent law of physics that applies to every zip code and every buyer. The honest version of home affordability today is narrower, more local, and far more fixable than the headline suggests.

But let’s start with the narrative that the Boomer generation had it easy. As one individual posted on X:

“You boomers had it easy, you could buy a home for the price of bread and a gallon of milk.”

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Decades of data across global markets reach the same verdict: the more frequently retail traders trade, the worse they perform. The infrastructure has never been more inviting. The losses have never been more documented. Here are some key statistics we will dive into further.

Retail traders have never had it so easy. Zero commission platforms, options on your phone, social media feeds full of "10 bagger" tips, and a Reddit thread for every stock in the S&P 500. The infrastructure for frequent trading has never been more frictionless, more democratized, or more psychologically seductive.

And the evidence is overwhelming that it is destroying investor wealth at scale.

The data is not subtle. It is not marginal underperformance that can be dismissed as noise. Across decades of academic research, multiple global markets, and every asset class retail traders favor, from stocks to complex options, the conclusion is remarkably consistent: the more frequently retail traders trade, the worse they perform. Not slightly worse. Dramatically, often catastrophically, worse.

The Behavioral Gap Is Growing

Every year, DALBAR publishes its Quantitative Analysis of Investor Behavior, the most comprehensive long-term study of how retail investors actually perform versus the benchmarks they chase. The 2025 report covering 2024 returns delivered yet another indictment.

The average equity investor earned 16.54% in 2024. The S&P 500 returned 25.02%. That 848-basis-point shortfall was the second-largest investor performance gap of the past decade. In one of the strongest bull markets in recent memory, retail traders left nearly a third of available returns on the table. And 2024 was not an anomaly. Retail traders have now underperformed the S&P 500 for 15 consecutive years.

DALBAR's "Guess Right Ratio," meaning how frequently investors correctly time their entries and exits, fell to just 25% in 2024, tying a record low. Retail traders got market direction right just once out of every four times. And yet, the urge to act, reposition, and trade around every headline only intensified.

The compounding consequences are brutal. A hypothetical buy and hold investor who started 2024 with $100,000 in the S&P 500 finished the year with $125,020. The "average" investor, mimicking the behavioral cash flows DALBAR tracks, ended with $112,774, over $12,000 less in a single calendar year, simply from repositioning at the wrong times. Extended over twenty years, that same $100,000 left untouched in the S&P would have grown to $717,503. The average behavioral investor ended up with $345,614, forfeiting more than half their potential wealth, not to the market, but to their own decisions.

The Hazardous Truth About Stock Trading Frequency

The academic literature on trading frequency and performance is unambiguous, and it dates back decades. The landmark 2000 study by Professors Brad Barber and Terrance Odean, "Trading is Hazardous to Your Wealth" (Journal of Finance), analyzed 66,465 household brokerage accounts from 1991 to 1996. Its central finding was stark: retail traders who traded most aggressively earned an annual return of just 11.4%, while the market returned 17.9%. That is a 6.5 percentage point annual performance drag attributable entirely to excessive trading.

Even the average household in the study, turning over 75% of its portfolio every year, still earned 1.5 percentage points less than a simple buy-and-hold strategy. The gross returns were nearly identical across groups. All the destruction happened after transaction costs and the accumulated impact of poorly timed decisions. Overconfidence was the root cause Barber and Odean identified. Retail traders consistently overestimated their informational edge, leading them to trade when sitting still would have served them far better.

Subsequent research confirmed the finding globally. A study of the Colombian Stock Exchange covering 5.38 million trades by over 42,000 individual investors from 2006 to 2016 found that retail investors generated negative abnormal returns of 4% to 4.4% per year, before transaction costs. The most active traders performed the worst, even on a gross basis. The problem is not just the cost of trading. It is the trading itself.

Day Trading: Where Retail Traders Go to Lose Everything

If frequent stock trading is hazardous, day trading is in a category of its own. FINRA data from 2020 showed that 72% of day traders ended the year with financial losses. Among proprietary traders, those treating it as a professional business, only 16% were profitable. A mere 3% earned more than $50,000 for the year.

The survival statistics are equally grim. 80% of day traders quit within the first two years. Nearly 40% abandon it within one month. After three years, only 13% remain active. Only 1% of day traders maintain consistent profitability over a five-year horizon.

The most comprehensive single market study, a 2020 examination of Brazilian equity index futures traders who persisted for more than 300 trading days, found that 97% lost money. Only 1.1% earned more than Brazil's minimum wage, and all of them experienced substantial volatility. No survivorship bias. Every trader who tried was measured over an extended period.

Retail traders, undeterred by the data, have gotten more aggressive since COVID. Post-pandemic research found that poor market timing, which cost investors roughly 0.53% per year before 2020, nearly doubled to 1.01% per year since. The explosion in retail participation, fueled by social media and zero-commission apps, has not produced better outcomes. It has produced worse ones.

Options: A Wealth Destruction Engine

If day trading is a casino, retail options trading is the casino where the house advantage is structural, invisible, and relentless. The research here is particularly damning.

A landmark study by de Silva, Smith, and So ("Losing is Optional," MIT Sloan and Stanford, 2022) found that retail traders lost approximately $3 billion in options trades over the period from January 2010 through February 2021. Market makers were the primary beneficiaries.

Bryzgalova, Pavlova, and Sikorskaya (Journal of Finance, 2023) calculated that the aggregate retail options portfolio lost $2.1 billion from November 2019 through June 2021 alone, with the bulk of those losses coming not from bad directional calls, but from the cost of trading itself. Retail traders in options incur average gross monthly losses of 1.81%, described by researchers as "economically large and statistically significant."

The mechanics of the losses fall into three repeating behavioral traps. First, retail traders systematically overpay for options relative to the realized volatility the underlying actually delivers, especially around earnings announcements. Second, they incur bid-ask spreads averaging roughly 8% of the option's value on a round trip, an immediate structural headwind equivalent to a 9 to 10% drag on invested capital before any directional bet pays off. Third, they hold losing positions well past the point where price decay accelerates after a catalyst passes, sitting on deteriorating contracts as volatility collapses around them.

Since the introduction of zero-commission complex options trading, retail volumes surged by more than 75%. More access did not produce better results. It produced more frequent losing trades.

The Common Thread: Overconfidence

Across every study, every market, and every asset class, the behavioral driver is the same: overconfidence. Retail traders overestimate their ability to predict short-term price movements. Unsurprisingly, they trade more after a strong recent performance, buy into momentum precisely when the easy money has already been made, and sell winners 50% faster than they sell losers. In other words, they confuse activity with skill.

Short-term trading is largely a zero-sum game. For every retail trader who profits, a more sophisticated, better capitalized, algorithmically equipped counterparty sits on the other side. The house advantage embedded in options markets alone, via bid-ask spreads and market maker flow, is the financial equivalent of playing blackjack at a table where the dealer wins on ties.

The antidote is not complicated, even if it is psychologically difficult. Discipline, lower turnover, longer time horizons, and a ruthless focus on what can actually be controlled, including cost, diversification, and behavior, remain the only reliable defenses against the retail trading trap.

Five Tactics to Navigate Risk Without Overreacting

None of the evidence above argues for passivity in the face of market risk. Risk is real, volatility is real, and periods of genuine portfolio danger require thoughtful responses. The problem is not that retail traders care about risk. The problem is that their responses to it, frequent repositioning, speculative options bets, and tactical timing, reliably make outcomes worse rather than better. The following five tactics are designed to keep investors engaged and protected without triggering the behavioral traps revealed by the data.

1. Write a Personal Investment Policy Statement. A written Investment Policy Statement (IPS) is the single most underused tool in retail investing. Furthermore, it forces the investor to commit, before any market stress arrives, to their asset allocation targets, acceptable drawdown thresholds, rebalancing triggers, and the conditions under which they will and will not make changes. When markets fall 15%, and every instinct screams to act, a pre-committed IPS replaces emotion with a predetermined framework. Writing an IPS does not eliminate risk. It eliminates the most dangerous variable in the portfolio, which is the investor's own unguided reaction to it.
2. Rebalance on a Schedule, Not a Sentiment. Rules-based rebalancing, triggered by calendar dates or percentage drift thresholds rather than market headlines, captures one of the few mechanical edges available to individual investors: it systematically forces buying of what is cheap and trimming of what is expensive. Research from Vanguard and Morningstar consistently shows that disciplined annual or threshold-based rebalancing adds 10 to 50 basis points of return per year over time while materially reducing drawdown severity.
3. Replace Speculative Options with Defined-Risk Structures. For investors who use options, the research is clear about where losses concentrate: in naked or leveraged directional bets, especially around earnings announcements, when bid-ask spreads widen and volatility collapses after the event destroys premium value. Instead, use defined-risk structures, including covered calls on existing long equity positions, protective puts sized to hedge a specific portfolio drawdown threshold, and vertical spreads that cap both gain and loss, to generate a fundamentally different statistical profile.
4. Require a Three-Day Waiting Period Before Any Non-Scheduled Trade. Before executing any trade that is not part of a pre-scheduled rebalance, the investor imposes a mandatory 72-hour waiting period and writes down, in plain language, why they are making the trade, what the exit criteria are, and what price action would tell them they are wrong. Most trades that feel urgent on Monday look considerably less urgent on Thursday. The behavioral literature consistently finds that the speed of a trading decision is inversely correlated with its quality. Slowing the process forces the investor to engage their deliberate reasoning rather than their reactive instincts.
5. Calculate Your Own Behavioral Return Gap Every Year. The exercise is straightforward: take the time-weighted return of each position as if it had been held without any transactions, then compare it to the account's actual dollar-weighted return, including every buy, sell, and repositioning decision made during the year. The difference is the personal behavioral gap, the exact cost in dollars of every trade made. For most active retail traders, this number is negative and larger than they expect. For some, it represents tens of thousands of dollars in self-imposed performance drag per year. Seeing that number concretely, attached to actual dollars rather than abstract percentages, is the most powerful behavioral intervention available.

The market will always be there tomorrow. The question is whether your capital will be, and whether the decisions you make today will compound in your favor or against you.

REFERENCES

• Barber, B.M. & Odean, T. (2000). Trading is Hazardous to Your Wealth. Journal of Finance, 55(2), 773–806.
• DALBAR (2025). Quantitative Analysis of Investor Behavior (QAIB). www.qaib.com.
• De Silva, T., Smith, B. & So, E. (2022). Losing is Optional: Retail Investors in the Options Market. MIT Sloan / Stanford GSB.
• Bryzgalova, S., Pavlova, A. & Sikorskaya, T. (2023). Retail Trading in Options and the Rise of the Big Three Wholesalers. Journal of Finance.
• Naranjo, A., Nimalendran, M. & Wu, S. (2024). Complex Options Study. University of Florida.
• Chague, F., De-Losso, R. & Giovannetti, B. (2020). Day Trading for a Living? SSRN Working Paper.
• FINRA (2020). Day Trading: Your Dollars at Risk. Finra.org.
• Morningstar (2023). Mind the Gap: A Report on Investor Returns in the U.S., Morningstar.com.
• Bessembinder, H. (2018). Do Stocks Outperform Treasury Bills? Journal of Financial Economics, 129(3), 440–461.

The post Why Retail Traders Consistently Underperform Over Time appeared first on RIA.

🔎 At a Glance

• Momentum Meltdown Catches Traders By Surprise
• Market Brief & Technical Review
• From Lance's Desk: Home Affordability: Better Than Headlines Suggest - RIA
• Market stats, screens, and risk indicators

🏛️ Market Brief - Momentum Breaks, Oil Spikes

The headline number this week was boring, but the action underneath was not, as the momentum meltdown was tearing through the market's most crowded trade. The S&P 500 slipped about 1.5% to close at 7,457.69, the Nasdaq 100 gave back roughly 4%, and the Dow held up with a fractional loss. Look only at the index, and you would think nothing much happened. That would be a mistake.

Underneath the calm surface, one of the most crowded trades on the planet came apart. Goldman Sachs' high-beta momentum basket fell about 24% month-to-date through the first half of July, its worst stretch since April 2009. Morgan Stanley's tech momentum index posted a 17-day rate of change of -35%, the worst reading in the 27 years that desk has tracked it. Back in early June, I asked in "Parabolic Semiconductor Rally: What Breaks The Trade," what would finally crack the parabolic semiconductor and momentum complex. This week, we got the answer.

The catalysts arrived together. China's Moonshot AI unveiled Kimi K3, a 2.8-trillion-parameter open-weight model that benchmarked close to leading US systems at a fraction of the cost, reigniting fears about the durability of the American AI premium. Chipmakers took the brunt. The Philadelphia Semiconductor Index dropped more than 10% this week and now sits near a 20% drawdown from its June high, the level that defines a bear market. Marvell fell 20%, Arm dropped 17%, and Micron lost 13%.

Then oil lit up. Renewed US and Iran strikes pushed WTI crude up roughly 14% on the week and Brent up more than 15%, handing Energy a 4.7% gain and the top spot on the sector board. Real estate, staples, and financials also finished green as yields fell on soft inflation readings. Overall, the damage was concentrated in one place. Technology lost 5.5% and stood alone at the bottom, while the average stock barely moved.

Cross-asset markets told the same rotation story. Gold slipped about 2%, silver dropped nearly 6%, and the dollar finished roughly flat. The ten-year Treasury yield held near 4.55% while the front end eased a touch. One bright spot for the consumer landed Friday, when the University of Michigan's preliminary July sentiment reading jumped to 54.4 from 49.5 as gasoline prices cooled earlier in the month.

The thread to follow into next week is simple. Money is not leaving the market. It is rotating hard, and the tape will not settle until the crowd finishes repositioning.

📈Technical Backdrop - Coiling Below The Record

Here is where the quiet-index story gets interesting for traders. The S&P 500 closed the week at 7,457.69, and that put it right on top of its 50-day moving average near 7,464. Call it dead flat against the line. The index still sits about 6.8% above its rising 200-day average near 6,985, so the primary uptrend remains fully intact, and it is roughly 2% below the June 2 record high of 7,620.

Momentum on the index itself is neutral, not broken. The 14-day RSI reads 48.8, smack in the middle of its range and nowhere near oversold. The MACD is the wrinkle. It just rolled below its signal line for the first time since the April low, and the histogram flipped negative. That is a fresh bearish crossover. One crossover is not a sell signal, but it is exactly the kind of longer-term warning we watch for as a correction builds.

The contrast between the index and the factor is the whole point. The Momentum ETF, MTUM, fell about 6% on the week and printed a 14-day RSI of 41, far weaker than the broad market. The average stock barely flinched. The equal-weight S&P lost less than half a percent and actually tagged a fresh record high midweek, and the Russell 2000 held up better than the Nasdaq. When the cap-weighted index falls, but the median stock does not, the damage is narrow by definition.

So how do you trade it? The 50-day is the line in the sand. Therefore, a decisive hold keeps the burden of proof on the bears, and the first real test on a break sits at the mid-July range low near 7,300. I would not chase the semiconductor and high-beta names lower into a knife that is still falling, and I would not short a market whose average stock is making new highs. This is a spot to rebalance risk, not to place a directional bet. Hold 7,464, and the rotation stays healthy. Lose it on volume, and the correction earns a wider berth.

🔑 Key Catalysts Next Week

Next week, the Federal Reserve goes silent. The July 28–29 FOMC meeting puts the committee in its blackout window, so there are no Fed speakers to move the tape. That leaves two things in charge: the economic data and the start of mega-cap earnings, with the second being the main event.

Wednesday after the close is the night that matters. Alphabet, Tesla, and Texas Instruments all report at once, and Intel follows on Thursday evening. This is the first real referendum on the AI-capex story since the momentum trade cracked. Alphabet is the tell. The company has guided to roughly $175 billion of capital spending in 2026, and JPMorgan's desk pegs 2027 buyside expectations for Google alone near $325 to $350 billion, well above a Street consensus closer to $250 billion. If the hyperscalers signal any hesitation on that spend, the chips that depend on it have further to fall. If they reaffirm it, the washed-out names finally get their catalyst.

The setup is loaded. Alphabet's blowout first-quarter results were flattered by tens of billions in mark-to-market gains on its Anthropic and SpaceX stakes; stripping those out, the operating number would have missed by a hair. That is exactly the earnings-quality question we have been raising for months. The market will judge this print on margins and cloud growth, not on the headline number.

Ed Yardeni has framed the broader mood as a case of AI Fatigue, with investors starting to ask whether the trillion-dollar buildout will ever pay off. The Friday flash PMIs are the data highlight, since they are the first look at how business activity handled the July volatility and the oil spike. Everything else bends around Wednesday night. A clean capex message from Alphabet steadies the entire complex. Any wobble, and the momentum meltdown gets a second leg.

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💰 Momentum Meltdown Sends A Warning

Every so often, the market hands you a week where the index and the internals tell opposite stories. This was one of them. The S&P 500 fell about 1.5%, a garden-variety pullback, while the momentum factor suffered its worst drawdown since the depths of the 2009 financial crisis. That gap is the entire story, and understanding it is the difference between panic-selling the wrong thing and using the rotation to your advantage. As I flagged two weeks ago in Mag 7 Stocks: Risk Or Opportunity In The Making?, this rotation was coming.

The scale of this move is genuinely historic, and the qualifier matters. As noted above, the Goldman Sachs high-beta momentum basket fell roughly 24% in the first two weeks of July, the worst such stretch since April 2009. Furthermore, the Morgan Stanley tech momentum index registered a 17-day rate of change of -35%, the worst in its 27-year history. Goldman's flagship momentum pair is now down about 33% from its highs and has broken below its own 200-day average, a drawdown that matches the late-2022 low. Those are numbers worth repeating for emphasis.

Here is the part that keeps this from being a catastrophe. That same high-beta momentum basket is STILL up about 16% for the year after peaking near +60%. This is a violent give-back of an enormous gain, not a wealth-destroying collapse. The single-stock casualties show where the crowd was hiding: in semiconductors.

It Is A Rotation, Not A Collapse

If money were fleeing the market, you would see it everywhere, but that is not the case. The equal-weight S&P 500 fell less than half a percent on the week and printed a new all-time high midweek, while defensive and cyclical value groups finished green. Energy led following the oil spike, and real estate, staples, and financials all gained. That is not what a market top looks like. That is capital rotating out of the most crowded corner and into everything else.

The leadership under the surface has quietly flipped. Look at what is working against what is breaking, and the rotation is obvious. Security-software names like Palo Alto and CrowdStrike, which benefit from AI adoption without the semiconductor bottleneck risk, are catching the bid alongside energy and the banks. The mega-cap AI generals held up far better than the speculative fringe, with Nvidia down under 4% and both Microsoft and Amazon actually positive on the week. The pain was surgical, not broad.

What Actually Broke The Trade

Four forces hit at once, which is why the move was so violent; the setup was a positioning problem. Momentum had been the undisputed king of 2026, and nearly everyone owned it, leaving no marginal buyer when selling started. The trigger came from leverage. In Asia, single-stock leveraged ETFs on names like SK Hynix had ballooned, and when the underlying prices dipped, those funds were forced to sell to maintain their 2x exposure, which fed a self-reinforcing unwind. Korea moved to halt new listings of these products midweek.

On top of that, China's Kimi K3 release cracked the assumption that US AI leadership was unassailable, and the oil spike from renewed Iran tensions revived a macro risk the momentum crowd had stopped pricing. The June index-rebalancing that had provided a price-insensitive buyer for winners like SpaceX and Marvell was gone. Take away the buyer, add forced sellers, and you get a washout.

The lesson of every crowded-trade unwind is the same. The factor that leads on the way up leads on the way down, and the exit door is always narrower than the entrance.

Goldman's own desk offers a hopeful footnote. Once the momentum factor drops more than 20% in a month, forward returns have tended to be positive, with a median gain near 4% over the following week and close to 6% over the following month. The path is rarely smooth, and next week's reports are the swing factor. Notably, a violent factor unwind is often closer to an opportunity than to the start of a bear market. Yes, that is an optimistic case, but it is a real one to consider given the rash of negative headlines this past week.

The Earnings-Quality Problem Underneath The Rally

There is a deeper issue that the momentum crowd has been willing to ignore, and it goes to the quality of the earnings that are holding up the AI trade. Take Alphabet's blockbuster first quarter. The headline was a record, but tens of billions of it came from mark-to-market gains on private stakes in Anthropic and SpaceX, not from the operating business. Stripping the paper gain would have caused the estimate to be missed. That is not a one-off quirk. Across the hyperscalers, a wave of AI capital spending is being depreciated over long schedules that assume these chips and data centers will earn their keep for years, thereby inflating near-term margins and quietly deferring the true cost.

We walked through that dynamic in Capex Spending On AI Is Masking Economic Weakness, and it is the reason next week's reports carry so much weight. The moment the market decides to pay for cash flow and earnings quality rather than capex headlines, the most crowded and most expensive names carry the most risk. Momentum had been priced for perfection. Perfection is an expensive thing to own the moment the story starts to wobble.

Why There Could Be More To Go

It helps to separate two ideas. The momentum meltdown is the event, and the violent two-week repricing we just lived through. The momentum shift is the bigger thing, a change in market leadership away from the narrow band of high-beta and semiconductor names that carried 2026 and toward the broad market underneath. The first can end in a week. The second is a process, and history says leadership changes take months to resolve, not days. That distinction applies to patience here, and it is why I think more air can still come out before this is finished.

The math tells you why the shift may not be over. As discussed above, following the worst two weeks since 2009, the high-beta momentum basket is still up about 16% on the year. That is the give-back of a parabola, not a full reset. Positioning has been reduced, but it has not capitulated, and not a single US semiconductor is even oversold yet on a 14-day RSI basis. Washouts of this scale rarely resolve in one clean flush. They tend to arrive in waves, with sharp relief rallies that pull money back in right before the next leg lower.

The healthy read is that the average stock is doing fine while the crowd unwinds. The cautious read is that the unwind still has fuel in the tank. This is because the crowd is sitting on a full year of gains it may yet decide to protect. Both can be true at once. That tension is exactly why the tape has felt so violent under a calm surface.

The Macro Has Turned Against The Trade

Here is where this week's other headline matters. In Inflation Will Be A Thing Of The Past, we covered Kevin Warsh's first testimony to Congress. The message was not what a momentum trader wants to hear. Warsh told lawmakers the Fed has "no tolerance for persistently elevated inflation." He also pointedly refused to offer forward guidance, arguing that published projections only breed confirmation bias. June CPI actually showed prices falling 0.4% on the month, and yet the committee is still split on the odds of a rate hike in September, not a cut.

Now read that against this week's tape. Oil just jumped roughly 14% on renewed Iran tensions, which threatens to undo the very disinflation that gave Warsh room to sound patient. A hawkish Fed with no rate cut on the horizon and no forward guidance to lean on is the opposite of the backdrop that inflated the momentum trade in the first place. The most expensive, longest-duration growth names need falling rates and easy liquidity to justify their multiples. Right now, they are getting neither, and policy uncertainty alone widens the risk premium the market demands to hold them.

None of this is a forecast of a bear market. It is a reminder that a leadership shift, once it begins, usually runs longer and further than the first move suggests. Here are both sides of the ledger, laid out honestly.

Weigh the calendar, too. We noted previously that the risk of a larger market correction (5-10%) is highest in August through October. That is particularly true given the upcoming mid-term elections. Those three months are historically the weakest stretch of the year anyway. However, the election uncertainty adds to that risk, and this unwind is landing right as we walk into it. That does not mean you sell everything and hide. It means you respect the shift. Therefore, keep tight risk controls on the crowded names, and let the earnings and the tape confirm the next move.

What Should Investors Do Now

This is a moment for discipline, not heroics. The rotation is healthy but not finished. Next week's reports will determine whether the momentum names have found a floor. As we laid out last week in The Dollar Narrative Has Turned, the play into late July is to lean toward the washed-out mega-cap leaders rather than the extended names, and to define the exit at the earnings dates themselves. If Alphabet and the others confirm the capex and cash-flow worries when they report, you sell and move on. If estimates hold, the oversold snapback has room to run.

Keep capital preservation first. An index sitting on its 50-day with a neutral RSI is neither a screaming buy nor a screaming sell. It is a market telling you to rebalance, tighten your stops on the crowded names, and let the earnings do the talking. The momentum meltdown was a warning shot about what happens when everyone owns the same thing at the same time. The momentum shift it kicked off is the story that matters now, and it likely has further to run.

Trade accordingly.

🖊️ From Lance’s Desk

This week's #MacroView blog examines the doom feed claiming home affordability has locked a generation out. The math on the payment you actually write says something the headlines won’t.

Also Posted This Week:

• Headwinds And Tailwinds: Minding The Market Weather - RIA - by Michael Lebowitz
• Spotting Market Bubbles: Why History Says It’s Nearly Impossible - by Lance Roberts

📹 Watch & Listen

The bigger story is happening beneath the surface. Leadership rotated sharply as investors sold semiconductor stocks despite ASML's earnings. With the semiconductor sector breaking below key technical support, investors should watch closely to see whether this is simply a healthy consolidation or the beginning of a larger topping pattern.

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📊 Market Statistics & Analysis

Weekly technical overview across key sectors, risk indicators, and market internals

💸 Market & Sector X-Ray: Market Gains Ground

Semiconductor stocks continued to be under pressure this past week as money rotated to other areas of the market with Energy, Financials, Real Estate and Staples caught the flows with International, Technology, Industrials and Discretionary more oversold.

📐 Technical Composite: 77.09 - Still Bullish But Easing

The technical condition eased last week as semiconductors and momentum names came under pressure. While not at more extreme levels, the market is overbought enough to continue limiting upside modestly over the next few weeks.

🤑 Fear/Greed Index: 79.65 – Greed Remains Elevated

Despite a bit of volatility last week, and pressure in the high beta and momentum names, overall allocations and sentiment remain elevated particularly as professional investor sentiment pushed sharply higher.

🔁 Relative Factor Performance

Last week we noted that the "compression of factors has been evident...that clustering will shake itself out sooner than later, and the opportunity will be in which factors start to take the lead." That occurred last week as the factors stretched back out with Low Volatility, Value, and Quality gaining flows while Emerging Markets (via Semiconductor exposure) and High Beta sold off.

📊 MFBR Index (Money Flow/Breadth Ratio Indicator): 60% = Buy Zone

NEW! MFBR Index: The Money Flow Breadth Ratio (MFBR) model is a rules-based equity allocation framework that uses weekly S&P 500 money flow data to generate buy, sell, and neutral signals. The MFBR systematically adjusts portfolio equity exposure in response to the direction and persistence of institutional capital flows. It aims to reduce drawdowns while capturing the majority of market upside.

"As of July 17, 2026, with the S&P 500 at 7,457.69, the Money Flow Breadth Ratio (MFBR) stands at 65% and rising. This places the indicator in BUY territory (60-70%), triggering a BUY signal. The prior week reading was 65%, representing a 5% decline over the trailing four weeks.

The model currently recommends increasing equity exposure aggressively, with a target equity weight of 92%. This reflects a FLOW-OVERLAY OVERRIDE: the trailing 4-week net dollar flow has swung sharply positive (>$300B) after a deeply negative prior 4 weeks, a historically strong contrarian buy signal."

📊 Sector Model & Risk Ranges

The market consolidation over the last month has slowly started reducing the more extreme deviations in some sectors and markets. Over the past week, Energy, Financials and Staples traded above their historical monthly ranges while Technology corrected along with Emerging Markets and Gold Miners. The market is going through a correction via rotation.

Have a great week.

Lance Roberts, CIO, RIA Advisors

The post Momentum Meltdown Catches Traders By Surprise appeared first on RIA.

Kevin Warsh delivered his first semiannual testimony to Congress earlier this week. In it, he used every opportunity to stress the urgency of returning inflation to the Fed’s 2% target. To wit, he stated, “Inflation will be a thing of the past.” He also said the Fed “has no tolerance for persistently elevated inflation.”

The June CPI inflation report, showing a 0.4% decline in prices, was released 90 minutes before his House testimony on Tuesday. It gave Warsh room to sound determined without the need to promise immediate action via a rate hike. He made it clear that while the inflation data was great news, “It’s one data point.... I don’t want to overread or cherry-pick data.”

Kevin Warsh's aversion to forward guidance was another key theme. His argument, in essence: "We're human." Importantly, Warsh seems to understand that behavioral flaws can negatively impact policy. Publish a projection,” he said, and the committee inevitably starts "taking information that's consistent with our priors and rejecting information that's inconsistent." When a person or group anchors to a forecast, they tend to favor it and may be less likely to consider opposing data. In Warsh's view, when members are not saddled with the perception of prior forecasts, they can be "more circumspect," which is a better way to set policy.  

Warsh did receive a few questions about the Fed’s independence. To wit, Rep. Nydia Velázquez asked whether Warsh "works for" the administration. Warsh replied, "We're an independent central bank." When pressed further, he committed only to "follow the law and follow the data."

The graphic below shows the Fed is currently split on the odds of a September rate hike.

What To Watch Today

Earnings

Economy

Fed Speakers

None scheduled. The pre-FOMC blackout begins Saturday, July 18, ahead of the July 28–29 meeting, so Friday is the last open day on the calendar. Chair Kevin Warsh’s semiannual monetary policy testimony wrapped on Wednesday before the Senate Banking Committee.

Market Trading Update

In yesterday’s report, we walked through semiconductors stretched to a historic extreme and made the case for trimming the parabola before it trims you, as we covered here. Today, I want to discuss what happens when that trade finally cracks, because the underlying tape is telling a very different story from the headline index.

On the surface, the markets look dull, well, actually just boring. The S&P 500 remains barely lower than its record high, but that calm is a cap-weighting illusion. The Nasdaq 100 slipped below its 50-day moving average for the first time in months, while the VanEck Semiconductor ETF (SMH) dropped roughly 3% as the chip bid unwound. The generals took the damage.

Now look at what the troops did. The equal-weight S&P 500 (RSP) rose, and its RSI is a healthy 60. Small caps (IWM) also lifted, with the Dow also gaining ground. On a day when Semiconductors and Technology retreated, the average stock advanced. As the chart below shows, RSP now sits 2.8% above its 50-day line, while the cap-weighted Nasdaq has fallen below its own 50-day line.

With the market broadening, there remains a bullish backdrop for investors for now. While the rally from the March lows has been impressive, it has relied primarily on a handful of stocks. With the relative strength of the equal-weight versus cap-weight index bottoming six weeks ago and climbing since, it is clear that money isn’t leaving the market. It’s changing seats.

Here’s the catch. Yes, the market's broadening is healthy, but the trigger matters. This rotation is being FORCED by tech rolling over, not pulled by fresh optimism about growth. Small caps still have to prove they can lead with a hawkish Warsh Fed and yields backing up on higher oil. IWM remains shy of its high with an RSI of just 54. A rotation that is really only tech deleveraging can reverse in a single session.

So, what does this mean to you? That is THE question, and there are no guarantees. Therefore, you manage the risk and let the markets dictate your next course of action. We are not chasing small caps up here, and we would rather add on a pullback toward the S&P’s 50-day near 7,456 than pay up into resistance at the old high. Keep quality high, keep a little dry powder, and most notably, continue to manage risk at the line. Broad is good. Forced-broad still has to prove itself.

One Company- Two Prices: Examining SK Hynix's Reverse Kimchi Premium

South Korea has long had what is called a "Kimchi discount." This is the tendency for Korean companies to trade at lower valuations than their global peers due to weak governance and limited shareholder returns. South Korean memory chip maker SK Hynix just demonstrated the discount in its new US ADR listing.

SK Hynix's Nasdaq-traded ADR (SKHY) began trading on Tuesday, closing at $193.92, up over 25%. Each ADR represents one-tenth of an ordinary Korean share. That same day, the Seoul-listed shares closed at $1,280. The ADR should have been $128. US investors are paying an approximately 50% premium for identical ownership, underlying business, dividends, and earnings. The only difference is which exchange processes the trade.

Why doesn't arbitrage close the gap immediately? Part of the gap reflects the structure of the listing itself. SK Hynix's ADRs can be converted freely into Seoul-listed shares, but conversions in the other direction require regulatory approval. This one-way conversion model mirrors TSMC's approach. Its US-listed shares have maintained persistent premiums of 13% to 20% for years as the arbitrage mechanism is hobbled by the same conversion limitations.

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The post Inflation Will Be A Thing Of The Past- Kevin Warsh appeared first on RIA.

The doom feed says home affordability locked a generation out. The math on the payment you actually write says something the headlines won't.

Here are the "facts" that the media tells you about home affordability.

Let's start with a recent survey. Two out of three Americans now say it's a bad time to buy a house, the most negative reading Gallup has ever recorded.¹ Another study showed that a record 25.2 million adults under 35 are living with their parents.² Scroll any feed, and you'll hear that home affordability has priced an entire generation out for good. Those are the "facts" according to the media.

However, here's the problem with that story. When you measure home affordability today against the metric that actually governs the check you write each month, the picture flips. By that measure, buying a home may be easier now than it was for the Boomers and Gen Xers who get blamed for everything.

Let me be clear about what's real, because I won't build an argument on a false floor. Since 2019, the median listing price has jumped about 34% to roughly $430,000.³ The payment on a median home went from near $1,700 in early 2020 to about $3,100 by late 2025.⁴ Rates tripled off the 2021 lows. That shock was real, and it landed in five short years.

So the frustration makes sense. What doesn't hold up is taking a recent, regional price spike and turning it into a permanent law of physics that applies to every zip code and every buyer. The honest version of home affordability today is narrower, more local, and far more fixable than the headline suggests.

But let's start with the narrative that the Boomer generation had it easy. As one individual posted on X:

"You boomers had it easy, you could buy a home for the price of bread and a gallon of milk."

Boomers Did Not Have It Easy

Here's the part the narrative skips. The Boomer who bought in 1980 financed at a 30-year fixed rate of 13.74%, watched it climb past 18% by October 1981, and had no way to know rates would ever come back down, which made every payment feel like a life sentence.⁵ Think about that. For a median home price of $64,600 with 20% down, that household sent roughly 39% of its income to the mortgage before property taxes.⁶ Add the taxes, and the typical 1980 family spent close to 47% of their income on housing.

Today's buyer, financing about $417,000 near 6.5%, spends closer to 32% on the mortgage and about 43% all in.6,14 Two independent analyses ran this exact math and landed in the same place. On the payment that matters, 1980 was as hard as, or harder than, 2026. So home affordability today is mostly a payment story, and the payment math favors the present. Notice what the work did. It isn't the price of the home, it's the rate.

The Crisis Is Regional, Not National

Now look at where the "home affordability" pain actually sits. A typical home in Iowa costs about 3.7 years of household income, near where the national buyer stood in 2000.⁷ Ohio, Indiana, Illinois, and Kansas still sell near or below $300,000. Among large metros, Chicago, Houston, Dallas, Atlanta, and Philadelphia rank among the most affordable in the country.⁷ Home affordability today is a function of your zip code first, your generation second.

The expensive markets are real, but they're specific. And here's the twist most coverage misses. The old escape hatch of moving somewhere cheap is closing, because Montana now costs 8.7 years of income, worse than California or New York.⁷ The same regional pattern shows up in who's living at home. In New Jersey it's 44% of young adults. In South Dakota, 18%.⁸ The map of "kids who can't move out" is mostly a map of expensive states.

That "one in three" figure above also deserves a second look. It counts everyone ages 18 to 34, which includes college kids, 22-year-olds in their first job, and people who've always lived at home for a stretch. If you narrow that gap to a more realistic home ownership range, ages 25 to 34, the share drops to about 18%.⁹ And roughly 70% of those 25-to-34-year-olds at home are employed.² So this "home affordability" story isn't about a lazy generation or a broken job market. It's a story about down payments, rent, and a marriage age that has drifted six years later since 1980.

Where The Skeptics Are Right

I won't pretend that nothing has changed. Two things genuinely got harder, and waving them away would insult the reader. First, the down payment. In 1980, 20% down ran about two-thirds of a year's income. Today it runs a full year or more, which is why the median first-time buyer now puts down just 9% to get in the door, and why the first-time buyer's median age has climbed from 29 to roughly 40.¹⁰ That capital wall is a real barrier.

Second, insurance. Premiums jumped 24% from 2021 to 2024 to an average of $3,303, twice the rate of inflation, rising in 95% of zip codes.¹¹ In Utah, insurance premiums rose 59%. That cost isn't your fault, and it won't be fixed by skipping lattes, but notice what both problems have in common. They're specific and addressable, not a sentence handed down to an entire generation. The home affordability debate today has two honest exceptions, and naming them is what separates analysis from a comment-section rant.

Where They Aren't

Here's the irony buried in the down payment story. The 1980 buyer didn't just face a 20% norm; they put down even more, averaging about 28%.¹⁰ To skip mortgage insurance on a conventional loan, you needed the full 20% in cash, no exceptions. There were no mainstream 3% conventional programs, no piggyback structures in wide use, no stack of state assistance grants to pull from. You saved the lump sum, or you stayed a renter.

Today, the menu is wide open. A first-time buyer can go conventional with as little as 3% down, FHA with 3.5% down, or zero down with a VA or USDA loan if eligible, and can cover even that with gift funds, a 401 (k) withdrawal, or a state assistance grant.¹⁵ The 20% rule is dead. The median first-time buyer actually put down 10% last year, not 20^.16 Less down means PMI and a bigger payment, of course. But the belief that you need 20% in cash just to walk in the door is the single most expensive myth keeping renters stuck, and it hasn't been true for decades.

The Playbook: Home Affordability Today Is on You

So what's the move? Stop reading a national headline as a verdict on your situation. The buyer who treats "homeownership is dead" as gospel, while sitting in a market where a solid house costs three or four times income, talks himself out of a purchase he could actually make. Bob Farrell's ninth rule fits here. When every expert and forecast agrees, something else usually happens.¹² Sentiment just hit a record low. That's historically when the patient buyer gets paid.

But mindset only gets you to the starting line. Here's the part nobody wants to hear.

Working isn't enough. Roughly 70% of the young adults living at home already have jobs, so a paycheck alone clearly doesn't get you out of the basement.² What gets you out is a set of decisions most people dodge because they sting. So let's say them plainly.

• Run the number, then automate it. A 3.5% down payment on a $250,000 home is $8,750, about $730 a month for a year. If you can't find $730, that's a spending problem or an income problem, and both are yours. But here's the part the pushback misses. The inability to save that money isn't just a down payment problem. It's a signal you can't afford to own yet. The mortgage is only the floor. Property taxes, insurance that now averages $3,303 a year, the roughly 1% of a home's value it consumes in annual upkeep, and HOA dues, if you have them, all add up to the monthly payment.¹¹ Can't bank $730 a month as a renter? You'll drown in those carrying costs as an owner. The savings test isn't the barrier. It's the readiness check.
• Cut the big rocks, not the pebbles. The daily coffee isn't what's keeping you in your childhood bedroom, but the $650 truck payment, the $1,900 rent in a city you picked for the nightlife, and the lifestyle you finance to look successful on a phone screen absolutely are. Sell the financed truck. Get a roommate. Buy smaller, because the median new home is 38% larger than it was in 1980, making a 1,500-square-foot starter a choice rather than a hardship.¹³ Live below your means on purpose. Nobody is coming to subsidize your standard of living.
• Then move to the money. The good jobs and the cheap houses rarely sit in the same expensive zip code you grew up in. They sit in Columbus, Des Moines, Indianapolis, and Greenville, where a median income still buys a median home.⁷ Remote work made that move easier than it has ever been. If you won't relocate for opportunity, fine, but then you've made unaffordability a choice, not a fate.
• Raise your income and your credit score at the same time. A side income of $1,000 a month is a full down payment in under a year. A credit jump from 580 to 620 can move you off a 3.5% FHA loan and onto a 3% conventional, saving you thousands up front and more over the life of the loan.¹⁵ And every year you stall has a price tag. The National Association of Realtors estimates that delaying a purchase from age 30 to 40 costs the typical buyer around $150,000 in lost equity.¹⁷

The market isn't fair. It was never fair. The only question that matters is what you're going to do about it.

The bottom line is this. Housing isn't unaffordable everywhere, for everyone, forever. It's expensive in specific places, for specific reasons, and most of all since 2020. The rest is geography, a savings problem, and a story people keep repeating until they believe it. After three decades of watching cycles, I've learned the worst financial decisions get made when people accept a narrative instead of running the numbers. Home affordability today is better than the Fed admits. Run your own numbers and see.

Sources

1. Gallup Economy and Personal Finance Poll, April 2026. 67% of U.S. adults say it is a bad time to buy a home.
2. Realtor.com analysis (Hannah Jones), 2025, via The Hill and TNND. A record 25.2 million adults under 35 living with parents; roughly 70% of those 25 to 34 are employed.
3. Realtor.com, 2025 median list price near $430,000, up about 34% since 2019.
4. Fox Business / Realtor.com, Q4 2025. Median home payment is near $3,100.That is up from about $1,700 in early 2020. Income needed climbed from roughly $66,000 to more than $120,000.
5. Freddie Mac via Bankrate and Rocket Mortgage: 1980 30-year fixed averaged 13.74%, peaking above 18% in October 1981.
6. Meredith Wealth and Landmark Wealth Management analyses of Census and FRED data. Mortgage as a share of income roughly 39% (1980) vs 32% (today); about 47% vs 43.5% all-in with property taxes.
7. Best Interest Financial and Visual Capitalist. Using Realtor.com, Census ACS, and NAR data, 2025-26: Iowa 3.7x, U.S. national 5.08x, Montana 8.7x; metro affordability rankings.
8. FinanceBuzz and Visual Capitalist, Census ACS 2024-25: New Jersey 44%, Connecticut 41%, South Dakota 18%.
9. Pew Research Center, 2023: 18% of adults ages 25 to 34 live in a parent's home.
10. Landmark Wealth Management. 1980 average down payment ~28% vs ~9% median for first-time buyers today; first-time buyer median age 29 to about 40.
11. Consumer Federation of America. "Overburdened," April 2025: premiums up 24% (2021-2024) to an average of $3,303. Twice inflation, in 95% of zip codes; Utah +59%, Illinois +50%, Arizona +48%, Pennsylvania +44%.
12. Bob Farrell's 10 Rules, Rule #9: "When all the experts and forecasts agree, something else is going to happen."
13. U.S. Census Bureau / NAHB: median new single-family home 1,595 sq ft (1980) vs 2,205 sq ft (2024), a 38% increase.
14. Freddie Mac Primary Mortgage Market Survey: 30-year fixed averaged about 6.49% for the week ending June 25, 2026.
15. 2026 minimum down payments: conventional 3% (Fannie Mae HomeReady / Freddie Mac Home Possible, 620+ credit), FHA 3.5% (580+ credit; 10% for 500-579), VA, and USDA 0% for eligible buyers. PMI applies to conventional loans with less than 20% down (roughly $30 to $70 per month per $100,000 borrowed) and is canceled at 20% equity; an 80/10/10 piggyback avoids it. Sources: Bankrate, Rocket Mortgage, lender data, 2026.
16. National Association of Realtors, 2025 Profile of Home Buyers and Sellers. Median first-time-buyer down payment of about 10%, the highest in nearly 40 years.
17. The National Association of Realtors estimates. Delaying a home purchase from age 30 to 40 costs a typical buyer roughly $150,000 in lost equity.

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A reader recently asked us: "Why are BDCs diverging from corporate junk bonds?" To his point, the graph below shows the ICE BOA index of BB and B yield spreads to Treasuries are at or near 30-year lows. At the same time, BDCs, which hold lower-rated credit loans to small and mid-sized companies, are trading in many cases at near-historical discounts to their NAVs. The answer is that "junk" is not a single market, and the ICE BOA indexes reflect a divide that partially helps explain the disconnect.

The top graph also shows that CCC junk bond spreads have diverged from their BB- and B-rated peers. The lower graph shows that this divergence is the largest in 30 years. BB spreads, the highest-quality junk, trade at 1.58%, just 22 basis points above their all-time low set in 1997 and in the 1st percentile of history. Single-B spreads, at 2.87%, sit in the 4th percentile. But CCC and lower spreads trade at 9.72%, the 52nd percentile, a full 558 basis points above their record low. Simply, investors have never paid this much for "quality" junk relative to distressed junk.

BDCs, publicly traded securities that hold private credit loans, trade at roughly 10-15% discounts to net asset value. The sector is generally down about 20-25% over the past year. Our reader notes the contradiction between BB- and B-rated bonds and BDCs. S&P's credit estimates place most BDC borrowers at B- or lower, with a tail in CCC territory. Part two, in a lower section, examines the relationship and why it broke.

What To Watch Today

Earnings

Economy

Market Trading Update

Yesterday, we dug into IBM’s guidance miss and how quickly one mega-cap warning can sour the whole tape, as we covered here. Today I want to widen the lens to the group that has actually carried this rally, and the one with the most air underneath it: semiconductors.

Start with the trend. At the time of this writing, the VanEck Semiconductor ETF (SMH) is trading near $604. That’s only about 1.7% above its 50-day moving average of $594. But it sits 38.6% above the rising 200-day near $436, and a remarkable 147% above its 50-month moving average of $244. That 50-month line has tracked the sector cleanly through every cycle since the fund’s inception. Price has rarely, if ever, been this far above it. Put it in trade terms. A garden-variety pullback to the 50-day is less than 2% away. A full reversion to the 200-day would be a 28% decline from here.

Here’s what matters. The move is already cooling. SMH is roughly 10% off its June closing high of $668.91. The 14-day RSI has slipped back into the high 40s from deeply overbought territory, the weekly RSI has eased into the mid-60s after printing above 80 at the peak, and the MACD has rolled below its signal line. Nvidia, the group’s bellwether, is trading near $211 has traded weakly, so leadership is narrowing rather than broadening. Momentum has cooled, not collapsed. The tape simply isn’t confirming new highs anymore.

Parabolic moves run further than anyone expects, and then they don’t correct sideways; they correct hard. What breaks this trade isn’t the fundamentals, at least not yet. ASML made the bull case louder on Wednesday. It beat on the quarter and raised full-year revenue guidance to 43 to 45 billion euros, lifted its gross margin outlook toward 56%, and said it will expand low-NA EUV capacity by roughly 30% in 2027.

SK Hynix ADRs jumped 27% on Tuesday. Demand is clearly intact. That’s exactly the risk. When the news is this good and everyone already owns the trade, the price reflects it, and there’s little room left to surprise on the upside. TSMC reports before the bell this morning with a very high bar to clear, and, behind the scenes, the hyperscaler bond market is flashing signs of funding stress. Crowded positioning and valuation gravity do the rest.

This is NOT a call that the AI buildout is over. It’s risk management at a point where the asymmetry no longer favors holders. Trimming a parabolic winner isn’t a market call. The reward for riding the last leg of a move like this is small, and round-tripping the prior run is permanent damage. Keep semis at target weight, tighten the stops, and manage risk at the line, not after it breaks.

More On BDCs and High-Yield Bonds

In our lede, we showed the record bifurcation between higher- and lower-rated junk bonds. We believe that the divide partially explains why BDCs trade at steep NAV discounts despite tight credit spreads for some junk bonds.

Over the last five years, BDCs (BIZD) and high-yield (HYG) show a correlation of 0.56, with no lead-lag relationship at any horizon. The correlation is somewhat regime-dependent. It's 0.70 on large high-yield moves but just 0.24 on quiet days. Essentially, BDCs and junk are more correlated in volatile markets and less so in calmer ones.

There are four primary drivers to explain today's divergence.

• S&P credit estimates rate most BDC borrowers at B- or lower, so BDCs tend to price off the CCC leg of the market.
• Tight spreads on the BDCs' underlying loans are an earnings headwind for BDCs. It reduces net interest income, which pressures dividends.
• BDC NAV calculations are quarterly, so rising non-accruals and PIK income are prompting some investors to sell and front-run writedowns.
• Retail-driven BDC flows, irrational forecasts, and poor sentiment can dislocate spreads for periods.

Warning: if BB and B spreads finally widen from record tights, statistics say BDCs will recouple at high correlation on the way down. That said, BDCs have already priced in a much weaker credit market than higher-rated junk, so the convergence may not be as damaging as it would be if the divergence hadn't existed.

Headwinds And Tailwinds: Minding The Market Weather

Market forecasting has more in common with hurricane forecasting than most investors appreciate. The goal when managing an investment portfolio is not to predict a single outcome but to understand the environment well enough to establish a range of possible outcomes.

When a hurricane is brewing, meteorologists don’t draw a single storm track forecast on the map; they draw a “cone of uncertainty” that contains dozens of possible paths. Over time, as more information is gathered, the cone tightens.

Some storms cause immense damage, while others prove much weaker than expected. Other once-threatening storms never reach land and peter away in the ocean. Which path materializes depends on many variables layered on top of each other.  Like markets, it’s a dynamic process that is impossible to predict with certainty.

Investors face the same task as meteorologists. We must gauge the many forces acting on markets simultaneously and consider a slew of others that may or may not pressure markets in the future. Doing so efficiently provides us with a range of outcomes rather than relying on a single forecast.

With many headwinds arising, the job for investors right now is to closely track the environment and be ready to trim their sails if needed.

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Coming in on Tuesday morning, investors were expecting to sift through earnings from the largest banks and the CPI data. Instead, IBM stunned investors by pre-releasing its earnings 8 days in advance. Its earnings were much weaker than expected, with revenue well below expectations and EPS declining 2% year over year. As shown below, IBM fell by nearly 25% in pre-market trading.

Its CEO, Arvind Krishna, was blunt in his assessment of the quarter, stating, "This quarter we faltered."

Beyond IBM's earnings-specific details, they had an industry-wide message with potentially far-reaching implications for other companies. Specifically, IBM said clients shifted:

their quarterly capex spend toward servers, storage, and memory purchases to secure supply-constrained infrastructure ahead of expected price increases, adding it did not anticipate the magnitude of the capex reprioritization.

Per IBM, enterprises are now hoarding inventory to front-run the surge in memory prices and some hardware devices. Such behavior is typical shortage psychology, and it is self-reinforcing: panic buying tightens supply further, which raises prices further, which triggers more panic buying.

The implications of these actions benefit some companies to the detriment of others. Memory and hardware suppliers like Micron and SanDisk are seeing a surge in demand from the industry. However, a pull-forward today often becomes an air pocket tomorrow. Thus, earnings over the next few years may remain unaffected in aggregate, but the timing may be significantly altered. Meanwhile, IT budgets at large enterprises are largely fixed, so every dollar diverted toward memory and scarce hardware is a dollar taken from software and consulting, precisely IBM's core business.

What To Watch Today

Earnings

Economy

Fed Speakers

Chair Kevin Warsh delivers day two of the semiannual monetary policy testimony, before the Senate Banking Committee at 10:00 a.m. ET, following Tuesday's House appearance. The Fed is not yet in its pre-FOMC blackout, so his tone on the cooler June CPI and sticky PPI is the read to watch.

Market Trading Update

Yesterday, Michael walked through the KOSPI bubble and the concentration risk hiding inside a country index. Today I want to read the other tape that mattered: big bank earnings kicked off the season, and as I argued in this past weekend's Bull Bear Report, the number that forecasts the economy isn't the headline beat. It's the credit book.

So did the four tells I told you to watch actually trip? Not yet. Wells Fargo posted the cleanest read of the group. Net charge-offs fell to $876 million, just 0.34% of average loans, down from 0.44% a year ago, as consumer losses dropped to 74 basis points due to lower auto and card write-offs. Deposits grew 10%. New card accounts jumped 46%. That is not a household balance sheet cracking.

JPMorgan told the same story. Its Card Services charge-off rate printed 3.34%, right on management's roughly 3.4% guide, and the consumer bank's reserves were flat. The $149 million reserve build Jamie Dimon's team did take landed in the WHOLESALE book, not the consumer. Firmwide charge-offs actually fell $44 million from a year ago. Citi's card delinquencies sit near 2.3%, the low end of the peer group. Read the footnotes, and the consumer passed this test.

Here's the catch, which is worth paying close attention to. These beats didn't come from Main Street. They came from the trading floor. JPMorgan's equity-markets revenue exploded 86%, Citi's equities desk rose 45%, and investment-banking fees ran 30% higher across the group. The bank bulls, Mike Mayo among them, will tell you the franchises have never been better capitalized. Fine. The consumer held, but he didn't drive the quarter. The deal desk did.

The tape sniffed that out. Goldman ripped 7.9% on its capital-markets haul, JPMorgan added 2.8%, and financials (XLF) led the day. But Wells Fargo, the purest lender in the bunch, slipped 0.7% on a clean beat. That's a sell-the-news fade on the one name most tied to the household, and it tells you how much good news is already priced into a group our own work flags as overbought.

The consumer earned the soft-landing benefit of the doubt for now. But the one thing nobody could verify this week is the private-credit and nonbank-lending exposure buried in these balance sheets, and that's the reserve line I'll read first next quarter. Bank the strength in the market, but don't chase it.

CPI Surprises

June's CPI report delivered the biggest downside surprise in years as the oil disinflation trade hit the data. Headline CPI fell 0.4% in June, versus forecasts of 0.0%. As a result, the annual rate fell sharply from 4.2% to 3.5%. The monthly decline was the largest since April 2020. Core CPI, excluding food and energy, was flat on the month against expectations for a 0.2% rise, pulling the annual core rate down to 2.6% from 2.9%. Core goods declined for the second straight month, down 0.09%; housing was up just 0.12%; and core services ex-housing was -0.2%, the lowest in four years. The graph below shows that the share of CPI components rising above the Fed's 2% goal is 59.2%, the lowest since inflation started rising in 2021.

Energy prices fell 5.7% after rising 3.9% in May, with gasoline prices down 9.7% and fuel oil down 9.2%. The data confirms that the BLS's three-week measurement lag finally caught up with the oil decline from $110 to the high $60s.

The Fed's newly hawkish tilt is likely to remain intact despite today's soft headline. A July hike is probably off the table, but September will likely keep rate-hike odds alive.

JPMorgan and Bank of America: Trading Profits Take Earnings Higher

JPMorgan (JPM) delivered a strong earnings report Tuesday morning. Revenue of $58.02 billion easily beat estimates by 13%, and its GAAP EPS of $7.70 crushed the $5.85 consensus. There are caveats, however. Its earnings jumped 41% to $21.2 billion, but excluding $5.6 billion in non-recurring one-time gains, growth was a more modest 13%. The standout line item was its trading departments. Equities revenue surged 86% to $6 billion, $2.11 billion above expectations. This is a payoff from the volatility markets experienced throughout the quarter, increased speculative retail trading behaviors, and the SpaceX IPO. JPM's net interest income slightly missed estimates of $25.65 billion, though it still grew 9.9% year over year.

Bank of America's (BAC) earnings were not as strong, but it, too, had impressive trading revenue. Net interest income came in at $16.2 billion, up 9%, driven by global markets activity and higher loan and deposit balances. It matched Wall Street's consensus.

The macro takeaway for investors is that second-quarter profits were bolstered by trading activity. Trading revenues and earnings are highly volatile and less dependable than the core banking services. To wit, net interest income, a bank's core earnings metric, suggests that the two banks' lending business is stable rather than rapidly accelerating. That helps explain the lackluster price activity, as we share below.

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A sailor who fixates on the barometer will rarely leave port. A sailor who never checks it will eventually get caught in a storm. It's easy for most investors to fall into one of those two modes, either warning that headwinds are approaching and taking cover, or waving off every warning because AI spending is carrying the market higher.

This article walks through several market headwinds that warrant attention, as well as a tailwind that may be large enough to keep the boat moving forward. Appreciating the headwinds and tailwinds in more detail will help you better monitor the market barometer, allowing you to assess and adjust risk levels with more awareness going forward.

Storm Forecasting

Market forecasting has more in common with hurricane forecasting than most investors appreciate. The goal when managing an investment portfolio is not to predict a single outcome but to understand the environment well enough to establish a range of possible outcomes.

When a hurricane is brewing, meteorologists don't draw a single storm track forecast on the map; they draw a “cone of uncertainty” that contains dozens of possible paths. Over time, as more information is gathered, the cone tightens.

Some storms cause immense damage, while others prove much weaker than expected. Other once-threatening storms never reach land and peter away in the ocean. Which path materializes depends on many variables layered on top of each other.  Like markets, it’s a dynamic process that is impossible to predict with certainty.

Investors face the same task as meteorologists. We must gauge the many forces acting on markets simultaneously and consider a slew of others that may or may not pressure markets in the future. Doing so efficiently provides us with a range of outcomes rather than relying on a single forecast.

With many headwinds arising, the job for investors right now is to closely track the environment and be ready to trim their sails if needed.

The Headwinds Worth Watching

Global Liquidity

Liquidity is the lifeline of markets. To wit, Stanley Druckenmiller once stated: 

"It's liquidity that moves markets"

With the recent surge in the use of derivatives, options, margin debt, and other forms of leverage, changes in liquidity conditions are even more important than ever in shaping market expectations.  

Michael Howell's Global Liquidity Index (GLI) uses factors such as central bank balance sheets, cross-border bank lending, shadow banking, repo markets, and collateral availability to assess how liquidity is likely to change. In a recent Commentary, in which we elaborate on his work and his current view, we stated:

The cycle is now pointing down into 2027. Howell projects $40 trillion in global debt rollovers by 2027, a $4 trillion increase from the previous year.  That borrowing demand comes as liquidity contracts, creating a mismatch between refinancing demand and tightening financial conditions.

The graph below charts Howell’s GLI alongside a 65-month sine wave that has been a good predictor of liquidity peaks and troughs. Howell’s index and the sine wave show the liquidity cycle peaked in mid-2025 and has been declining since, with the next trough not expected until 2027. Historically, the declining phase of this cycle has favored cash, long-duration government bonds, and gold over risk assets, precisely because a shrinking pool of global liquidity makes markets more dependent on cash flow and less prone to speculative excess.

Treasury Issuance

In a similar vein, the federal deficit continues to demand liquidity to fund the rapidly growing issuance of Treasury debt. That supply of debt has to be absorbed by someone. Heavier net debt issuance competes with demand for all other investments. On the demand side, with no QE and domestic banks constrained by regulation, there is less ability to absorb the new supply than in years past.  

Bear in mind, however, that if there is a stimulus package or even increased government spending to boost support for Republicans in the midterm elections, this headwind can also be a tailwind.

Restrictive Fed Policy

Even with the last cycle of rate cuts, real policy rates, as shown below, remain above levels most economists would consider neutral. Such a restrictive policy works with a lag, and the economy has so far absorbed it well. That does not mean the lagged effects are gone.

Furthermore, the Fed’s hawkish tone and the potential for rate increases could make financial conditions even more restrictive.

The Yield Curve And Volatile Equity Rotations

We recently wrote, Are Flattening Yield Curves and Style Rotations Deceptive Omens, to help readers differentiate between monitoring financial conditions and timing market tops.

The article explains why a bear flattening of the yield curve and instability in leadership between growth and value stocks, as we are witnessing now, are both symptoms of the repricing of growth expectations and the discount rate. The lesson from that piece is that these signals describe a changing environment but do not tell you when or whether a market or economic downturn might occur.    

The last two sentences of the article sum up this headwind well:

The signals suggest the regime may be changing, and we should be prepared for that possibility. However, until that becomes more evident, we must take advantage of what the market has to offer. 

Low VIX – High Implied Correlation

Our daily Commentary from July 9, 2026, points out a wide and unusual divergence between the low S&P 500 volatility index (VIX) and the lack of correlation among the index's individual stocks. 

As we share below, the condition represents a potential headwind, but for now, just something to be mindful of.

The low VIX (first graph) implies smooth sailing ahead, while a record-low implied correlation (second graph) suggests the market could be at risk. Goldman is hedging the risk of a correction, i.e., an implied correlation spike. Often, when implied correlation rises sharply from extreme lows, as it did in August 2024 during the yen carry trade unwind, the divergences that kept the index calm disappear. Stocks start moving together again, and most of the time they move down. This condition is not a warning to expect a market downdraft, but it does suggest that risk awareness is critical.  

Midterm Elections

Markets tend to dislike uncertainty. Accordingly, the months leading up to the midterm elections often bring volatility. This year, the potential for the Democrats to regain the House and, less likely, to take the Senate as well poses greater risks than if the Republicans were expected to maintain control of both houses.

We suspect that toward later summer and early fall, market trepidation will increase over the unknown election outcomes and what they may mean for policies and ultimately markets. Accordingly, this is likely a stock market headwind that will intensify as the year progresses.

Consumer Struggles

After two strong months of outsized growth, consumer credit, mainly credit cards, contracted for the first time in almost two years. The personal savings rate sits at 3.0%, near its lowest level since 1960. Both sets of data indicate that consumers' wage growth is no longer keeping pace with inflation, forcing them to reduce borrowing and/or draw down savings and run tighter budgets.

This is a genuine headwind, and it isn't going away soon. But it's not the whole consumer story either. Unemployment remains low, and the struggle appears concentrated among lower-income individuals and parts of the middle class. Many indications of spending among upper-income households point to continued strength, and that cohort accounts for an outsized share of total consumption. Per Yahoo Finance:

A new report from Moody's Analytics shows the top 10% of earners now account for nearly half of all U.S. consumer spending, a historic high that shows how dependent economic growth has become on wealthy households.

A squeezed lower class matters for retailers and lenders exposed to that segment, but less for the broader market, where spending is increasingly a story about who still has room to spend.

This is a headwind worth watching more closely if the unemployment rate starts to rise and financial struggles spread to higher-income earners.

Tailwinds That Could Become Headwinds

Margin Debt

Record levels of margin debt have boosted demand for stocks, providing a strong tailwind for the market. As we wrote in Margin Debt Risk;

Margin debt just set another record. In May 2026, investors owed their brokers a combined $1.42 trillion, the highest in history and a 53.7% jump from the prior year.

While record and growing margin debt is a powerful tailwind, it’s a wind that can reverse direction suddenly. Per the article:

Leverage peaks near tops. Then it mean-reverts violently because the unwind forces the selling.

In addition to watching margin debt, pay attention to the most favored stocks. Today, semiconductor stocks are bolstered by a disproportionate share of the margin. If they start faltering while the broader markets hold up, this may be a sign that margin usage is about to reverse. Further, any indication of liquidity trouble in the money markets could also result in a decline in margin debt.

The Yen Carry Trade

The yen carry trade is a source of leverage pushing the market higher. As we wrote in a recent Commentary:

The carry trade thrives with a weak yen, as we have today.  Despite higher Japanese borrowing costs, the yen has depreciated significantly against the dollar, more than offsetting the higher interest costs for carry trades. A weakening yen means the trade remains profitable, and the leverage the carry trade provides to markets continues to build.

The risk today to US investors is that higher Japanese yields and a stronger yen could force a rapid, disorderly reversal of the carry trade.  Bear in mind that the more the yen falls, the more the trade grows, and the larger the unwind will be whenever the BOJ finally acts.

The Tailwind: AI Capital Spending

Working against every headwind we discussed, and others, is a single counterweight of extraordinary size: the capital spending boom tied to artificial intelligence infrastructure.

The four largest hyperscalers (Amazon, Microsoft, Alphabet, and Meta) are on pace to spend roughly $725 billion combined on capital expenditures in 2026, up about 75% from last year.  Goldman Sachs has raised its cumulative capex estimate for these four companies from 2025 through 2030 to $5.3 trillion, up from $4.5 trillion prior to first-quarter earnings.

That spending shows up directly in corporate earnings, employment in construction and semiconductors, and demand for everything from GPUs to transformers to turbines. The spending is also self-reinforcing in the near term. For instance, cloud backlogs at companies are growing, giving management the revenue predictability needed to justify increased spending. Although there is considerable skepticism about the durability of this spending cycle, it has thus far yielded results that suggest otherwise.

This is the tailwind doing the heavy lifting in the economy and market. It has been large enough and persistent enough to absorb concern about the headwinds. The question worth asking is not whether the tailwind is real but how much further it can carry markets before the headwinds start to matter more than the continued spending.

Summary: Take Advantage Or Trim Your Sails?

In meteorological speak, the Cone of Uncertainty is wide. However, just because the headwinds are numerous and the range of potential outcomes is vast, investors don't need to trim their sails and batten down the hatches.

The more productive approach is to keep using the favorable winds while they are blowing, and to pay close attention to market barometers and remain prepared for a shift in the winds. That means participating in the areas of the market most directly tied to the AI capital spending cycle while it remains intact, while also paying attention to balance sheet quality, maintaining valuation discipline, closely monitoring technical conditions, and remaining diversified in other sectors less impacted by the AI spending boom.

The post Headwinds And Tailwinds: Minding The Market Weather appeared first on RIA.

Semiconductor chip companies have been benefiting from strong momentum and a powerful narrative. For instance, memory chip producers like Micron, AMD, and Intel have risen by 192%, 138%, and 166%, respectively, year to date. While they provided a nice boost to the Nasdaq and an impressive, albeit lesser, tailwind to the S&P 500, the impact of Korean chipmakers on the Korean Composite Stock Price Index (KOSPI) has been stunning.

Consider the graph below, showing that the KOSPI has grossly outperformed the Nasdaq over the last three years. Incredibly, most of the KOSPI gains have occurred over the last year. Since the beginning of 2026 alone, the index has surged more than 88%. The KOSPI is now up over 200% in the last two years.

The reason for its parabolic ascent is two stocks. As of June 30, 2026, Samsung Electronics and SK Hynix together account for nearly 60% of the KOSPI, up from roughly 40% just two years ago. For context, Nvidia and Apple combined account for only about 20% of the Nasdaq.

The concentration carries serious risks. One such risk is regulatory. Goldman Sachs warns that if the combined KOSPI weight rises by just one more percentage point, foreign institutional investors subject to US Investment Company Act diversification rules will be forced to sell.

The KOSPI is no longer a gauge of South Korea or its financial markets. It is a bet on the global AI infrastructure buildout, packaged as a country index.

What To Watch Today

Earnings

Economy

Fed Speakers

Chair Kevin Warsh delivers the semiannual monetary policy testimony before the House Financial Services Committee at 10:00 a.m. ET, roughly 90 minutes after the CPI print. His debut testimony as Chair, with the Senate Banking hearing to follow on July 15. The Fed is not yet in its pre-FOMC blackout.

Market Trading Update

Yesterday, I discussed the technical backdrop coming into this trading week and published a piece on why spotting market bubbles is nearly impossible in real time. If you didn't read it, I want to recap on it today, as it is important given some of the prognostications running through the media, and there is one image that keeps landing in my inbox. It’s the AI bubble analog: today’s Nasdaq laid on top of the 1998 to 2001 Nasdaq, scaled so the two curves march up the page together. The caption always reads some version of “deja  vu.” Look at it for three seconds, and the conclusion writes itself.

Here’s the problem with that chart. It’s a magic trick built from two y-axes. The left axis runs the modern Nasdaq from 10,000 to 26,000. The right axis runs the old one from 1,000 to 5,000. Stretch and squeeze the scales until the curves kiss, and any two rising markets will look like twins. Shape is not substance.

The differences from 1999 are real, and they matter. In March 2000, dozens of marquee Nasdaq names had no earnings, no cash flow, and a business model built on burning venture money to buy eyeballs. Pets.com had about nine months of cash in the tank when it went public. Cisco, the most valuable company in the world at the peak, traded north of 100 times trailing earnings. That was a market priced on stories.

Today’s leaders are a different animal. Nvidia, Microsoft, Alphabet, and Meta generate enormous free cash flow. Nvidia alone booked tens of billions in operating profit last quarter. The technology is REAL, and so are the profits underneath the biggest names. A bubble built on hope pops one way. A bubble built on real but over-extrapolated earnings pops another. That distinction is the whole ballgame for how much damage a reset actually does.

Read that scorecard the right way. It’s not a green light, and it’s not 1999 wearing a costume. It’s a stretched market with one dominant story and severe concentration, sitting atop profitability, policy, and retail behavior that are all in better shape than they were at the last comparable top. The piece that worries me more than the headline multiple is that concentration. When a handful of names drive most of the index return, you don’t own a diversified portfolio anymore.

Bubbles, real or imagined, create a behavioral problem more than a portfolio problem. Investors flip from all-in to all-out on the week’s headlines, and both extremes are usually wrong. Stocks aren’t a light switch. The decision is rarely between fully invested and fully in cash, so stop framing it that way.

Four rules have carried through every prior cycle.

1. Stay invested in a diversified mix you can defend in any tape.
2. Trim what’s run, add to what hasn’t.
3. Hold meaningful positions in assets that behave differently from the popular trade, including bonds, value stocks, and, most importantly, cash, which gives you an opportunity.
4. Above all, define in advance what would force you to reduce risk, and write it down.

I’ve argued for a while that bonds remain the best stabilizer for most investors, because in a true unwind, when growth and inflation expectations fall together, that negative correlation with stocks tends to reassert itself.

You don’t need to know when the music stops. You need to know what your book looks like when it does. That’s the question to answer this week, well before it turns urgent.

Breadth Improves Post Quarter End

The Heat Map below, courtesy of FinViz, shows that last week was very mixed, with much divergence within sectors. For instance, in the communications sector, Meta was up double digits while Google fell by 2.5%. Similarly, NVDA and AVGO led the semiconductor sector higher by over 5%, while many of the recent chip outperformers, such as MU and INTC, performed poorly. As a result, the market's breadth improved, with recent outperformers now underperforming and vice versa.

The second graphic from our soon-to-be-released new version of SimpleVisor shows that the sectors are clustered around fair value. Our new dispersion index, which measures breadth, is relatively low, signaling a healthy market. However, while the sectors show lower dispersion relative to each other, there is still considerable dispersion within some sectors.

The third graphic shows that the factors are even more clustered, again signaling that market breadth has improved significantly. Of the 23 factors, 20 have relative scores within ±0.20 of fair value.

Spotting Market Bubbles: Why History Says Its Nearly Impossible

If you knew you were standing inside a stock market bubble, you wouldn’t be standing in it for long. You’d sell. So would I, and so would everyone reading this. And if spotting market bubbles was something everyone could do in real time, the bubble couldn’t form in the first place. That paradox is why spotting market bubbles is one of the hardest jobs in finance, and why bubbles look painfully obvious only after the fact.

Market bubbles are not a modern invention. They’ve been a recurring feature of financial life for almost 400 years, ever since the first organized stock exchange opened in Amsterdam in the early 1600s.

The Dutch Tulip Mania of 1636 to 1637 is the textbook case. Tulip bulb prices in the Netherlands soared roughly twentyfold in a few months, then collapsed by about 99% in May 1637. Less than a century later, the South Sea Bubble of 1720 took shares of the South Sea Company from £128 in January to £1,050 in June before collapsing back to near the starting price by year-end. Isaac Newton, often cited as the smartest man of his era, lost a fortune in that one. He’s reputed to have said: “I can calculate the motion of the heavenly bodies, but not the madness of crowds.”

The 20th century gave us bigger versions of the same story. The Roaring Twenties ended with the 1929 crash and a peak-to-trough Dow drawdown of nearly 89% by 1932. Japan’s late-1980s asset bubble carried the Nikkei 225 to 38,915 on December 29, 1989, and triggered a collapse that eventually took the index down more than 80%, with the post-bubble low not arriving until October 2008, nearly 19 years after the peak. Then came the dot-com bubble. Between January 1995 and March 10, 2000, the Nasdaq Composite rose roughly 572% to a peak of 5,048.62. It then fell 78% by October 2002, and didn’t recover its 2000 high until April 2015.

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If you knew you were standing inside a stock market bubble, you wouldn't be standing in it for long. You'd sell. So would I, and so would everyone reading this. And if spotting market bubbles was something everyone could do in real time, the bubble couldn't form in the first place. That paradox is why spotting market bubbles is one of the hardest jobs in finance, and why bubbles look painfully obvious only after the fact.

Market bubbles are not a modern invention. They've been a recurring feature of financial life for almost 400 years, ever since the first organized stock exchange opened in Amsterdam in the early 1600s.

The Dutch Tulip Mania of 1636 to 1637 is the textbook case. Tulip bulb prices in the Netherlands soared roughly twentyfold in a few months, then collapsed by about 99% in May 1637. Less than a century later, the South Sea Bubble of 1720 took shares of the South Sea Company from £128 in January to £1,050 in June before collapsing back to near the starting price by year-end. Isaac Newton, often cited as the smartest man of his era, lost a fortune in that one. He's reputed to have said: "I can calculate the motion of the heavenly bodies, but not the madness of crowds."

The 20th century gave us bigger versions of the same story. The Roaring Twenties ended with the 1929 crash and a peak-to-trough Dow drawdown of nearly 89% by 1932. Japan's late-1980s asset bubble carried the Nikkei 225 to 38,915 on December 29, 1989, and triggered a collapse that eventually took the index down more than 80%, with the post-bubble low not arriving until October 2008, nearly 19 years after the peak. Then came the dot-com bubble. Between January 1995 and March 10, 2000, the Nasdaq Composite rose roughly 572% to a peak of 5,048.62. It then fell 78% by October 2002, and didn't recover its 2000 high until April 2015.

The 2008 housing-and-credit bubble ended differently. Instead of a single speculative asset, the bubble formed in mortgage credit and spread across the entire global banking system. The S&P 500 lost 57% from its peak to its trough. None of these episodes looked the same on the way up. Yet all of them look identical on the way down. This is why spotting market bubbles is always a function of hindsight.

Notice in the chart above. The drawdowns from the four largest equity bubbles ranged from 57% to 99%. None of them recovered quickly. The Nasdaq took 15 years. The Nikkei took 34 years to finally reclaim its 1989 peak, hitting it in February 2024, before pushing on to fresh all-time highs since. The damage from a real bubble isn't measured in months. It's often measured in lost decades.

Why Spotting Market Bubbles Is Mostly Hindsight

As stated above, spotting market bubbles in advance is often futile. Just because assets sport high prices, valuations, or any other metric you choose, those alone do not necessarily define a bubble. A good example of the futility of spotting market bubbles in advance was in 1996 when Alan Greenspan warned of "irrational exuberance." Yes, prices were elevated, sentiment was extremely bullish, and the Nasdaq then tripled over the next three and a half years before peaking. Anyone who sold on that warning missed an enormous gain before the eventual crash. That's the trap.

Owen Lamont, a portfolio manager at Acadian Asset Management who has spent years studying market extremes, put it bluntly. He once joked that a bubble is just "when I think the stock market is overpriced and then it doubles." That's not really a joke. It captures the practical impossibility of timing a top in real time. Stanley Druckenmiller, working alongside George Soros, identified the Japanese bubble in 1988 and shorted it. The Nikkei kept ripping higher into late 1989, and Druckenmiller eventually said his lesson was simple." Valuation is not a catalyst."

Bubbles also sustain themselves through narrative, not arithmetic. In 1999, the story was that the internet had repealed the rules of economic gravity. Cisco Systems, the world's most valuable company at its peak, traded at a trailing P/E ratio above 100. In 1989, the story was that Japan Inc. was unstoppable. In 2007, the story was that housing prices would never fall nationally. Each story was wrong, but each story sounded reasonable at the time, especially because each story had real evidence supporting it. The internet did transform commerce. Japan was a manufacturing powerhouse. Housing prices had not, in fact, fallen nationally for decades. The bubble forms when investors take a real trend and extrapolate it past any reasonable mean reversion.

The Four Horsemen Investors Should Watch

So, with that said, if high prices or valuations alone don't make a bubble, what does? Several decades of academic and practitioner research point to a consistent checklist. Lamont calls them the four horsemen, and they are essentially what you would expect.

1. High prices, measured by valuation multiples that significantly exceed long-term averages.
2. High volatility. Bubbles don't drift higher quietly. They lurch up and down with bigger and bigger swings.
3. High trading volume, particularly among retail and speculative accounts that were previously inactive.
4. The spread of "bubble beliefs," the idea that this time is different and traditional valuation rules no longer apply.

However, for me, I would include a fifth indicator that's saved me more than once. It's defensiveness. When the cheerleaders of an asset stop selling its merits and start attacking the people who question it, the bubble has gone parabolic. We saw it in late-1999 internet stocks. We saw it again at the 2021 SPAC mania and the Bitcoin peak. And we saw it most recently in the 2025 precious metals run.

When I published my critique of the commodity supercycle and dollar-debasement thesis last year, the response from precious metals advocates wasn't a counterargument backed by data. It was dismissal and accusations of being on the wrong side of history. Silver then rallied roughly 135% on the year before suffering its biggest single-day drop since the 1980s in late January 2026. Gold knocked more than 10% off its peak in the same window. When debate stops, and tribal loyalty takes over, the top is usually close.

How the Current Setup Compares to 1999

Naturally, the question is whether we are currently "spotting a market bubble"? The honest answer is that some signals are flashing yellow. Others aren't.

The yellow signals are real. The S&P 500's cyclically adjusted P/E sits within striking distance of the all-time high set in December 1999. Concentration risk is severe. The top 10 stocks now make up a larger share of the S&P 500 than tech, media, and telecom did at the March 2000 peak. Performance for AI infrastructure leaders has gone parabolic. A normalization of multiples back toward the long-term average would, by itself, deliver a market drawdown of 30% or more even without a recession.

However, the differences from 1999 are real and matter. In March 2000, dozens of marquee Nasdaq names had no earnings, no cash flow, and business models built on burning venture capital to acquire eyeballs. Today's leaders, meaning Nvidia, Microsoft, Alphabet, and Meta, throw off enormous free cash flow. Pets.com had 9 months of cash left when it went public. Nvidia generated tens of billions in operating profit last quarter. That isn't a small distinction. A bubble built on hopes and venture capital pops differently than one built on real, but extrapolated, earnings power.

The table below puts the comparison on a single page. Some indicators are eerily similar. Some are actually worse today. And a few key fundamentals are meaningfully better.

Read the verdict column carefully. Out of 13 indicators, four flash similar or worse than 2000, six look genuinely better, and three sit on the watch list. That's not a green light. It's also not 1999 with a new ticker symbol. The honest read is that we have a stretched market with a single dominant narrative and severe concentration, but with profitability, monetary policy, and retail behavior in better shape than they were at the last comparable top.

The piece that worries me more than the headline P/E is concentration. When the S&P 500 owes most of its return to a handful of stocks, you don't actually own a diversified U.S. equity portfolio. You own a thematic AI bet dressed as an index fund. That's the exposure most readers should be measuring carefully right now.

How to Stay Invested Without Catching a Falling Knife

Bubbles, real or imagined, create a behavioral problem more than a portfolio problem. The behavioral problem is that investors flip from "all in" to "all out" based on the week's headlines. Both of those positions are usually wrong. Stocks aren't a light switch. The decision is rarely between fully invested and fully in cash.

What's actually worked through every prior bubble cycle is straightforward.

1. Stay invested in a diversified mix you can defend in any tape.
2. Trim what's run, add to what hasn't.
3. Hold meaningful positions in assets that behave differently from the popular trade, including bonds, value stocks, and, most importantly, cash, which gives you an opportunity.
4. Above all, define in advance what would force you to reduce risk, and write it down.

I've been arguing for some time now that bonds remain the best portfolio stabilizer for most investors, even after the 2022 drawdown. In a real equity unwind, bonds historically offset stock losses through the duration trade as the Fed cuts in response. That's the relationship that briefly broke down in 2022 because both stocks and bonds were repricing higher inflation at the same time. In a true bubble pop scenario, when growth and inflation expectations both collapse, the negative correlation tends to reassert itself.

The other rule is worth repeating. Rebalancing is not market timing. Selling some of your winners and buying some of your laggards forces you to do something contrarian on a calendar, not on a hunch. Investors who rebalanced annually from 2000 to 2002 still suffered, but suffered far less than those who rode the Nasdaq concentration into the abyss.

Free Resource: If you want the full framework we use to stress-test client portfolios for concentration risk, download our RIA Portfolio Risk Guide. It walks through the same checks our team runs every quarter.

The Signals That Mark the End

What actually triggers the unwind, in past bubbles, is rarely the thing analysts spend the most time worrying about. The Fed didn't pop the Nasdaq with the warnings of 1996. The Fed popped it with the 1999 and 2000 rate hikes. The Bank of Japan popped its bubble by raising the discount rate from 2.5% to 4.25% in late 1989. In 2007, a small wave of subprime mortgage delinquencies sparked the contagion. The catalyst is usually a tightening of liquidity, not a change in the narrative.

Several signs tend to cluster near the top:

• First, a flood of new stock issuance. SPACs in 2021. Internet IPOs in 1999 and early 2000. When the supply of speculative paper finally meets demand, prices roll over. Lamont himself has flagged issuance as the single signal he's watching most closely right now. With multiple AI-era giants reportedly preparing to go public, that signal is worth tracking week to week.
• Second, a shift from "buy the dip" to "buy the rip." Healthy bull markets see investors add on weakness. Late-stage bubbles see investors pile in on strength because they're afraid of being left behind. That FOMO behavior is the textbook performance-chasing pattern.
• Third, mainstream financial coverage that stops debating valuation entirely. When the question "are we in a bubble" disappears from major publications and gets replaced by exclusive feature stories on the personal lives of momentum traders, the top is usually close. We aren't there yet, but we're closer than we were a year ago.
• Fourth, a credit event. Bubbles don't usually pop from inside the asset. They pop because something in the financing chain breaks. In 2000, it was margin calls and burning cash balances. Then, in 2008, it was subprime credit. In 2021, it was the SPAC unwind that started taking down low-quality issuers.

The next pop, whenever it comes, will likely be triggered by stress somewhere in private credit, leveraged loans, or AI infrastructure financing rather than in the equity market itself.

The bottom line is that you don't need to know exactly when the music stops. You need to know what your portfolio looks like when it does. That's the question to ask yourself this week, well before the question becomes urgent.

The post Spotting Market Bubbles: Why History Says It’s Nearly Impossible appeared first on RIA.

The graph below paints a very interesting picture of US energy efficiency and a key structural economic change in this country. For roughly 25 years after WWII, the US economy's crude oil consumption nearly tripled. Feeding the growth were a booming post-war economy and strong population growth. To put consumption in a different context, the graph shows consumption as a ratio to a dollar of real GDP, on a per capita basis. It shows that consumption per dollar of GDP declined rapidly starting in the mid-1970s, suggesting an increase in US energy efficiency. The US per capita energy efficiency is less pronounced but noticeable. In addition to productivity gains and urbanization, there are a few reasons for the gains in efficiency.

• The 1973 Arab oil embargo was a shock to the economy. During this time, a quadrupling of gas prices and long gas lines forced policymakers and consumers to treat oil as a strategic vulnerability rather than a cheap given.
• Washington enacted numerous measures in response to persistently high oil prices in the 1970s. For instance, the Energy Policy and Conservation Act of 1975 mandated US energy efficiency standards for appliances and introduced fuel-economy standards. Legislators also encouraged a shift from oil and natural gas to coal for power generation. Utilities largely stopped building oil-fired plants.
• Structural change was equally important. The economy shifted from heavy manufacturing to services and technology, sectors that require far less energy per dollar of output.

Ironically, AI data centers are now driving a renewed focus on efficiency, this time with natural gas and renewables.

What To Watch Today

Earnings

• No notable earnings today

Economy

Market Trading Update

Price closed Friday at 7,575, sitting 1.86% above its rising 50-day moving average near 7,429 and a healthy 8.7% above the 200-day average at roughly 6,960. Both averages slope higher, and the price is above both. That is a bullish structure, full stop. The 14-day RSI reads 59, which is firmly neutral with room to run before it flashes overbought, and the MACD remains in a positive posture with the signal line trailing below. Momentum is constructive, not stretched.

The wrinkle is under the surface. This week's advance was driven by a handful of names while the equal-weight index and small caps slipped, so the momentum you see on the chart is thinner than it looks. We have maintained equity exposure at target weight in our models since April 17, and this is precisely the tape that argues for discipline rather than taking on fresh risk. When the generals march, and the troops sit, you respect the trend, but you tighten your stops.

Volume told the same story as breadth. The push toward the highs came on unremarkable participation, and the new-high lists were dominated by the same technology and communication-services names that led the tape all week. That is not the broad thrust you want confirming a durable breakout to fresh records. At nearly 9% above the 200-day average, the index is not dangerously stretched, but it is closer to the top of its typical band than the bottom, which is another argument for buying pullbacks rather than chasing breakouts. It does not break the uptrend. It lowers the quality of it.

The line that matters most next week is 7,612. A clean, high-volume breakout above the June record clears the runway toward 7,700 and keeps the trend intact. A failure right at the old high, especially on the same narrow breadth we saw this week, would set up a pullback to the 50-day average, and that is the level I would be watching for a low-risk entry rather than chasing strength into resistance.

The Week Ahead

After a lull in economic data, we get three important data releases, two days of congressional testimony from Fed Chair Warsh, and the opening of Q2 earnings season.

The June CPI, to be released on Tuesday, is expected to show no headline inflation and +0.2% core inflation. Such a reading may give the Fed some confidence that the recent spurt in inflation is Iran/oil-related and reversing. The market will look at PPI in a similar vein. Retail Sales on Thursday is the consumer reality check. With credit card delinquencies at 15-year highs, the savings rate near historic lows, and elevated gasoline prices, the risk is skewed toward a soft print. The consensus is for a 0.3% gain after a hot +0.9% last month. Also, watch the control group, which feeds directly into GDP calculations.

Fed Chair Warsh testifies before the House Financial Services Committee on Tuesday, July 14, at 10 am ET, and the Senate Banking Committee on Wednesday, July 15. This will be his first Humphrey-Hawkins appearance as Chair. We want to see just how transitory he thinks the recent inflation push will be. Furthermore, whether his "AI productivity disinflation" thesis surfaces. We presume he will be bold in his call to get inflation back to target. With fewer Fed speeches, no dot plots, and no forward guidance, this quarterly testimony is now one of the only windows markets have into Warsh's thinking.

Financials kick off earnings next week, as we share below.

AI Capex Risk Cuts Both Ways In The American Economy

Just over a year ago, I made the case that the deficit narrative would find its cure in artificial intelligence. Goldman Sachs has since published research that, on first reading, appears to refute. It isn’t. But after more than thirty years of watching capex cycles play out, I’ve learned the right move when new data lands is to test the original argument against it. So far, that thesis from June 2025 holds. However, the AI capex risk profile has gotten sharper since then, and the argument needs tightening in a few places. The bull case and the tail risk are now the same buildout, but they are running in different directions.

The case I made last June rested on a straightforward chain. The deficit narrative was overstated. AI infrastructure would lift GDP. A higher denominator would stabilize debt-to-GDP. That chain still holds. However, Goldman’s economics team, led by Elsie Peng, just published a careful look at how much of all this AI capex actually flows through to measured U.S. GDP, and the answer landed well below most published estimates.

The backdrop has also gotten messier. The BEA’s second estimate revised Q1 2026 GDP growth down to 1.6% from the 2.0% advance estimate, with most of the downgrade attributable to inventory investment. Strip out the rebound in federal spending after the Q4 government shutdown, and core domestic demand looks softer than the headline. Middle East supply shocks, lingering tariff effects, and tighter immigration are all weighing on the consumer side. That backdrop turns AI capex risk from an academic question into a portfolio-management one. AI capex isn’t just a contributor to growth. It’s increasingly the entire growth story.

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🔎 At a Glance

• Big Bank Earnings Kick Off Earnings Season
• Market Brief & Technical Review
• From Lance's Desk: AI Capex Risk Cuts Both Ways In The American Economy - RIA
• Market stats, screens, and risk indicators

🏛️ Market Brief - Mega-Cap Tech Retakes The Lead

The tape flipped its script this week. As we noted two weeks ago, we rotated back to the mega-cap growth stocks. Since then, the mega-cap complex grabbed the wheel again and dragged the index within a whisker of a new record. The S&P 500 rose 1.38% to close Friday at 7,575. That leaves it less than 1% below the June 2 all-time high of roughly 7,612. The Nasdaq Composite added about 1.8%, and the winners were exactly the names you would guess.

Meta Platforms exploded 14.5% on the week. Nvidia tacked on 7.8%. That is where the fuel came from, and the breadth numbers prove it. The Dow slipped 0.30%, the Russell 2000 fell 0.53%, and the S&P 500 Equal Weight index dipped 0.18%. Read that again. The cap-weighted benchmark climbed while the average stock went nowhere or lost ground. That is the opposite of the broadening we flagged in last week's discussion of the rotation. Narrow leadership is back.

The macro backdrop is where things get interesting. June payrolls came in at just 57,000, roughly half of what economists penciled in. Furthermore, the unemployment rate ticked to 4.2%. Softer labor data would normally be a warning, yet the market cheered it, because it pushed the odds of a September rate cut up toward 80%.

The problem is that inflation refuses to cooperate. May CPI ran at 4.2% year over year, up from 3.8% in April, so the Fed is staring at a slowing job market and sticky prices at the same time. Energy led all sectors, up 3.31% on firmer crude, while technology gained 2.93%. Defensives lagged badly, with materials, health care, and staples all lower.

Across assets, the 10-year Treasury yield backed up to 4.54% from 4.49% a week earlier, a quiet reminder that the bond market is not fully sold on those cut odds, and the VIX stayed becalmed near 15.7. Calm tape, hot inflation, cooling jobs. That particular combination rarely coexists for long without one of the three forcing the other two to move.

Into the coming week, watch whether the mega-cap bid is a durable leadership shift or a one-week head fake. If Meta and Nvidia are doing all the heavy lifting again, the index can print a new high while most portfolios feel left behind. That gap between the headline and the holdings is the story I would keep front and center.

📈Technical Backdrop - Coiling Below The Record

Price closed Friday at 7,575, sitting 1.86% above its rising 50-day moving average near 7,429 and a healthy 8.7% above the 200-day average at roughly 6,960. Both averages slope higher, and the price is above both. That is a bullish structure, full stop. The 14-day RSI reads 59, which is firmly neutral with room to run before it flashes overbought, and the MACD remains in a positive posture with the signal line trailing below. Momentum is constructive, not stretched.

The wrinkle is under the surface. This week's advance was driven by a handful of names while the equal-weight index and small caps slipped, so the momentum you see on the chart is thinner than it looks. We have maintained equity exposure at target weight in our models since April 17, and this is precisely the tape that argues for discipline rather than taking on fresh risk. When the generals march, and the troops sit, you respect the trend, but you tighten your stops.

Volume told the same story as breadth. The push toward the highs came on unremarkable participation, and the new-high lists were dominated by the same technology and communication-services names that led the tape all week. That is not the broad thrust you want confirming a durable breakout to fresh records. At nearly 9% above the 200-day average, the index is not dangerously stretched, but it is closer to the top of its typical band than the bottom, which is another argument for buying pullbacks rather than chasing breakouts. It does not break the uptrend. It lowers the quality of it.

The line that matters most next week is 7,612. A clean, high-volume breakout above the June record clears the runway toward 7,700 and keeps the trend intact. A failure right at the old high, especially on the same narrow breadth we saw this week, would set up a pullback to the 50-day average, and that is the level I would be watching for a low-risk entry rather than chasing strength into resistance.

🔑 Key Catalysts Next Week

Two storylines collide next week, and both land on the same days. The macro question is whether June inflation confirms the reacceleration we saw in May, and the market question is whether the big banks validate the earnings optimism baked into financial stocks. The marquee event is Tuesday's CPI report at 8:30 a.m. ET. Consensus looks for a cooler headline near 3.5% year over year, but the Cleveland Fed nowcast is tracking closer to 4%. That gap is the whole ballgame for the September rate-cut narrative.

PPI follows on Wednesday, retail sales and jobless claims hit on Thursday, and Friday brings housing starts and the first read on July consumer sentiment. Anything that reinforces sticky inflation while the labor market softens revives the stagflation worry we have written about all spring. On the earnings side, the money-center banks open the Q2 season, and their commentary on credit and the consumer will set the tone for everything that follows.

The single most market-moving event is Tuesday's CPI, and the asymmetry is what makes it dangerous. A cool print near 3.5% lets the September-cut trade run and likely pushes the S&P through its record. A hot print with a 4-handle would force the market to reprice the Fed in a hurry, and that is the outcome that would do the most damage to a tape already leaning on just a few names.

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💰 What Big Bank Earnings Will Tell Us About The Consumer

Every quarter, the ritual is the same. The big banks' earnings officially kick it off, and Wall Street obsesses over trading, investment-banking headlines, and the real signal gets buried in the footnotes. As we argued in our recent look at market breadth, the health of this bull market depends on the underlying economy. Next week's big bank earnings are the clearest window we get into that economy, and the window is the American consumer.

Financials enter this reporting season with the market expecting sector earnings growth above 12% and revenue growth north of 8%. Simply, the bar is not low.

Goldman Sachs is expected to earn $13.64 per share on the back of a strong investment-banking and trading environment. JPMorgan is pegged near $5.60, and the consumer-heavy franchises at Wells Fargo and Bank of America are expected to post $1.72 and $1.10, respectively. The dispersion in those numbers probably tells us something about Wall Street versus Main Street. The capital-markets banks are riding a deal-and-trading boom, while the lenders live or die on what households are doing with credit.

Here is the tension. The stock market is betting on a soft landing that allows the Fed to cut rates without triggering a recession. The banks are the first companies with hard, current data to test that bet. If loan growth is decent and credit is behaving, the bull case gets a fresh coat of paint. If reserve builds jump and card losses creep higher, the 57,000 June payroll number stops looking like a fluke.

The Credit Signals Buried In The Big Bank Earnings

Forget the headline beat or miss. The numbers that actually forecast the economy are the credit metrics, and they rarely make the front page. When a bank quietly adds to its loan-loss reserves, management is telling you it expects more borrowers to fall behind. When net charge-offs climb, borrowers already have. Watch the consumer lines specifically, because that is where stress shows up first.

The reason this matters right now is the labor market. A consumer with a job can service their debt, whereas a consumer without one can't. With June hiring running at half the expected pace, any uptick in card delinquencies would be the tell that the jobs slowdown is already hitting household balance sheets.

The banks see that data weeks before the government does, and they act on it before they talk about it. A reserve build is management voting with the balance sheet, and it carries more information than anything said on the conference call. Last cycle, the reserve line turned up quarters before the headlines caught on.

The tells are specific, and they rarely sit in the headline. Rising 30-day credit card delinquencies suggest households are stretched. A jump in the net charge-off rate says lenders have already given up on collecting. Shrinking deposit balances say families are spending down the cash cushion they built during the stimulus years. Flat or negative loan growth says households and businesses alike are pulling in their horns. One of those moving is noise. Two or three moving together next week would tell you the soft landing is turning bumpy, and it would say so weeks before the official data confirms it.

Net Interest Margins Into A Rate-Cut Cycle

The second major theme is how falling rates affect bank profitability. Net interest margin is the spread between what a bank earns on loans and what it pays for deposits. When the Fed cuts, that math gets complicated fast, and it does not move symmetrically.

Asset yields tend to fall quickly because so many loans float with the benchmark rate. Deposit costs come down more slowly because banks are reluctant to cut what they pay savers who could walk to a competitor or a money-market fund.

That lag pinches margins in the early innings of an easing cycle. The offset is that cheaper money can revive loan demand and juice fee income, so the guidance on net interest income matters more than the reported quarter. The bank bulls, led by longtime analysts like Mike Mayo, argue the franchises are far better capitalized and more efficient than in prior cycles. They may be right. THE MARGIN MATH STILL HAS TO CLEAR.

The banks are not just companies to trade around earnings. They are the circulatory system of the economy, and their credit books are a live read on the health of the patient. Ignore the trading-desk headline and read the reserve line.

The Private Credit Blind Spot

Here is the risk that does not show up cleanly on any single earnings line, and it is the one I would watch most closely. Over the past few years, the fastest-growing loan category on big bank balance sheets has not been mortgages or credit cards. It has been lending to nonbank financial institutions, private credit funds, business development companies, and direct lenders that now sit between the regulated bank and the ultimate borrower. Banks report these as loans to NDFIs. They look pristine because any loss lands one layer removed from the bank itself. That is precisely what makes them dangerous.

Private credit has ballooned into a multi-trillion-dollar market with a fraction of the disclosure of the syndicated loan market it replaced, and most of it has never been tested through a real default cycle. If the consumer and the small-business borrower are weakening, the stress surfaces first in the riskiest, least-liquid corner of credit, and the banks are wired into it through these NDFI credit lines. Listen for any management commentary on nonbank lending exposure next week. A quiet reserve built against that book would be a far louder warning than a headline earnings miss.

What Should Investors Do Now

So, as we head into next week, how should we position? First, do not trade the headline, but trade the setup. Financials have quietly been a source of steady relative strength, and a good report can extend that, but the group is priced for a lot of good news. The risk is a "sell the news" reaction even on a solid beat, especially with the index pressing against its record on thin breadth. Position accordingly.

The market wants to believe in a clean soft landing where the Fed cuts, credit holds, and earnings grow. Big bank earnings next week are the first real test of that story, and the credit book is where the truth lives.

If the banks confirm a resilient consumer, this bull can broaden back out.

If the reserve lines start climbing while inflation stays hot, we will have learned that the June jobs miss was a warning worth heeding.

Watch the footnotes closely. For a deeper look at the mean-reversion math behind stretched valuations, our recent work on mega-cap concentration risk pairs directly with this week's theme, and the Fed's Senior Loan Officer survey and the BLS inflation data are the two macro anchors that we will monitor our portfolio positioning around.

Trade accordingly.

🖊️ From Lance’s Desk

This week's #MacroView blog reexamines last year's analysis of the impact of AI buildout and capex spending on the US economy, and how productivity increases could help stabilize debt and deficit concerns.

Also Posted This Week:

• Are Flattening Curves And Style Rotations Deceptive Omens? - RIA - by Michael Lebowitz
• Margin Debt Risk: The Ratios That Mislead Investors - RIA - by Lance Roberts

📹 Watch & Listen

Markets remain trapped in a tight consolidation pattern, but the technical picture has not materially changed. The S&P 500 once again found support at the closely aligned 20- and 50-day moving averages, preserving the current buy signal as investors await a decisive breakout.

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📊 Market Statistics & Analysis

Weekly technical overview across key sectors, risk indicators, and market internals

💸 Market & Sector X-Ray: Market Gains Ground

Semiconductor stocks took a hit this past week as money rotated to other areas of the market with Discretionary, Industrials, Mag 7 stocks, and Communications catching some flows. Overall, Financials and Discretionary are very overbought, with Bonds, Technology (semiconductors) and Energy oversold.

📐 Technical Composite: 85.22 - Still Overbought

Even with the restart of the Iran conflict this past week, investors added to equity risk and push markets further into overbought territory. While not at more extreme levels, the market is overbought enough to potentially limit upside over modestly over the next few weeks.

🤑 Fear/Greed Index: 80.41 – Greed Remains Elevated

Despite a bit of volatility last week, with the restart of the Iran conflict, stocks gained ground as investors continued to increase equity exposure ahead of the start of earnings season.

🔁 Relative Factor Performance

The rotation between previous winners and losers continues. As shown the compression of factors has been evident in the increase in the Mag 7 stocks on a relative performance basis as Emerging Markets and Developed Markets (previous leaders) have reversed. That clustering will shake itself out sooner than later, and the opportunity will be in which factors start to take the lead.

📊 MFBR Index (Money Flow/Breadth Ratio Indicator): 60% = Buy Zone

NEW! MFBR Index: The Money Flow Breadth Ratio (MFBR) model is a rules-based equity allocation framework that uses weekly S&P 500 money flow data to generate buy, sell, and neutral signals. The MFBR systematically adjusts portfolio equity exposure in response to the direction and persistence of institutional capital flows. It aims to reduce drawdowns while capturing the majority of market upside.

"As of July 10, 2026, with the S&P 500 at 7,575.39, the Money Flow Breadth Ratio (MFBR) stands at 65% and rising. This places the indicator in BUY territory (60-70%), triggering a BUY signal. The prior week reading was 65%, representing a 5% increase over the trailing four weeks.

The model currently recommends HOLDING exposure at 92% down from 100% last week. The model remains long since April 17, 2026 (12 weeks). This reflects a FLOW-OVERLAY OVERRIDE: the trailing 4-week net dollar flow has swung sharply positive (>$300B) after a deeply negative prior 4 weeks, a historically strong contrarian buy signal."

📊 Sector Model & Risk Ranges

This past week Communications, Financials and Energy rallied outside of their historical monthly ranges. Most notably, Technology is now 20% above its long-term weekly mean which suggest some risk is building in that trade. The same goes for Small Caps and Emerging Markets which have primarily been a function of just Semiconductor, rather than a broad advance. Trade accordingly, take profits, and manage risk.

Have a great week.

Lance Roberts, CIO, RIA Advisors

The post Big Bank Earnings Kick Off Earnings Season appeared first on RIA.

The FOMC released the minutes from Chair Warsh's first meeting on Wednesday, and the best word to describe the Fed's advice is "ambiguous." Merriam-Webster defines ambiguous as a state or, in this case, a statement that allows for more than one interpretation.

Officials entertained policy scenarios in both hawkish and dovish ways.  Some see inflation easing enough to allow rate cuts, while others envision sustained price increases that would require rate hikes. Warsh billed the ambiguous internal debate as a "family fight" that ended with a unanimous vote to hold. The statement doesn't paint the picture of a committee marching lockstep toward a hike later this year. It is a committee uncertain about what comes next. Might this become the norm as they attempt to dissuade forward guidance?

Regarding inflation, the meeting participants judged that inflation would:

Remain elevated in the near term and then begin to decline as the effects of tariffs and energy price increases wane and other supply disruptions related to the closure of the Strait of Hormuz diminish.

Importantly, the risks to the inflation outlook, they noted, were "still tilted to the upside."

There was more ambiguity with the Feds outlook on AI-driven inflation and disinflation. The committee stated, "Ongoing strong demand for AI infrastructure would likely sustain upward pressure on prices for technology products and electricity." The AI buildout is a source of inflationary pressure, at least in the near term. However, Warsh and some other Fed members have also discussed the disinflationary benefits of AI-related productivity gains.

Given the ambiguous nature of the minutes, investors should watch the upcoming June CPI and PPI data, and then the July employment data, for policy clues. As we share below, the market assigns a 50% chance of a hike at the September meeting. Given the lack of visibility under Warsh, as we wrote in Forward Guidance R.I.P., the data will gain in importance and likely boost market volatility around key data releases.

What To Watch Today

Earnings

Economy

• No notable economic releases

Market Trading Update

Yesterday, discussed that both Volatility and Realized Volatility were hiding some fierce undercurrents. Today, bring that question down to the tape and ask the simpler version: who is actually buying these stocks? The S&P 500 sits near 7,534 as I write, roughly 1.5% under the June 2 record high of 7,620, and someone has to be lifting the offer to keep it there.

Start with the price. The index is holding about 1% above its 50-day average near 7,419 and about 8% above a still-rising 200-day average near 6,955. The 14-day RSI reads in the mid-50s, neither overbought nor washed out. This tape looks fine on the surface. The question is what’s underneath it.

Run through the buyers one at a time, and the picture gets thinner. Retail set records in May and pressed higher in June. Passive and ETF flows have pulled in better than a trillion dollars this year, running about 45% ahead of last year’s record pace.

Scott Rubner at Citadel Securities, who sees roughly a third of US retail order flow, has laid out that mechanical bid in detail, and I don’t argue with his map. But the same map shows the pillars starting to wobble. CTAs are already near the top of their range with little room to add. Pension plans sitting around 110% funded don’t press their luck; they de-risk into strength. And corporate buybacks, the most reliable buyer of all, go quiet as Q2 earnings season opens and companies slip into their blackout windows.

Notice in the chart above where the marginal buyer is fading. Over the past month, equal-weight (RSP) has actually edged past cap-weight, and small caps led again today. That’s a tentative broadening, and it’s welcome. But for the quarter, the cap-weighted index still beat the equal-weighted index by more than 2 points. The bid stays concentrated in a shrinking list of names.

Let me restate what we concluded yesterday, as it is appropriate still today.

None of this times a top. It does tell you the margin for error is thin. In our models, we’re holding equity at target weight rather than above it, keeping quality high, letting the cash buffer ride, and managing risk at our stops instead of chasing the tape. When the mechanical buyers step back, you want to be the one holding dry powder, not the one forced to sell.

One Rate Hike Rarely Means One Rate Hike

The ambiguity in Wednesday's minutes is deliberate and may be masking something the market is not fully pricing in. While the Feds debate was split, history offers an important lesson: once the Fed starts hiking rates, it rarely stops at just one.

Former St. Louis Fed President Jim Bullard stated it plainly.

"The committee does not generally do that. What's the point of one rate increase?

The Feds record supports his skepticism. Since 1990, the Fed has initiated five distinct tightening cycles. Not one ended after a single move.

• 1994: Seven hikes — Fed funds doubled from 3% to 6% in twelve months
• 1999: Four hikes over twelve months before the dot-com bust forced a reversal
• 2004: Seventeen consecutive hikes over two years from 1% to 5.25%
• 2015: Nine hikes spread over three years
• 2022: Eleven hikes, 525 basis points in sixteen months — the most aggressive cycle in forty years

Today's environment environemnt is a little unique as it's a supply-driven inflationary concern. The Fed's policies will have little influence on oil prices.

While the minutes were ambiguous, the historical playbook is not. If September brings the first hike, investors should be thinking about November and assessing whether the rate hike is temporary and a one-off move or the first in a series. If they hike, our bet is they hike once or twice and quickly reverse course once oil prices head lower again.

The graph below shows the correlation between oil prices and year-end Fed Funds expectations.

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The post The Feds Ambiguous Guidance appeared first on RIA.

Just over a year ago, I made the case that the deficit narrative would find its cure in artificial intelligence. Goldman Sachs has since published research that, on first reading, appears to refute. It isn't. But after more than thirty years of watching capex cycles play out, I've learned the right move when new data lands is to test the original argument against it. So far, that thesis from June 2025 holds. However, the AI capex risk profile has gotten sharper since then, and the argument needs tightening in a few places. The bull case and the tail risk are now the same buildout, but they are running in different directions.

The case I made last June rested on a straightforward chain. The deficit narrative was overstated. AI infrastructure would lift GDP. A higher denominator would stabilize debt-to-GDP. That chain still holds. However, Goldman's economics team, led by Elsie Peng, just published a careful look at how much of all this AI capex actually flows through to measured U.S. GDP, and the answer landed well below most published estimates.

The backdrop has also gotten messier. The BEA's second estimate revised Q1 2026 GDP growth down to 1.6% from the 2.0% advance estimate, with most of the downgrade attributable to inventory investment. Strip out the rebound in federal spending after the Q4 government shutdown, and core domestic demand looks softer than the headline. Middle East supply shocks, lingering tariff effects, and tighter immigration are all weighing on the consumer side. That backdrop turns AI capex risk from an academic question into a portfolio-management one. AI capex isn't just a contributor to growth. It's increasingly the entire growth story.

According to Goldman, AI-related spending will reach $800 billion annualized by year-end and contribute roughly 3.3 percentage points to "true" capital expenditure growth in 2026. So far, so consistent with the bull case. But here's where it gets interesting. When that capex gets translated into actual GDP growth, the bank estimates a contribution of just 0.3% on a "true" basis and 0.1% on a measured basis.

That's a small number. And it looks, at first glance, like a refutation of what I wrote in June. It isn't. The Goldman framework is mechanically correct for what it measures, yet badly incomplete for what matters most to the deficit thesis. As we have noted previously, the difference between mechanical accounting and economic reality lies in where the actual investment opportunity lies.

Why The Original Multiplier Was Too Generous

There are three things in the June piece I'd write differently today.

The first is the multiplier math. I used the American Society of Civil Engineers' estimate that every $1 billion in infrastructure investment generates roughly $3 billion in GDP over a decade, and applied it to the $1.8 trillion in committed AI infrastructure to estimate a cumulative GDP impact of $5 trillion. The ASCE figure is real and well-supported. But it was estimated for traditional public infrastructure: roads, bridges, transit, and water systems. Those projects carry near-100% domestic content. AI capex doesn't.

Goldman makes the point sharply. Much of the equipment in this buildout (servers, memory storage, advanced semiconductors, and some power transmission gear) gets sourced from Taiwan, Korea, and Japan. Those dollars leave U.S. shores at the point of equipment sale. They show up in those countries' export numbers, not in U.S. GDP. The structures portion (data centers, power facilities, transmission upgrades) does carry near-100% domestic content, but the equipment portion does not. So a blended multiplier closer to 2:1 is more defensible than the 3:1 figure I used.

This haircuts the original GDP math, of course, but it doesn't kill the thesis. Even at 2:1, $1.8 trillion of committed spending lifts cumulative GDP by roughly $3.6 trillion over a decade. The debt-to-GDP improvement is smaller than I projected, but the direction holds.

Productivity Is What Actually Cures Deficits

The second adjustment matters more. I underweighted productivity in the June piece. The line about "AI-driven productivity gains" appeared near the conclusion. It should have been the headline.

Make no mistake, capex is the visible, measurable, GDP-accounted-for portion of the AI story. That's what Goldman counts. That's what shows up in BEA tables. But the historical record on debt-to-GDP improvement is unambiguous. The periods where the ratio actually improved were periods of productivity acceleration, not periods of investment line growth.

Look at the post-World War II era. Then look at the 1990s tech boom. Both featured strong capex, of course, but the deficit improvement came from total factor productivity gains compounding through services, manufacturing efficiency, and labor output. The capex was the down payment. The productivity gains were the payoff.

That's why the bull case for AI's impact on the deficit isn't really about how many data centers get built. It's about whether AI adoption accelerates productivity across the economy in healthcare, in software development, in logistics, in financial intermediation, in professional services. Those gains compound. They don't suffer import leakage. And they're exactly what CBO projections systematically fail to model. The productivity lens also reframes the AI capex risk question. If adoption matures on time, the buildout pays off. If it doesn't, you're left holding a one-trick economy.

The Asymmetry In AI Capex Risk Is Wider Than The Framework Shows

Now we come to the part of the original piece that I'd weigh much more heavily today. The asymmetry between upside and downside is sharper than I gave it credit for, and it stems directly from the same understatement in the Goldman framework.

Goldman's 0.3% number captures direct investment lines but leaves out the domestic structures pass-through, the labor income flowing into PCE through construction workers and operators, the utility-side domestic capex, and the regional spillovers in concentrated data center geographies. A more inclusive accounting probably puts the AI footprint closer to 0.7% or 0.9% of GDP. Still not transformative, but materially larger than the headline implies.

Here's the catch. Those same components that get undercounted on the way up will absolutely show up on the way down. Goldman models a dot-com-style reversal scenario and estimates a drag of 0.2 to 0.4 percentage points on GDP. However, if the AI capex cycle rolls over for real, the structures, the labor, and the regional spillovers don't quietly vanish from the data. They contract violently. Construction trades lay off in waves. Utility capex gets stranded. Regional economies built around data center clusters take real damage all at once. The 0.2-to-0.4 figure is itself an understatement, for exactly the same reason Goldman's upside number is.

So the AI capex risk is wider than the framework shows. The understatement that masks the upside also masks how violent the downside could be. That's the part of the deficit-narrative argument that I want to put a sharper point on this time around. The bull case from June is intact. The tail risk has gotten louder.

What AI Capex Risk Means For Portfolios

The investment implications shift in a useful way. The original list of beneficiaries still holds: utilities, infrastructure plays, hyperscalers, and picks-and-shovels names like Caterpillar and United Rentals. But the framework for sizing those positions should change.

First, productivity adoption matters more than buildout exposure. Companies whose products embed AI into existing workflows and deliver measurable productivity gains to their customers will compound returns more durably than companies whose revenue depends on the next quarter of hyperscaler capex orders. The software and services layer is where the productivity story plays out over time. That's where I'd be willing to pay up.

Second, the buildout names still work, but treat them as cyclical exposures rather than secular ones. The 2000-2001 dot-com bust offers a real template for how fast capex revenue can contract when expectations turn. Position sizes should reflect that. As we have noted previously in our work on AI productivity and innovation, the timing question is harder than the direction question.

Third, watch the financing side closely. The current AI capex cycle is increasingly funded by debt and circular vendor-financing arrangements among hyperscalers, chipmakers, and data center developers. That's a different risk profile than capex funded by retained earnings. Goldman's research desk also flagged a labor bottleneck in May, with roughly 600,000 skilled trade openings against an apprentice pipeline of about 150,000 per year. So even if the capital is there, delivery timelines may slip. If financing conditions tighten or labor capacity caps the pace of the buildout, the capex reversal scenario gets pulled forward.

The bottom line is the thesis from June still holds, but the prescription is different. Bet on productivity adoption, not on capex multipliers alone. Stay diversified across the buildout's beneficiaries. And size positions for an asymmetric risk profile, because the same buildout that's driving 75% of GDP growth right now will cut the other way fast if it stops.

The Cure Is Still There, But It Lives In A Different Place

The June 2025 piece argued the deficit narrative had a cure in artificial intelligence. Just over a year on, I'd say the cure is still there, but it lives in productivity, not in spending lines. The prescription requires watching the AI capex cycle the way an emergency room watches a patient. You're looking for the signals that decide whether this becomes the recovery story or the next recession.

Importantly, neither outcome is foreordained. The capex cycle could roll on for another two or three years before adoption catches up to the buildout, in which case the productivity gains arrive on time and the debt-to-GDP trajectory bends in the right direction. Or capex expectations could break before adoption matures, in which case we get a violent unwind that takes a chunk of GDP with it. The setup right now contains both paths. Position accordingly.

Sources & References

1. U.S. Bureau of Economic Analysis, "GDP Second Estimate, 1st Quarter 2026," released May 28, 2026. bea.gov. Third estimate scheduled for release June 25, 2026.
2. Goldman Sachs Economics Research, "AI Capex and the GDP Math," analysis by Elsie Peng and team, May 2026.
3. Goldman Sachs Research, "AI buildout labor bottleneck," May 13, 2026, on skilled trade capacity constraints through 2027-2028.
4. Bureau of Labor Statistics, "Productivity and Costs, First Quarter 2026, Revised," USDL 26-0785, June 4, 2026. bls.gov.
5. American Society of Civil Engineers, "Failure to Act: Economic Impacts of Infrastructure Investment Gaps," ASCE Infrastructure Economic Report Series.
6. McKinsey & Company, "The economic potential of generative AI," industry capex projection through 2030.
7. Congressional Budget Office, "The Budget and Economic Outlook," historical projection accuracy and methodology notes.
8. Federal Reserve Bank of St. Louis (FRED), historical federal debt-to-GDP series.
9. Roberts, L. "The Deficit Narrative May Find Its Cure In Artificial Intelligence," RIA Advisors, June 2025.
10. Roberts, L. "AI Productivity And Innovation: Prosperity Or Engels Pause?" RIA Advisors, May 2026.
11. Roberts, L. "AI Productivity, Employment and UBI" RIA Advisors, January 2026

The post AI Capex Risk Cuts Both Ways In The American Economy appeared first on RIA.

Goldman Sachs's volatility desk made the following comment: "With the VIX back to its lowest levels in more than a month, our Vol desk is focused on hedging opportunities as 1-month S&P implied correlation is near its lowest level in 20 years."  Simply, a low VIX can convey a sense of market calm on the surface, yet implied correlation tells a different story.

The VIX, based on option trading data, measures the implied volatility of the S&P 500 index. A low VIX means traders expect the market to be relatively calm with not much volatility. Conversely, a higher VIX reflects expectations for high levels of volatility. Today, the VIX is relatively low at 17, as S&P 500 index option trades appear complacent.

Implied correlation measures how much S&P 500 stocks are expected to move together. When implied correlation is high, as it was during COVID, the 2022 interest rate shock, and more recently at the beginning of the Iran conflict, macro forces dominate trading activity, and stocks tend to go up or down together. When correlation is low, stocks decouple. Individual company fundamentals, technical setups, and momentum chasing drive returns. As we see in the chart below, the implied correlation is at a 20-year low.

The low VIX implies smooth sailing ahead, while a record-low implied correlation suggests the market could be at risk. Goldman is hedging the risk of a correction, i.e., an implied correlation spike. Often, when implied correlation rises sharply from extreme lows, as it did in August 2024 during the yen carry trade unwind, the divergences that kept the index calm disappear. Stocks start moving together again, and most of the time they move down. This condition is not a warning to expect a market downdraft, but it does suggest that risk awareness is critical.  

What To Watch Today

Earnings

Economy

Market Trading Update

Yesterday, we walked through how the dollar narrative flipped from collapse to strength. Today, I want to add to Michael's commentary above and focus on volatility and positioning side by side, because together they describe a tape priced for calm, even as almost everyone is already long. That's the setup that tends to bite.

Start with the volatility complex. The VIX closed Tuesday at 15.57 and popped back toward 16 on Wednesday as oil jumped and headlines about the Iran ceasefire returned. A 16 handle looks tame on its own. The tell sits underneath it. Twenty-day realized volatility on the S&P 500 has nearly doubled since early June, climbing from under 9 to the mid-teens and brushing 18 last week. So implied vol isn't sitting comfortably above what the market is actually delivering anymore. On Tuesday, it even printed a hair below realized, which almost never happens outside of stress. The cushion option sellers count on, the gap between implied and realized, has compressed to almost nothing.

That changes the math for the crowd that's been short volatility and long everything. When implied runs well above realized, selling vol pays you to wait. When the two converge, you're collecting pennies with no margin for a surprise. And the surprises are stacking up, from oil to the Iran deal back in doubt to the first real Q2 earnings prints.

Now layer positioning on top. The NAAIM Exposure Index, which tracks how invested active managers actually are, hit 98.6 in late June and still sat near 85 into July. That's NOT cash on the sidelines waiting to buy a dip. That's money already committed. The BofA Fund Manager Survey pushed equity allocation to its most overweight since early 2022 this spring, close to Michael Hartnett's contrarian sell trigger.

None of this is a sell signal. It's a risk-management signal, and the difference matters. We've written for weeks that this is a tape driven by positioning more than fundamentals, and nothing this week changes that.

In our Equity models, we haven't chased the tape. We previously trimmed the most stretched winners back toward their target weights, lifted quality, and kept the cash buffer rather than spending it in a crowded, low-premium market. If volatility stays this cheap relative to what stocks are actually doing, that's your cue to buy protection while it's still on sale, not to add risk. Manage the position before the crowd tries to leave through the same door. Trade accordingly.

Iran: Oil, Gold, And Bonds

Yesterday, President Trump told reporters that he considers the US-Iran ceasefire "over," after Iran struck American bases in Bahrain and Kuwait following renewed US strikes. Crude oil jumped on the headline, now trading near $74/bbl, up from the mid- to upper-$60s last week.

Textbook logic says gold should be rallying alongside oil due to a war premium, inflation risk, and safe-haven bid. Despite what "logic" may expect, gold has had a negative correlation with oil prices since the war started. Bond yields, on the other hand, are positively correlated with oil prices as inflation concerns dominate bond trading. The 10-year Treasury yield has climbed by nearly 15 basis points from a week ago. We think the confusing gold trade can be explained by the rational bond trade.

We discussed the recent disconnect in gold prices in "Gold Investors Are Likely Confused." To wit:

As we have quantified in numerous articles, gold prices often have a strong negative correlation with real rates. High real rates, denoting a hawkish, restrictive monetary policy, typically correlate with lower gold prices. Conversely, low to negative real rates point to easy policy and are usually friendly to gold investors. The relationship stopped working for the last two years. With real rates remaining high and the Fed moving to a more hawkish stance, might the historical correlation be reasserting itself? Might gold investors be betting on a hawkish Fed?

Gold's decoupling from war headlines isn't irrational; it reflects rising real rates. When nominal yields rise faster than inflation expectations, real yields rise, which raises the opportunity cost of holding a non-yielding asset like gold. Oil-driven inflation fears are pushing yields higher, while inflation expectations stay reasonably anchored. Gold, which should theoretically benefit from the same inflation fear, is instead punished by the widening gap between yields and inflation expectations.

The graph below shows that the relationship that matters for gold holders is not between oil and gold, but between gold and 10-year yields. Our advice: watch real yields, not war headlines, for the next move in gold.

Are Flattening Curves And Fierce Style Rotations A Deceptive Omen?

Bond market pundits often warn that bear yield curve flatteners or inverted yield curves ultimately lead to recessions. Similarly, some equity experts caution that periods of violent back-and-forth rotations among stock sectors and/or style factors are precursors to a market top.  Additionally, the combination of a bearish flattening trend and volatile equity rotations leads some analysts to forecast a recession, with concerning market repercussions.  

The argument we present in this article is that predicting economic or financial market activity is not as simple as following two indicators. Bear flattening trades, inverted yield curves, and frantic style (factor or sector) rotations are not definitive warnings of a market peak. They are extremely informative about where the economy, markets, and investor sentiment stand, but they do not tell investors whether or when the economic or market cycle will turn. Knowing where you are in a cycle is not the same as knowing when it ends. Confusing the two is a common mistake and can be a costly one for investors in late-cycle analysis.

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Michael Howell, founder of CrossBorder Capital, is one of the most followed global liquidity analysts. Howell's Global Liquidity Index (GLI) often tracks closely to a 65-month sine-wave cycle that has tracked liquidity conditions well since 1965. As we share below, the 65- month cycle (green) bottomed in October 2022 and peaked in August 2025, exactly where his GLI (blue) predicted it would. Also shown, the Chicago Fed National Financial Conditions index (NFCI- orange) tends to align with the cycle and the GLI.

While there are many definitions of liquidity, Howell considers it the ability and willingness of credit providers to lend. His GLI captures factors such as central bank reserve injections, the US Treasury General Account (TGA) balances, cross-border capital flows, repo market conditions, collateral availability, and the dollar's strength. Importantly, about three-quarters of all credit market transactions are estimated to be debt rollovers rather than new borrowing. Thus, measuring how easily and cheaply maturing debt can be refinanced is an important gauge of global liquidity.

The cycle is now pointing down into 2027. Howell projects $40 trillion in global debt rollovers by 2027, a $4 trillion increase from the previous year.  That borrowing demand comes as liquidity contracts, creating a mismatch between refinancing demand and tightening financial conditions. Per his work, commodities, including gold, long-duration government bonds, cash, and defensive equities, tend to be among the best performers when the liquidity cycle falls. Conversely, more speculative and often leveraged assets such as crypto, small-cap stocks, emerging-market stocks, and private credit and equity tend to be among the worst performers.

What To Watch Today

Earnings

• No earnings reports today

Economy

Market Trading Update

Yesterday, we covered Kevin Warsh using his Sintra debut to bury forward guidance, Forward Guidance: R.I.P. Today, back to a risk building quietly underneath a record tape. Leverage. Monday's piece walked through which margin-debt gauges actually matter, and now the plumbing under that leverage has changed.

Start with the size of it. Margin debt hit a record $1.42 trillion in May, up 8.5% in a single month and better than 53% from a year ago. The dollar level always prints records in a bull market, so the level alone tells you little. The rate of change does not. A 53% annual jump is near the pace that outpaced the 2000, 2007, and 2021 tops.

The other side of the ledger looks worse. The net credit balance, investor cash minus margin debt, sank to a record negative $991.7 billion in May. That is the thinnest cushion against forced selling on record, when a year ago it sat at negative $557 billion. Put simply, investors have never owed this much against the cash they actually hold.

Now, the change most investors missed. On June 4, FINRA scrapped the $25,000 pattern day trader minimum and the trade count, swapping them for a real-time intraday margin system. The old $2,000 floor to open a margin account still stands. The honest read is that the prior rule was a blunt wealth gate, and the new one is more risk-sensitive on paper. But the effect at a cycle peak is what counts. It lifts a brake on leveraged intraday trading for the smallest, most active accounts, and firms have until October 2027 to build the real-time monitoring meant to replace it. That does NOT cut leverage in the system. It lowers the friction on adding more, right when confidence runs highest.

So here is the setup. Records on the screen, a record on the margin ledger, the thinnest cash cushion ever, and a rule that just made piling on easier. None of this times a market top. Margin debt tells you how much fuel is in the room, not when it lights.

What it does tell you is the size of the air pocket if sentiment turns, because leverage cuts both ways. We are holding equity exposure at target weight rather than above it, keeping quality high and dry powder ready, and managing risk at our stops instead of chasing the tape. Know how much of your own gain is borrowed before the market asks the question for you.

The First Half Chip Rally Reversal

Many semiconductor and computer hardware stocks posted extraordinary first-half gains this year. For instance, Micron was up more than 260% through June, SanDisk was up by over 850%, and the broader semiconductor ETF SOXX had gained over 75% in the first half of 2026. That trade appears to be reversing. Interestingly, some blame Broadcom's earnings announcement, in which its CEO chose not to raise the full-year AI semiconductor outlook. The truth is that the stocks had priced in so much future growth and were so grossly extended that any bit of bad news could have burst that bubble. Moreover, as we share in the Tweet of the Day, the massive profits and high margins in chip manufacturing and design will attract competition. We are already seeing that break the narrative.

Three forces are simultaneously driving the reversal: profit-taking after parabolic gains, valuation reality setting in as guidance stops beating expectations, and a broader market rotation back into value stocks and perhaps the hyperscalers. To wit, Jeff Kilburg of KKM Financial noted:

"The Great Rotation trade persists into Q3 as the blue boring names of the Dow Jones continue to attract inflows directly from recent profit-taking money from tech stocks."

The bottom line is that this is not a fundamental collapse. It is what happens when stocks are priced for perfection for 2028-2029 earnings in 2026.

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Bond market pundits often warn that bear yield curve flatteners or inverted yield curves ultimately lead to recessions. Similarly, some equity experts caution that periods of violent back-and-forth rotations among stock sectors and/or style factors are precursors to a market top.  Additionally, the combination of a bearish flattening trend and volatile equity rotations leads some analysts to forecast a recession, with concerning market repercussions.  

The argument we present in this article is that predicting economic or financial market activity is not as simple as following two indicators. Bear flattening trades, inverted yield curves, and frantic style (factor or sector) rotations are not definitive warnings of a market peak. They are extremely informative about where the economy, markets, and investor sentiment stand, but they do not tell investors whether or when the economic or market cycle will turn. Knowing where you are in a cycle is not the same as knowing when it ends. Confusing the two is a common mistake and can be a costly one for investors in late-cycle analysis.

Given that both indicators are currently flashing red, we explore how they can serve as important warnings of pending financial market and economic turbulence, but also as deceptive omens.

What The Yield Curve Tells Us

The shape of the yield curve, or the difference in yields between long and short-term US Treasury securities, indicates the market's expected path for short rates plus a term premium. In other words, where does the market expect Fed Funds to be in the future, plus how much of a yield premium is the market paying investors to take on the inflation, economic, and oversupply risks of holding Treasury securities?

To help appreciate where the yield curve stands today and how it's changed recently, we've included the graph below.

A notable feature of this long-term graph is that every time the yield curve flattened and inverted, i.e., the 2-year yield rose above the 10-year yield (the blue line fell below 0 on the y-axis), a recession (gray) followed. There is one exception. In 2022, the curve flattened, inverted, and then steepened, yet a recession has not materialized. 

Current Yield Curve Flattening

Recently, the yield curve has been flattening (declining) while bond yields have risen. In bond market parlance, that is called a bear market flattener (higher yields and a flattening yield curve). The table below shows that since late February, when the Iran conflict started, the 2-year note has risen by 76 basis points, the 10-year note by 46 basis points, and the 30-year bond by only 25 basis points. As a result, the 2/10-year yield curve flattened by 30 basis points and the 2/30-year curve by 51 basis points.

A bear flattening is the result of investors raising their collective expectations for higher short-term rates. This can be due to strong economic growth expectations and/or higher prices. At the same time, longer-maturity yields are less responsive, likely due to a subdued long-run growth forecast or a belief that higher inflation is temporary.

The flattening or inversion of the yield curve creates more restrictive financial conditions, acting as a brake on economic activity. An economy that warrants slowing is often one that is late in its economic cycle.

When the long-maturity yield falls below the short-maturity yield, i.e., it inverts, the usual interpretation is that investors expect future rate cuts because policy and/or rates are restrictive enough that the central bank will have to reverse course. However, that definition fails to consider the term premium, the compensation investors demand for holding longer-duration notes and bonds. A curve can flatten or even be inverted because the market expects rate cuts and/or because the term premium has compressed toward zero. Thus, it's not definitive whether an inverted curve is due to expected rate cuts, well-anchored inflation, or forecasts of an economic downturn.

Equity Rotations

Equity leadership can be a tell of similar concerns, but through a different mechanism. Stocks are claims on future corporate cash flows, and those claims have duration. For instance, growth companies tend to have minimal cash flows or even run losses in the near term, but expectations are for large and growing earnings in the future. Thus, valuations for growth companies are based on distant-future cash flows and, accordingly, have a long duration.

Conversely, value companies generate cash flows that are nearer and more certain and are therefore considered to have shorter durations. When short-term interest rates rise and uncertainty about the future increases, the present value of distant cash flows is marked down far more than that of near cash flows.

For example, the 1-year present value of $100 at a 5% discount rate is $95.24, and at a 4% discount rate, it's $96.15. The 1% change in rates impacts the present value by $0.91. Conversely, the 10-year present value of $100 at 5% and 4% is $61.39 and $67.56, respectively, resulting in a difference of $6.17 for the 1% change in rates. Accordingly, valuation multiples of growth companies tend to compress relative to those of value companies.

As we share below, in a hypothetical example, the value of the future cash flows of a value company with more upfront cash flows declines less with a 3% increase in the discount rate than that of a growth firm with more cash flows expected in the distant future.

A growth-to-value rotation is the equity market's version of the yield curve flattening: both are duration-related repricings driven by the same change in the cost of money.

When Rotations Become Volatile

Typically, equity rotations in a late-cycle market become more volatile. In other words, no style or sector leads or lags for long stretches. These rapid rotations help clue us into a market regime that is becoming contested or changing.

Through the middle of an expansion, the macro picture is often clear with trend growth, accommodative or neutral monetary policy, and a steady discount rate. Because the regime is stable, leadership often remains in place for long periods as investor capital concentrates on the companies that benefit most from prevailing conditions. However, the market regime becomes challenged as changes in the broad economic and market environment are anticipated. Investors start asking questions such as:

• Is monetary policy changing?
• Is growth decelerating or reaccelerating?
• Is inflation sticky or transitory?

As new economic and corporate data feed into the market, the discount rate becomes more sensitive. The market is forced to continually toy with its assumptions, and leadership ping-pongs as a result.

The volatility of style leadership is a proxy for regime uncertainty. The whipsaw action itself, not necessarily which types of stocks lead or lag, is the tell. A market that cannot decide between value and growth is a market that cannot decide what the discount rate will be, which is to say, a market that senses the regime is changing beneath it.

False Signals

There is a complication with what we have presented. The yield curve can be distorted by forces unrelated to the business cycle, such as shifts in the bond term premium, large-scale asset purchases (QE) or their reversal (QT), and significant government bond supply.  Equity rotations are at times heavily influenced by momentum chases and bouts of speculative behavior. Moreover, the rise of passive investment strategies tends to accentuate momentum trends.

When other factors influence the yield curve or the volatility of equity rotations, the "forecast" embedded in the curve and rotations becomes muddied and can falsely signal a market and economic top.

Condition And Timing Indicators

This brings us to the distinction that should govern how the signals are used. There is a difference between a condition indicator and a timing indicator. A condition indicator describes the economic and market landscape. A timing indicator tells you when the next event arrives. Flat curves and unstable leadership are good indicators of conditions, but can make for poor timing indicators.

This concept is like weather forecasting. A falling barometer tells you the atmosphere favors a change in the weather, likely a storm. It does not tell you what day or time the storm will arrive. In fact, despite the drop in barometric pressure, the storm may never form. Reading a barometer as a surefire countdown clock to a storm is an error, no matter how reliably storms and falling pressure correlate.

Summary

If you cannot extract a time frame for an economic and market peak from these signals, then what purpose do they serve?

The answer is that they help us prepare for a widening series of potential outcomes. Today, for instance, with the yield curve flattening and a series of violent rotations, we are maintaining stricter stop-loss levels, paying closer attention to technical analysis, focusing on our SimpleVisor rotation analysis tools, and assessing our risk more frequently.

The signals suggest the regime may be changing, and we should be prepared for that possibility. However, until that becomes more evident, we must take advantage of what the market has to offer. 

The post Are Flattening Curves And Style Rotations Deceptive Omens? appeared first on RIA.