Bruce Murray’s Top Picks for June 30, 2026
Tuesday, June 30, 2026
Tuesday, June 23, 2026
Technology-Driven Growth Industries over the Past Two Centuries
Technology-Driven Growth Industries over the Past Two Centuries
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If you look at technology-driven growth industries over the past two centuries - steam engines, railroads, telephony, electric power, the Internet - people become too excited about growth and overinvest in it. When the bubbles burst, markets overcorrect on the downside, even though the fundamental growth drivers may still be as present as they were before...How might this apply to the current market of AI hysteria?
You have laid out the classic, immutable template of the technological deployment cycle. Whether it’s the British "Railway Mania" of the 1840s or the telecom/fiber-optic buildout of the late 1990s, the human psychology driving capital markets never changes.
Carlota Perez, a renowned techno-economist, formalized this exact pattern into two distinct phases: the Installation Period (where financial capital drives a frantic, speculative frenzy and overbuilds the physical infrastructure) and the Deployment Period (where production capital takes over, the technology becomes a boring utility, and the actual productivity gains embed themselves into the broader economy).
Looking at the current landscape of AI hysteria through this structural lens, we can map out exactly where the structural overinvestments are occurring, what the "bust" looks like, and how the fundamental growth drivers will survive the inevitable downside overcorrection.
1. The Asymmetry of the Current Buildout
The sheer scale of the current capital expenditure (CapEx) is historically unprecedented.
The core of the current hysteria lies in a massive revenue mismatch:
The Supply Side: Trillions of dollars are being committed to long-term physical infrastructure buildouts over the next five years.
The Demand Side: Current annualized revenues generated directly from AI software and enterprise applications are estimated at a fraction of that cost (roughly $80 to $150 billion).
This creates an intense structural asymmetry. The hyperscalers are locked in a classic Nash Equilibrium prisoner's dilemma: they cannot afford to stop buying chips and building data centers because falling behind in the intelligence race means structural obsolescence, even if the current return on investment (ROI) doesn't justify the spend.
2. What the "AI Underwrite" Correction Will Look Like
When markets realize that the software monetization curve is lagging far behind the hardware CapEx curve, a sharp valuation compression—a "healthy" or perhaps brutal overcorrection—is inevitable.
In a standard historical tech bust, the pain follows a specific waterfall effect:
[ Phase 1: The Revenue Reality Check ] Hyperscalers signal a flattening of CapEx because enterprise software adoption takes longer than expected.
[ Phase 2: The Hardware Crud ] The "picks and shovels" providers (chipmakers, server assemblers, specialized cooling) see demand drop off a cliff. Valuations priced at >30x Price-to-Sales collapse violently.
[ Phase 3: Financial Contagion in Private Credit ] A massive chunk of modern data center construction is funded by private credit and asset-backed debt. As project timelines stretch and secondary market chip prices drop, junk-rated data center bonds face distress.
When this bubble bursts, the market will almost certainly overcorrect to the downside. The financial press will declare AI a "fad," tech stocks will bleed indiscriminately, and the general public will sour on the entire concept.
3. The Institutional Post-Burst Reality (The "Deployment" Phase)
This brings us to the core of your point: the fundamental growth drivers will still be present.
When the railroad bubble burst in the 1840s, the track didn't vanish into thin air; it just changed hands from bankrupt speculators to disciplined operators who ran trains on it at pennies on the dollar, completely transforming global commerce. When the dot-com bubble burst, the thousands of miles of "dark fiber" laid by WorldCom and Global Crossing remained in the ground, ultimately lowering bandwidth costs so precipitously that it paved the way for Netflix, YouTube, and the modern cloud economy.
If and when the AI market overcorrects, the physical reality left behind will be profoundly deflationary and highly productive:
Stranded, Hyper-Advanced Infrastructure: The world will be left with an astonishing abundance of hyper-dense data centers, next-generation electrical grid connections, and warehouses full of high-end silicon.
The Reallocation of Compute: The cost of running advanced machine learning models will collapse. Startups and enterprise incumbents who couldn't afford $100,000 clusters during the hype phase will suddenly inherit a deeply discounted, highly accessible utility.
The Productivity Paradox Solved: True economic productivity gains lag technological introduction by years. Businesses require time to re-engineer workflows, retrain staff, and restructure management. The post-bubble period is precisely when companies stop treating AI as a boardroom buzzword and start quietly integrating it to drive real cash-flow margins.
The Investor’s Takeaway
For a fundamental investor focused on quality and a margin of safety, the current market demands a strict distinction between merely owning a narrative versus owning durable, cash-generative economic moats.
The current hysteria has priced many "picks-and-shovels" businesses as if hyper-growth will continue linearly forever. History guarantees it won't. But history also guarantees that the wreckage of the bust will provide the exact foundation upon which the true, long-term AI-driven economy will be built.
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Source
Google Gemini
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Postscript
What makes tracking these cycles so compelling is that human psychology remains the ultimate constant. No matter how advanced the technology becomes—whether we are talking about steam pressure or neural networks—the financial architecture of booms, busts, and the quiet, productive eras that follow, human nature will continue to shape the contours of what follows.
Monday, June 22, 2026
AI buildout gives tech investors new reasons to watch bond market
AI buildout gives tech investors new reasons to watch bond market
Key Points
- Tech giants are depleting reserves and leveraging debt in their ambitious data center buildouts.
- That’s making the group much more exposed to the cost of borrowing and giving tech investors reason to pay attention to the Fed.
- “Tech investors are learning what it’s like to be an investor in old-economy industrial businesses,” said Peter Boockvar, chief investment officer of One Point BFG Wealth Partners.
Artificial intelligence is giving tech investors an entirely new reason to pay attention to the Federal Reserve.
For years, mega-cap tech companies with hefty balance sheets have been able to shrug off rising rates, which tend to weigh more heavily on smaller, less-profitable peers.
But companies that were once cash cows are depleting reserves and leveraging debt in their ambitious data center buildouts. That’s making the group much more exposed to the cost of borrowing.
“Tech investors are not as used to looking at rates,” Peter Boockvar, chief investment officer of One Point BFG Wealth Partners, said in an interview. “All of a sudden tech investors need to listen to what Kevin Warsh has to say, they need to start paying attention to what the inflation stats are and how the U.S. Treasury market responds to it.”
Warsh held his first press conference as Fed chairman on Wednesday. The central bank indicated the possibility of a rate hike in 2026, which sparked a sell-off in equities and an increase in rates. The 10-year yield is trading near 4.45%.
Higher rates have always had an outsized impact on smaller tech companies, as investors value them based on future profits. When yields spike and the so-called “risk-free rate” rises, investors discount future cash flows, making them worth less today.
The effect of rising rates is now moving upstream. That’s because tech’s hyper-scalers are engaged in a high-speed race to build out AI infrastructure, with Amazon, Alphabet, Microsoft and Meta projected to deploy a combined $750 billion this year, up more than 80% from 2025.
The Amazon Web Services IAD10 data center in Sterling, Virginia, US, on Sunday, May 31, 2026. NextEra Energy Inc. agreed to pay about $67 billion in
Lexi Critchett | Bloomberg | Getty Images
A big piece of that expansion is being funded by debt, which becomes a more difficult sell if rates are rising. Nvidia, Oracle, Amazon, Alphabet and Meta are turning to the debt market to the tune of tens of billions of dollars each.
OpenAI CFO Sarah Friar has pointed to an ability to leverage debt markets as one motivation to go public. Reuters reported on Thursday, citing two sources familiar with the matter, that bankers for SpaceX, which debuted on the Nasdaq last week, are preparing to meet investors about a bond offering of at least $20 billion.
“It’s underappreciated,” said Jeff Kilburg, CEO of KKM Financial, adding that there’s an “insatiable demand” for AI-related funding. “Tech leadership is embracing debt. It’s the perfect recipe for these AI folks who feel comfortable in what they want to borrow, and spend.”
Dwindling free cash flow
Tech giants need the money as some of them deplete their cash reserves they’ve spent years building up. Goldman Sachs recently noted that capex as a percentage of cash flow is at the highest level since the dot-com era. The firm also expects that capex this year will be closer to $920 billion, and says analyst estimates have been “too conservative” each of the past three years.
Amazon, which has forecast spending of roughly $200 billion this year, is widely expected to see negative free cash flow.
“Tech investors are learning what it’s like to be an investor in old-economy industrial businesses that are capital intensive,” Boockvar said. “Free cash flow is volatile and access to both debt and equity markets are crucial in order to finance it all.”
Issuing debt can be a deliberate strategy. It can preserve liquidity for acquisitions while bringing flexibility when it comes to financing long-term buildouts.
Jay Woods, chief market strategist at Freedom Capital Markets, is assessing the debt risk based on each individual company, not the sector as a whole. Nvidia, for example, is in a strong cash position, with free cash flow jumping past $48.5 billion in the latest quarter, up from $26.1 billion a year earlier.
“They still have a deep cash bench, so I don’t think it’s that big of a red flag,” Woods said about Nvidia. “It does give them flexibility.”
-- CNBC’S Drew Troast contributed reporting.
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Source
https://www.cnbc.com/2026/06/20/ai-buildout-giving-tech-investors-new-reasons-to-watch-bond-market.html
Sunday, June 21, 2026
Canadian Economy...Banking regulator lowers capital levels to spur more loans at ‘hinge moment’ for the economy
Canadian Economy...Banking regulator lowers capital levels to spur more loans at ‘hinge moment’ for the economy
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Canada’s banking regulator, the Office of the Superintendent of Financial Institutions (OSFI), has lowered the Domestic Stability Buffer (DSB) for the country's six largest banks to 3% from 3.5%, effective June 19, 2026.
This decision, the first reduction in three years, aims to free up approximately $74 billion in excess capital, enabling banks to extend up to $673 billion in additional risk-weighted assets to support defense spending, critical infrastructure, and artificial intelligence projects.
Key Details of the Policy Shift
Buffer Adjustment: The DSB range was also narrowed from 0–4% to 0–3%, signaling regulatory confidence in the financial system's resilience during a period of geopolitical and trade uncertainty.
Strategic Goal: Superintendent Peter Routledge described the move as a proactive measure to help the economy adapt to a "hinge moment" of structural change, encouraging banks to deploy capital rather than hold it as a precautionary reserve.
Impact on Banks: The adjustment lowers the Common Equity Tier 1 (CET1) ratio requirement to 11% from 11.5%, though major lenders currently maintain an average ratio of 13.5%, providing a significant cushion above the new minimum.
Market Reaction: While intended to spur lending, analysts note that increased credit availability ultimately depends on pent-up demand for commercial loans and the approval of nation-building projects, with Bank of Montreal and National Bank of Canada potentially benefiting most due to their higher commercial loan portfolios.
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'Canada’s banking regulator, the Office of the Superintendent of Financial Institutions (OSFI), has lowered the Domestic Stability Buffer (DSB) for the country's six largest banks to 3% from 3.5%, effective June 19, 2026.
This decision, the first reduction in three years, aims to free up approximately $74 billion in excess capital, enabling banks to extend up to $673 billion in additional risk-weighted assets to support defense spending, critical infrastructure, and artificial intelligence projects'...What might be some of the ramifications of this move?
OSFI’s decision to cut the Domestic Stability Buffer (DSB) to 3.0% is a fascinating, proactive regulatory pivot. For context, the DSB is the rainy-day capital insurance policy that Canada’s Big Six banks are forced to hold to absorb systemic shocks.
By lowering the buffer, OSFI isn't acting out of a sense of economic panic. Instead, they are signaling that the banking sector is exceptionally well-capitalized—with average Common Equity Tier 1 (CET1) ratios sitting robustly around 13.5%, well above the new 11.0% regulatory floor.
However, freeing up $74 billion in regulatory capital—which translates mathematically to roughly $673 billion in capacity for new risk-weighted commercial loans—creates ripples across several areas.
1. The Loan Demand Challenge: A "Pushing on a String" Dilemma
The most critical immediate question is whether businesses actually want to borrow this money.
The Policy Goal: OSFI and the federal government want this capital diverted into high-productivity, nation-building avenues: critical infrastructure, domestic defense, natural resources, and artificial intelligence.
The Reality Check: Regulators can expand the supply of credit, but they cannot manufacture the business confidence required to ignite credit demand.
For this move to truly benefit the broader Canadian economy, the public and private sectors must rapidly develop "bankable," high-yield commercial projects. If corporate confidence remains subdued, that credit capacity will just sit idle on balance sheets.
2. Capital Allocation: Commercial Loans vs. Share Buybacks
Because banks are ultimately accountable to shareholders, they will not let idle capital sit unproductive indefinitely. If loan demand in the target sectors fails to materialize over the coming quarters, executive teams will face massive pressure to return that excess capital to investors.
The Capital Management Pivot: We could see a significant wave of share buybacks or dividend hikes.
Market Perception: While buybacks would provide a tailwind for bank equity prices (which have already been outperforming over the last year), it would signal to the market that organic credit growth is weak.
OSFI has clearly stated they anticipate this capital will be used for economic structural change, making heavy buybacks a potential point of political or regulatory friction.
3. Shift in Risk Profiling
By explicitly pointing the banks toward infrastructure, defense, and AI, OSFI is encouraging a migration toward longer-duration and structurally complex corporate assets. This alters the risk profile of the banks' loan books:
The Trade-off: Historically, Canadian banks have been anchored heavily by residential real estate lending. Moving deeper into large-scale commercial, technological, and infrastructure underwriting requires highly specialized risk management.
The Security Blanket: OSFI’s narrowing of the buffer's future range (now 0% to 3%, down from 0% to 4%) acts as a psychological anchor.
It signals to the banks that this lower capital requirement is a structural fixture for the foreseeable future, giving them the long-term regulatory visibility needed to underwrite projects that take years to pay off.
4. A Cushion Against Macro Vulnerabilities
The domestic Canadian consumer remains highly leveraged, and while mortgage delinquencies and credit losses have stabilized within normal ranges, household debt-to-income ratios are still structurally elevated.
By lowering the buffer now during a period of relative macro stability, OSFI is betting that the remaining 3% buffer—combined with the banks' organic internal capital generation—is more than enough of a safety net.
It is a calculated trade-off: accepting marginally less systemic insurance in exchange for a potentially massive economic catalyst.
Ultimately, this move hands the ball squarely to the banks and the corporate sector.
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Source
Google Gemini
Wednesday, June 10, 2026
The Current State of the Markets
The Current State of the Markets
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How does the New High-Low Index look like on the NYSE?
(New Highs / (New Highs + New Lows)) * 100
The High-Low (H-L) Index on the NYSE provides a raw, unfiltered picture of structural market tops. While Justin Mamis focused heavily on "listening to the tape" for subtle shifts in leadership, the High-Low Index—traditionally calculated as a 10-day moving average of the High-Low Ratio—is the mathematical confirmation of his theories.
When plotted as a smooth index (usually between 0 and 100), it reveals the ultimate battle between the "Generals" and the "Soldiers."
1. The Anatomy of a High-Low Top
In a booming, healthy bull market, the High-Low Index pins itself consistently above 80, and often spikes near 90. This means that out of all the stocks making extreme 52-week moves, the vast majority are expansionary new highs.
When a Mamis-style distribution top forms, the High-Low Index behaves like a leading indicator, executing a highly specific structural breakdown:
The "Subsurface Divergence"
This is the holy grail of top-spotting using this tool. As the broader index makes a spectacular new record high, the High-Low Index fails to confirm it. Instead, it slopes dramatically downward, often slipping below 70.
What it means: Even though the headline index looks invincible, the pool of stocks driving it to new heights has shrunk dramatically.
The Silent Expansion of Lows: More importantly, it reveals that beneath the surface, individual companies have rolled over so severely that they are starting to hit 52-week lows simultaneously while the index hits a 52-week high. On a single-day basis, you will see days where the S&P or Dow is flat to positive, but the absolute number of New Lows on the NYSE starts outnumbering New Highs.
2. Crossing the 50 Line: The "First Break"
In Mamis’s framework, the "First Break" is the moment the market takes a sharp hit, which the complacent crowd assumes is just another healthy buying opportunity.
Quantifying this through the High-Low Index is simple: a decisive drop below the 50 mark.
When the index falls below 50, it means new 52-week lows have officially taken control of the NYSE universe. From a momentum perspective, the internal mechanics of the market have inverted. The "strong hands" have distributed so much supply that the average stock is now breaking down, leaving only a tiny bunker of mega-caps holding the line.
3. The Flawed Rally Signature
After the first break, when the market attempts to claw its way back toward the highs on the back of retail complacency, the High-Low Index provides the final reality check.
If the market rallies but the High-Low Index remains trapped in a low range (say, between 30 and 50), it screams that the bounce is completely artificial. The broad market is refusing to make new highs; it is merely a dead-cat bounce for the averages, heavily manipulated by the index's capitalization-weighted structure.
The Mamis Synthesis: Tracking the High-Low Index completely strips away the emotional noise of the financial media. When the news narrative says "the economy is fundamentally sound" but the NYSE High-Low Index has plunged from 85 down into the 40s, the market is telling you that the foundation has eroded. The distribution process is nearing completion, and the risk of a swift structural break is at its peak.
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How does this indicator currently look like?
When evaluating these tools under the Mamis framework right now, we are seeing a fascinating, textbook demonstration of subsurface fracture and the beginning of the "Generals vs. Soldiers" divergence.
If Justin Mamis were looking at the tape today, he would likely warn that the market is attempting to paint a picture of immense confidence on the surface, while the internal breadth engine is bleeding liquidity.
Here is exactly how the NYSE High-Low Index, the Advance-Decline data, and the McClellan Summation Index look structurally right now:
1. The High-Low Dynamics: The Silent Expansion of Lows
On the major cap-weighted indexes (like the Nasdaq 100 or the S&P 500), heavyweights like Nvidia and select mega-caps have been orchestrating massive, vertical runs to keep the headline prices elevated.
However, if you look at the raw expansion of 52-week highs versus lows, the underlying reality is messy:
The Seduction: Headlines emphasize specific individual leaders breaking out to new records.
The Reality: The broader NYSE universe is experiencing a quiet, rolling correction. On recent down-days, the raw number of daily declining issues has consistently outpaced advancing issues (for instance, a recent session clocked 1,446 declines against just 1,295 advances).
The Indicator State: Because individual non-mega-cap stocks are quietly fracturing and breaking key moving averages, the High-Low Index is showing a classic Mamis bearish divergence. It is failing to confirm the strength of the major indices because the absolute pool of stocks participating in the rally is narrowing dramatically.
2. The McClellan Summation Index: Losing Altitude
The McClellan data provides the definitive proof of institutional distribution underneath the surface.
The Roll-Over: The NYSE McClellan Summation Index has recently turned downward, slipping from its prior highs to sit around the 1567 level.
The Negative Engine: This decline is driven by the daily McClellan Oscillator dropping into negative territory (recently printing -66).
The Mamis Interpretation: Remember, the Summation Index acts as the market's liquid fuel gauge. When the major indices attempt to press forward or hold their ground, but the Summation Index is actively shedding altitude, it means the velocity of buying power has broken. The market is burning massive amounts of energy (churning) just to keep the headline indices flat to slightly positive. The strong hands are feeding stock to a complacent public.
3. The Classic "Generals" Divergence
The most striking evidence of Chapter 13's "What the Market Says" framework is the stark divergence between market leaders and their underlying indices. As noted by breadth experts at the McClellan Financial Publications, we are seeing explicit bearish divergences where mega-cap leaders are pushing higher, but the broader indices and the daily A-D lines are refusing to follow.
This is the exact definition of a market propped up by a shrinking bunker of "Generals." The public looks at the giant tech and growth names and thinks, "The market is safe," entirely blind to the fact that the broader troop count—the mid-caps, cyclicals, and small-caps—has already turned and begun to retreat.
The Takeaway: The current tape is a masterclass in Mamis's distribution. The information environment remains heavily focused on the power of artificial intelligence, strong corporate earnings, and mega-cap dominance.
But the High-Low Index is fracturing, the McClellan Summation Index is losing ground, and the broad universe of individual stocks is fading. The market is speaking the language of a classic distribution top—it is feeling very comfortable to the uncritical observer, precisely because the risk is concentrated right beneath the surface.
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Source
Google Gemini
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Postscript
I don't believe in timing the market but as Howard Marks observed in his book, 'Mastering the Market cycle'..."You can't predict but you can prepare". So this is not about timing the markets, but rather, positioning your portfolio to reflect the underlying cyclic change in the markets. In other words, investors should be thinking more defensively (managing their risk and exposure to stocks) instead of reaching for more profits (reward).
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