I’ve been a trader and investor for 44 years. I left Wall Street long ago—-once I understood that their obsolete advice is designed to profit them, not you.
Today, my firm manages around $4 billion in ETFs, and I don’t answer to anybody. I tell the truth because trying to fool investors doesn’t help them, or me.
In Daily H.E.A.T. , I show you how to Hedge against disaster, find your Edge, exploit Asymmetric opportunities, and ride major Themes before Wall Street catches on.
Table of Contents
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H.E.A.T.
Value investing is broken. Not because Graham was wrong — but because AI has split the market into two universes: businesses it will destroy, and businesses it physically cannot. Here’s how to tell the difference.
The Gospel
Here is the most dangerous idea in investing right now: that a cheap stock is a good stock.
For most of the last century, that logic held. Find a company trading below its intrinsic worth. Buy it. Wait for the market to wise up. Ben Graham built the architecture. Warren Buffett turned it into the greatest wealth-creation machine in modern history. The logic was elegant: markets misprice assets, patient investors who do the work get paid, and time does the rest.
It worked. For a long time.
But two things have changed — quietly, then all at once. And together they have made the old value investing playbook not just less effective, but actively dangerous.
The Crack in the Gospel
The first crack is information. Graham’s edge was simple: he was reading what most investors never bothered to read, doing arithmetic most couldn’t be bothered to do. Today, every ratio, every screen, every “value list” is available to everyone, instantly, for free. Bloomberg killed that edge. The internet finished it off. If a stock looks cheap, there’s almost always a reason — and the reason is rarely “the market missed it.”
And that brings us to the second crack. The deeper one. The existential one.
A growing share of stocks don’t screen cheap because the market is being irrational. They screen cheap because AI is going to hollow them out. The market hasn’t miscalculated. It has correctly identified a structural threat and priced it in. Buying that stock isn’t value investing. It’s catching a falling knife in the dark.
“The problem isn’t finding cheap stocks. The problem is that a stock can be cheap because the market has already figured out that AI is going to destroy it. That’s not a value opportunity. That’s a warning label.”
We have already watched single AI product announcements erase tens of billions in market cap in a single session — particularly in industries where the core product is information, analysis, routing, or workflow. Financial data platforms. Logistics intermediaries. Credit scoring incumbents. Research services. Every one of those businesses built its moat on cognitive work. And cognitive work, it turns out, is exactly what AI replaces first.
The old screening process — low P/E, low P/B, high dividend yield — cannot distinguish between a stock that is temporarily misunderstood and a stock that is cheap because a software model is in the process of replacing its entire business model. That distinction is now the most important one in investing.
The Mechanism: Where Real Value Hides Now
So where does genuine value live in a world where information arbitrage is dead and AI is rewriting business models in real time?
It lives in the one place AI cannot reach: the physical world.
AI is a software revolution. It replicates cognitive tasks at near-zero marginal cost — writing code, analyzing contracts, pricing risk, routing logistics decisions. What it cannot do is mine copper, pour concrete, generate electricity, lay pipeline, or move a freight car. Those things require physical infrastructure. Physical infrastructure takes years — sometimes decades — to permit, finance, and build.
Here is the paradox at the heart of the AI boom: AI is creating physical scarcity before it creates financial returns. The combined annual capital expenditures of Amazon, Alphabet, Meta, and Microsoft now reach $610 billion — four times what they spent before ChatGPT launched in 2022. That capital wave is colliding with a physical supply chain that cannot scale at software speed. Power interconnection queue wait times in high-demand markets stretch 5 to 10 years. Transformer lead times have gone from weeks to years. Amazon has bypassed the open commodities market entirely, signing direct supply deals with Rio Tinto for Arizona copper because the market cannot deliver on the timeline the data center buildout demands.
Former Google CEO Eric Schmidt testified before Congress that the country needs 92 additional gigawatts of power to support the AI buildout. The average nuclear plant delivers 1.5 gigawatts. That gap does not close quickly. Only natural gas can bridge it on any realistic timeline, and even that requires years of permitting and construction.
“We’re running out of electricity. I testified in Congress we need 92 gigawatts more power. The average nuclear power plant is 1.5 gigawatts. You see the problem.”
— Eric Schmidt, Former Google CEO, before Congress
In the age of infinite software, value lives in finite stuff.
That is the investing framework we call HALO: Hard Assets, Low Obsolescence. Businesses with irreplaceable physical infrastructure and tollbooth economics — assets that AI needs to function but cannot replicate, in industries where revenue stability is structural rather than cyclical. The un-disruptables.
HISTORICAL ANALOGUE The 1970s: When Physical Scarcity Rewrote the Investment Landscape The closest parallel to today’s environment is the early 1970s, when a decade of growth-stock mania centered on the Nifty Fifty gave way to a prolonged period of commodity-driven, hard-asset outperformance. The mechanism was identical to what we see today: speculative capital had concentrated in businesses whose valuations assumed perpetual capital-light growth. When the real economy demanded physical resources — energy, metals, infrastructure — pricing power shifted decisively to the holders of those assets, not the holders of software licenses. The difference today is that the catalyst isn’t an oil embargo. It’s a $610 billion annual AI capex cycle consuming natural gas, copper, concrete, water, and land at rates the physical supply chain cannot match. The businesses sitting at those physical bottlenecks — the ones that look boring, that don’t make headlines, that trade at discounts to the index because nobody is writing research notes about them — are positioned exactly where the Nifty Fifty refugees were positioned in 1973. |
What a HALO Company Looks Like
The HALO framework asks three questions about every business. The answers determine whether it qualifies or gets filtered out.
Does it own heavy, irreplaceable physical assets?
Not just “some equipment.” The bar is assets whose replacement would take years and cost multiples of book value — quarries, pipelines, rail lines, power generation facilities, freight terminal networks. Assets that cannot be digitized and cannot be replicated by a well-funded startup in three years. A software company can be copied. A rail right-of-way that runs through the center of a major city cannot.
Is the cash flow toll-like and repeatable?
Utilities charge for electrons. Pipelines charge for throughput. Rail lines charge for weight-miles. These businesses don’t have product cycles. They don’t have user bases that can be poached by a better algorithm. They have infrastructure that charges tolls, and the tolls are remarkably consistent across market cycles. High revenue stability and high margin stability — earned through structural necessity rather than competitive moat — are the hallmarks of a HALO business.
Is the competitive advantage rooted in atoms, not cognition?
The most important filter: how much of this company’s competitive advantage comes from human cognitive work that AI can replicate, versus physical infrastructure that AI cannot touch? A law firm is almost entirely cognitive. A copper mine is almost entirely physical. Most businesses sit somewhere in between. HALO targets the physical end of that spectrum — businesses where intangible assets are minimal, fixed assets per employee are high, and the core value delivered is a physical service, not an intellectual one.
The result tilts hard toward energy, utilities, industrials, and materials — the physical substrate the AI economy is literally being built on top of — and away from the parts of technology and services most exposed to software substitution.
Two HALO Companies Worth Knowing
The HALO framework surfaces a consistent set of businesses that pass all three filters. We’re going deep on two today — one the most obvious AI scarcity story that almost nobody is telling correctly, and one a genuine contrarian idea that requires sitting with a counterintuitive premise long enough for the logic to land.
FCX Freeport-McMoRan The world’s largest publicly traded copper producer — and the company sitting at the physical bottleneck the AI economy cannot route around. Every AI buildout ends in the same place: copper. Inside the data center. In the transformers. In the transmission lines. In the grid upgrades surrounding each campus. You cannot build the physical infrastructure of the AI economy without it, and you cannot synthesize it, import it on a short timeline, or substitute your way around it. Here is the supply problem in plain arithmetic. Bringing a major copper mine from discovery to full production takes, on average, sixteen years. The mines that will supply the copper for the data centers being built in 2035 need to be in development right now. Most of them are not. Meanwhile, hyperscalers are consuming copper by the millions of pounds — in the buildings themselves, in the power infrastructure around them, and in every mile of transmission line connecting them to the grid. The demand curve is accelerating. The supply curve cannot respond at software speed. Freeport operates the Grasberg complex in Papua, Indonesia — the world’s largest copper mine by reserve base, in continuous production since 1972. It also operates the Morenci mine in Arizona, the largest copper mine in North America. Combined, Freeport produces approximately 4.2 billion pounds of copper annually, representing roughly 8% of global mined supply. No other publicly traded company approaches that scale. The operating leverage is what makes this more than a commodity story. Freeport’s cost of production is largely fixed. The mine operates whether copper is at $3 a pound or $5 a pound. Every dollar of price appreciation above the cost curve flows disproportionately to the bottom line. When copper rallied sharply in 2021 and 2022, Freeport’s free cash flow nearly quadrupled over two years. That leverage structure is intact, and the demand thesis is materially stronger today than it was then. The Amazon-Rio Tinto deal is the tell. Amazon did not go to the open market for copper. They signed a direct, long-term supply agreement with a producer to secure Arizona copper for their data centers. That is not a purchasing decision. That is a company publicly acknowledging that open-market supply is insufficient and that securing physical resources directly from producers is now a strategic imperative. Freeport is the largest producer of the resource that Amazon just classified as a strategic necessity. This is not a cheap-stock story. Freeport rarely is, because copper pricing is volatile and the market prices that volatility into the multiple. The HALO argument is about structural positioning: the world’s largest copper producer, at the precise moment when copper demand is structurally accelerating and new supply cannot come online fast enough to meet it.
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4.2B lbs Annual Copper Production | ~8% Share of Global Supply | ~16 years New Mine Lead Time | 1972 Grasberg First Production |
ODFL Old Dominion Freight Line The company the market sold on AI disruption fears — and why that reaction was exactly wrong. Earlier this year, an AI startup announced a tool that could autonomously configure and book freight shipments. The market’s response was swift: trucking stocks were sold hard across the board. Old Dominion fell with the sector. The narrative wrote itself in about forty-five minutes: AI disrupts logistics, freight companies are obsolete, get out. The narrative is wrong. And understanding precisely why it is wrong is the clearest possible illustration of what the HALO framework is built to find. The AI freight tool automates the cognitive task of freight booking — comparing rates, selecting carriers, filling out forms, routing shipments through intermediaries. That is real disruption, and it will hit logistics brokers, freight management software companies, and booking intermediaries very hard. Those businesses are almost entirely cognitive. An algorithm can do what they do, and eventually will. What an algorithm cannot do is operate a terminal. Old Dominion’s competitive advantage is not in booking freight. It is in moving it. The company operates 255 service centers across the United States — the physical network of terminals, dock doors, loading bays, and route infrastructure that constitutes less-than-truckload logistics at scale. Building that network from scratch would require billions of dollars, years of real estate acquisition in urban and suburban markets where suitable industrial property is increasingly difficult to obtain at any price, and decades of operational refinement. There is no shortcut. There is no software substitute for a dock door in Charlotte. The performance metric that matters is Old Dominion’s operating ratio — operating expenses as a percentage of revenue — which has run roughly 7 to 8 percentage points better than the LTL industry average for over a decade. That gap is not produced by better booking software. It is produced by a physical network that has been positioned, configured, and optimized over decades in ways that took years to build and cannot be replicated by writing a prompt. Here is the part the market missed entirely: the AI economy is not a weightless economy. Every data center being constructed across the Sun Belt requires physical delivery of servers, cooling infrastructure, electrical components, and construction materials. Every mile of new transmission line being built requires physical delivery of cable, transformers, and installation hardware. The AI buildout is, in a direct and measurable sense, a logistics boom. Old Dominion’s terminal network is the infrastructure layer that the AI economy is literally being assembled on top of. The market sold Old Dominion because it confused cognitive disruption with physical disruption. The HALO framework buys that confusion. A world-class physical network, temporarily mispriced because investors could not distinguish between what AI disrupts and what it cannot, is exactly the kind of opportunity this lens is designed to identify.
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255 Service Centers | ~75% ODFL Operating Ratio | ~82% LTL Industry Average OR | ~7 pts OR Advantage vs. Industry |
WHAT WOULD BREAK THIS THESIS ▪ AI capex slows materially: The Mag-4’s free cash flow is on track to decline significantly as capex consumes what was once returned to shareholders. If investor pressure forces a pullback in the buildout, the physical scarcity thesis loses its near-term catalyst. ▪ Commodity price collapse: A global recession or demand shock would compress copper prices and energy revenues quickly. Hard-asset businesses are not immune to macro drawdowns — they can be punished faster than the broader index when the cycle turns. ▪ Asset-heavy leverage risk: By construction, capital-intensive businesses carry more fixed costs and often more balance sheet leverage. In a credit contraction, they absorb losses disproportionately. Physical asset moats do not protect against liquidity stress. ▪ AI disruption reaches the physical layer faster than expected: Autonomous trucking at scale, AI-managed grid optimization, and robotic construction are not near-term realities — but if the physical automation timeline accelerates meaningfully, some moats that appear durable today may narrow. ▪ The constraints eventually ease: Copper mines get built. Power plants come online. Grid infrastructure expands. The scarcity premium commands a duration, not a permanent ceiling. The thesis is strongest over the next five to ten years while the supply response plays catch-up. |
Five Takeaways
1. “Cheap” and “undervalued” are no longer synonyms. A low multiple today may reflect a real structural problem, not a market mistake. The first question to ask about any value screen result is: why is this cheap? If the answer touches cognitive work, be very careful.
2. AI creates physical scarcity before it creates financial returns. The $610 billion annual hyperscaler capex cycle is hitting a physical supply chain that cannot scale at software speed. Copper, power, concrete, transformers, and land are all bottlenecked. The companies sitting at those bottlenecks have structural pricing power.
3. The highest-risk “value stocks” are the ones exposed to cognitive substitution. Information, analysis, routing, pricing, underwriting, reporting — if the business is fundamentally doing cognitive work, AI is building a cheaper substitute. A low P/E in that context is not a margin of safety. It is a forward discount.
4. Market overreactions to AI disruption create entry points in HALO names. Old Dominion fell because investors couldn’t distinguish booking freight from moving it. That confusion is the HALO framework’s hunting ground. When the market sells physical infrastructure because it rhymes thematically with cognitive disruption, pay attention.
5. Physical constraints are not solved by software updates. The copper supply deficit is measured in decades. The grid interconnection queue is measured in years. The concrete permitting process takes most of a decade. These are not narrative risks. They are arithmetic. And the companies sitting at those physical bottlenecks are not going away because someone trained a better model.
The market has spent three years rewarding the companies building the AI revolution. It is only beginning to price the companies the AI revolution cannot function without.
The Moon Was Never About the Moon
Control of the high ground has always shaped what happens below it. Apollo was the
opening move. Artemis is the next — NASA sending crews back to the Moon and building
the infrastructure to keep them there. Satellites already run global supply chains,
communications, and economies. Nations are spending heavily to protect that access.
The Tuttle Capital Space Industry Income Blast ETF (SPCI) holds 11 pure-play names
across that stack. Could SPCI have a place in a diversified portfolio?
Learn More at incomeblastetfs.com/etf/spci.
News vs. Noise: What’s Moving Markets Today
The market regained it’s 50 and 200 day moving averages last week……
That’s a good support level to use, any break back below increases the odds we retest the lows. The rally last week was due to the 14 day cease fire, and hopes it becomes permanent. So far not so good…
Right now the SPY is still above the 50 day, think traders are learning the game—-fade the rallies and buy the dips. That Iranian guy who was tweeting a couple of weeks ago has been right on so far.
Now we wait to see what impacts this has, if any, on inflation, and how long oil stays elevated. We are likely to see at least a few months of elevated inflation and some central bank hiking.
This week we get another data point, earnings, with numerous banks kicking things off.
We continue to believe there are three ways you can play this current environment:
If you are nimble you can buy the dips and sell the rips
Stay out—-Problem with this always is when do you get back in?
Figure out where you want to be when this is “over” and be there.
We think that’s energy, commodities, gold miners, memory (on weakness), photonics (on weakness), cybersecurity, HALO, defense, crypto, and of course space (for more on that sign up for our webinar on Thursday).
What Iran Tells Us About UFO Disclosure
When governments confront unknown threats in their airspace, defense budgets surge
and the same aerospace and surveillance companies move hardest. On March 2nd,
Northrop jumped 6% and Lockheed 3.3% on the Iran news — and President Trump has
since ordered the formal release of government UAP files, with the Pentagon confirming
compliance. So if a conventional conflict can move these stocks this fast, what happens
when the bigger story breaks?
See the UFOD holdings: [thetruthisoutthereufod.com
ETF News
$MEMY Holdings Update:
We replaced $TEM ( ▲ 10.92% ) $AAPL ( ▲ 0.44% ) $BRZE ( ▼ 2.91% ) and added $BABA ( ▲ 1.11% ) $INFQ ( ▼ 1.41% ) $BTU ( ▼ 2.84% ) All 5% positions.
For a full list of MEMY holdings, visit:
https://incomeblastetfs.com/etf/memy
Distributor: Foreside Fund Services, LLC
A Stock I’m Watching
Today’s stock is $BTU ( ▼ 2.84% )
BTU undercut Thursday’s low but then rallied back above. Buyable as long as it stays above the 200 day moving average.
In Case You Missed It
I had the pleasure of talking to Dividend Degenerates on why I like put spreads better than covered calls for income…..
The H.E.A.T. (Hedge, Edge, Asymmetry and Theme) Formula is designed to empower investors to spot opportunities, think independently, make smarter (often contrarian) moves, and build real wealth.
The views and opinions expressed herein are those of the Chief Executive Officer and Portfolio Manager for Tuttle Capital Management (TCM) and are subject to change without notice. The data and information provided is derived from sources deemed to be reliable but we cannot guarantee its accuracy. Investing in securities is subject to risk including the possible loss of principal. Trade notifications are for informational purposes only. TCM offers fully transparent ETFs and provides trade information for all actively managed ETFs. TCM's statements are not an endorsement of any company or a recommendation to buy, sell or hold any security. Trade notification files are not provided until full trade execution at the end of a trading day. The time stamp of the email is the time of file upload and not necessarily the exact time of the trades. TCM is not a commodity trading advisor and content provided regarding commodity interests is for informational purposes only and should not be construed as a recommendation. Investment recommendations for any securities or product may be made only after a comprehensive suitability review of the investor’s financial situation.© 2026 Tuttle Capital Management, LLC (TCM). TCM is a SEC-Registered Investment Adviser. All rights reserved.