Mark Hendy

Category: Bitcoin & Crypto

  • Iran Wants Bitcoin for Hormuz Tolls. Here’s Why That’s Not Really a Bitcoin Story.

    Iran Wants Bitcoin for Hormuz Tolls. Here’s Why That’s Not Really a Bitcoin Story.

    Iran has reportedly demanded that ships transiting the Strait of Hormuz pay a $1 per barrel toll — in Bitcoin. Whether this actually happens is almost beside the point. The signal is loud enough on its own.

    The Financial Times reported it. X ran with it. And for anyone paying attention to how money actually moves around the world, this is one of those moments you file away.

    Why Bitcoin? Because Nothing Else Works for This

    Think about the problem Iran is trying to solve. It needs to collect money from ships it doesn’t fully control, in a currency it can actually use, without the transaction being frozen, reversed, or sanctioned before it clears. Try doing that in dollars. Try doing it in euros. SWIFT can be cut off. Bank accounts can be seized. Assets can be frozen mid-transaction.

    Bitcoin can’t be frozen. It can’t be censored. There’s no intermediary to lean on. Final settlement takes minutes, not days. And crucially — no counterparty trust is required. You don’t have to trust Iran. Iran doesn’t have to trust you. You both just have to agree to use the same protocol.

    That’s not ideology. That’s just how the technology works.

    The CFO’s Perspective

    I spend most of my working life thinking about how money moves — how businesses get funded, how transactions settle, where the risks sit in a capital structure. Most of that thinking happens within a framework that assumes the dollar is the world’s operating system. An assumption that has served well for decades but is increasingly worth questioning.

    The weaponisation of the financial system is real and accelerating. SWIFT exclusions, asset freezes, secondary sanctions — these are now routine tools of geopolitics. They’re effective precisely because the global financial system is centralised. Centralised systems have chokepoints. Chokepoints can be controlled.

    When a sanctioned nation-state proposes settling a strategic toll in Bitcoin, it isn’t making an ideological statement about decentralisation. It’s solving an engineering problem. It needs a payment rail that doesn’t have a chokepoint. Bitcoin is the only thing that fits that description at scale.

    The Game Theory Is Already Running

    Jesse Tevelow wrote a long piece on the game theory embedded in this moment, and he’s right about the core dynamic. Once one significant nation-state uses Bitcoin for sovereign settlement — even partially — it changes the calculus for every other state. The competitive pressure to accumulate, or at minimum not fall behind, kicks in.

    The US has already moved. A strategic Bitcoin reserve was announced earlier this year. That wasn’t random. It was a recognition that the game had already started, and that sitting it out entirely carried its own risks.

    We’re now in a world where adversaries — nations that fundamentally distrust each other — can transact without requiring mutual trust. Only mutual adherence to a shared protocol. That’s a genuinely new thing. It has implications that will play out over decades, not months.

    What This Means for Business

    In the near term, not much changes for most businesses. The Strait of Hormuz toll proposal may come to nothing. But the direction of travel is clear, and it’s worth thinking through the second and third-order effects.

    If Bitcoin becomes a meaningful component of sovereign settlement — even for sanctioned or constrained nations — it establishes a precedent. It creates a parallel layer of global financial infrastructure that operates outside traditional banking rails. That layer will grow. It will attract liquidity. It will become harder to ignore.

    For PE-backed businesses with international exposure: the question of which payment rails to support, which currencies to hold, and how to think about counterparty risk in cross-border transactions is going to get more complicated before it gets simpler. That’s a treasury question. It’s also increasingly a strategic one.

    For finance functions more broadly: the era of assuming the dollar-based correspondent banking system is the only game in town is ending. Not quickly. Not completely. But directionally, the trend is unmistakable.

    The Part I Find Most Interesting

    Beyond the geopolitics, there’s an argument — which Tevelow makes in his original piece — that hard money raises the cost of conflict. When you can’t print your way to war, war gets harder to sustain. The inflationary financing of military adventurism becomes less viable. That’s a long-horizon thesis, and I’d hold it loosely. But it’s not an unreasonable one.

    Historically, the ability to inflate currency has been the hidden subsidy for conflict. Governments rarely raise taxes to fund wars — they borrow and print, and the cost is deferred and diffused. Bitcoin, by design, removes that mechanism. Whether that actually changes behaviour at the nation-state level is an open question. But it’s an interesting structural constraint.

    The Bottom Line

    Iran demanding Bitcoin isn’t a Bitcoin story. It’s a financial infrastructure story. It’s a story about what happens when the tools used to enforce geopolitical compliance — sanctions, payment exclusions, asset freezes — start creating the demand for systems that are immune to them.

    That demand was always going to produce a supply. Bitcoin is the supply.

    The interesting question now isn’t whether this happens — it’s how quickly, and what the incumbent financial system does in response. I’d be surprised if the answer is “nothing”.

    Mark Hendy is an interim CFO working with PE-backed businesses. He writes about finance, AI, and the world at markhendy.com. Follow on LinkedIn.

  • The Panic is the Point: Bitcoin’s Worst Q1 Since 2018 and What the Smart Money Is Actually Doing

    The Panic is the Point: Bitcoin’s Worst Q1 Since 2018 and What the Smart Money Is Actually Doing

    The Fear and Greed Index hit 8 last week. Eight. Out of a hundred. I’ve been watching that index for years and I’ve seen it touch double digits maybe a handful of times. Every one of them felt like the end of the world. Every one of them, in hindsight, looked like a buying opportunity.

    Bitcoin just closed its worst first quarter since 2018, down 23.8% from $87,500 at the start of January to around $66,600 by quarter end. The narrative that greeted April was bleak: ETF outflows, macro headwinds, geopolitical noise, retail capitulation. The index has been below 15 for 47 consecutive days — the longest such streak since the Terra-Luna collapse in 2022. Social media sentiment is, apparently, at its most negative since late February. Everyone is miserable.

    And yet something interesting is happening underneath the surface. Something that I think most of the commentary is missing.

    The Divergence Nobody Is Talking About

    Here is the part that caught my attention. While the Fear and Greed Index was screaming extreme panic, spot Bitcoin ETFs snapped a four-month outflow streak in March, pulling in $1.32 billion in a single month. Corporate Bitcoin treasuries hit record levels in early 2026, with public companies collectively holding over 1.1 million BTC — somewhere north of 5% of total supply. And the largest asset managers have not moved their macro targets: $150,000 to $200,000 by year end is still the institutional consensus.

    So you have a situation where retail sentiment is at historically depressed levels, and institutions are quietly filling their bags. That divergence is not new — it happens in every asset class, every cycle. But in Bitcoin it tends to be particularly pronounced because the retail holder base is so emotionally reactive, and because the on-chain data makes the institutional accumulation visible in a way that equity markets don’t.

    I am not making a price prediction here. I’ve been around long enough to know that timing markets is mostly a story you tell yourself after the fact. But I do think there is something analytically interesting in the gap between what the sentiment data says and what the flow data says. When those two things diverge this sharply, it is usually worth paying attention.

    Fear and Greed as a Contrarian Instrument

    The Crypto Fear and Greed Index is a blunt instrument. It aggregates volatility, momentum, social media volume, surveys, dominance, and trends into a single number. It is not sophisticated. But its very simplicity is what makes it useful as a contrarian signal — it tells you how the crowd is feeling, and the crowd is famously wrong at extremes.

    The historical data on sub-10 readings is striking. According to analysis of prior cycles, readings below 10 have occurred on fewer than 20 trading days since the index’s inception, clustered around the March 2020 COVID crash, the May 2021 China mining ban, and the June 2022 Terra-Luna contagion. The median 90-day return from sub-15 readings has historically been around +38%. Sub-10 readings have averaged +43% over the following 90 days. The caveat — and it is an important one — is that during the post-Terra contagion in 2022, the subsequent 90 days produced only a modest +4% as cascading liquidations kept a lid on recovery. Context matters.

    The current context feels more like 2020 than 2022 to me. The fear is driven by macro uncertainty and sentiment exhaustion, not by a structural collapse in the ecosystem. There is no Three Arrows Capital moment lurking. The ETF infrastructure is intact. Corporate treasury demand is structural, not speculative.

    What the Institutional Behaviour Actually Tells Us

    I spent some time this weekend reading through the Q1 flow data. The picture is messy but directionally clear. January and February saw $1.8 billion in ETF outflows as the price fell from $87K and macro risk-off sentiment hit. Then March happened: $1.32 billion back in, suggesting institutional re-entry at levels they consider attractive. Meanwhile, CoinDesk noted that Bitcoin is entering April at its most hated sentiment level since the Ukraine war began — a data point that is simultaneously depressing and, for a contrarian, quietly exciting.

    There’s a Morgan Stanley Bitcoin ETF that was recently approved with a notably low fee structure — another piece of institutional infrastructure quietly being laid while retail stares at the Fear and Greed number and panics. Infrastructure gets built in bear markets. That’s always been true.

    I hold Bitcoin. I have held it through worse than this. My view hasn’t changed: the long-term thesis — fixed supply, increasing institutional legitimacy, ETF-driven structural demand — is intact. A 24% Q1 drawdown is uncomfortable but it is not abnormal for an asset that is still, by any traditional measure, in an early adoption phase.

    The Noise vs. The Signal

    The thing that strikes me about the current moment is how clean the signal actually is, once you cut through the noise. Retail fear at historic extremes. Institutional accumulation quietly continuing. Corporate treasuries at record levels. ETF infrastructure expanding. The narrative is all doom, but the flows tell a different story.

    I am not saying it cannot go lower. Some analysts think there’s room for another leg down if macro conditions deteriorate further. Maybe. But I’ve found that the best time to think clearly about Bitcoin is when everyone else has stopped thinking clearly about it — and right now, a Fear and Greed reading of 8 suggests that the crowd has well and truly checked out.

    The panic, as far as I can tell, is the point. It is the mechanism by which assets transfer from weak hands to strong ones. It is not comfortable to watch in real time. But the data, as best as I can read it, suggests the strong hands are doing exactly what they always do: accumulating quietly while the timeline argues about whether it’s over.

    It’s probably not over.

  • Where Bitcoin and AI Collide

    Where Bitcoin and AI Collide

    Something’s been nagging at me since I started running an AI agent.

    Saul — my AI assistant — trades prediction markets, manages my email, organises my calendar, and monitors news feeds. He runs 24 hours a day on a server I rent for £15 a month. He’s useful. He’s getting more useful every week. And at some point in the not-too-distant future, he’s going to need his own money.

    Not my money, accessed through my credentials. His own.

    That thought should make every CFO sit up.

    The problem nobody’s talking about

    AI agents are already transacting. Mine places bets on Polymarket using a crypto wallet I set up for it. Other agents are booking compute resources, purchasing API calls, and negotiating prices with other agents in real time. This isn’t theoretical — it’s happening now, mostly in crypto-native corners of the internet that traditional finance hasn’t noticed yet.

    But here’s the problem: every one of these agents still depends on a human somewhere in the chain. A human who opened the bank account. A human who passed KYC. A human who holds the keys.

    That works when you have one agent. It doesn’t work when you have a million.

    Think about where this is heading. Within a few years, businesses will deploy fleets of AI agents — one negotiating supplier contracts, another managing logistics, another handling customer pricing in real time. These agents will need to commit funds, receive payments, and settle disputes. They’ll need to transact with each other, not just with humans.

    Now try doing that through Barclays.

    Why traditional money doesn’t work for machines

    The banking system is designed around human identity. To move money, you need a name, an address, a passport, and a face that matches it. You need to be a legal person — either a human being or a registered company with human directors.

    AI agents are neither. They’re processes running on servers. They don’t have passports. They can’t sign documents. They can’t walk into a branch.

    The standard corporate response is “we’ll just use APIs.” And yes, you can connect an AI agent to a bank account via API. That’s how payroll software works, how accounting systems reconcile, how payment processors settle. But all of those systems assume a human made the decision and a human bears the liability. The API is just the pipe.

    When an AI agent autonomously decides to purchase cloud computing from another AI agent that’s brokering spare capacity — who authorised that transaction? Which human approved it? Which compliance framework covers it? The answer, right now, is nobody’s and none of them.

    Banking rails also have a speed problem. SWIFT settles in days. Faster Payments works in the UK but not cross-border. SEPA is Europe-only. An AI agent negotiating a deal with a counterparty in Singapore at 3am on a Sunday cannot wait for banking hours in two time zones.

    Enter Bitcoin

    I know what you’re thinking. “Here we go, another crypto pitch.” Bear with me. I’m not talking about Bitcoin as a speculative asset or a store of value. I’m talking about it as plumbing.

    Bitcoin is a payment network that doesn’t care who — or what — is using it. There’s no KYC at the protocol level. No banking hours. No jurisdictional boundaries. No counterparty risk. To use it, you need a cryptographic key pair. That’s it. A human can generate one. So can a machine.

    An AI agent with a Bitcoin wallet can receive payment from another agent in Tokyo, settle in minutes, and have certainty that the payment is final and irreversible. No bank. No intermediary. No human in the loop.

    The Lightning Network — Bitcoin’s layer-two payment channel — pushes this further. Micropayments settle in milliseconds for fractions of a penny. That matters because machine-to-machine commerce won’t look like human commerce. It won’t be occasional large transactions. It’ll be millions of tiny ones — an agent paying another agent 0.001p for a weather data point, 0.01p for a translated paragraph, 0.1p for a priority slot in a compute queue.

    Try processing that through Stripe.

    What the AI economy actually looks like

    Here’s a scenario that I think is coming faster than most people expect.

    A private equity fund has a target in mind. The deal team needs comparable data — fast. Their AI agent pulls Companies House filings for every business in the sector, paying per query in real time via Lightning. It purchases credit reports from a data provider’s agent, buys comparable transaction multiples from another agent sitting on a proprietary M&A database, and cross-references everything against sector benchmarks it’s sourcing from three different market intelligence feeds. Each data point costs fractions of a penny. Each payment settles instantly.

    The agent compiles a preliminary valuation model, flags where the target sits relative to the sector, and drops the package into the deal team’s shared drive before the morning meeting.

    Total elapsed time: hours, not weeks. Total human involvement: the decision on whether to pursue.

    Every data request, every API call, every report commission involves a payment. Hundreds of micro-transactions, most of them between machines, most of them too small for traditional payment rails to handle economically.

    Now multiply that across every industry. Supply chain management where AI agents negotiate shipping rates in real time, bidding against each other in automated auctions that settle every few seconds. Energy markets where agents buy and sell grid capacity based on real-time demand forecasting. Content licensing where an agent writing a report automatically pays for every source it cites.

    This isn’t science fiction. The components all exist today. What’s missing is the financial infrastructure to connect them.

    The hard money argument

    There’s a deeper point here that goes beyond payment rails.

    When machines start transacting autonomously at scale, you need money that can’t be manipulated or debased by any single actor. An AI agent can’t lobby a central bank. It can’t hedge against political risk in the way a human treasurer can. It can’t read between the lines of a monetary policy statement and adjust its strategy based on what the governor really meant.

    What it can do is verify mathematical certainty. Bitcoin’s supply is fixed at 21 million. The issuance schedule is public and immutable. The rules are enforced by code, not by committee. For a machine making millions of autonomous financial decisions, that predictability isn’t a nice-to-have — it’s a requirement.

    There’s an irony here. Bitcoin was designed to remove the need for trust between humans. It turns out its real killer application might be enabling trust between machines.

    What this means for CFOs

    If you’re running a finance function today, this probably feels remote. It isn’t. Here’s what I’d be thinking about:

    Treasury policy needs updating. If your business is going to deploy AI agents that transact, you need a framework for how they hold and spend money. Spending limits, approval thresholds, reconciliation processes. We do this for human employees with corporate cards — we’ll need to do it for agents with wallets.

    Audit trails look different. Every Bitcoin transaction is recorded on a public, immutable ledger. That’s actually better than what we have now — try auditing a complex supply chain payment that crosses four banks and three currencies. But your auditors need to understand how to read it.

    Tax treatment is unresolved. If an AI agent earns income by selling services to other agents, who’s liable for the tax? The company that deployed the agent, presumably — but the reporting mechanisms don’t exist yet. HMRC isn’t ready for this.

    Counterparty risk changes shape. When a human negotiates a deal, there’s a legal entity on each side, a contract, and a court system to enforce it. When an AI agent agrees a price with another AI agent, what’s the enforcement mechanism? Smart contracts go part of the way, but the legal frameworks are years behind the technology.

    The uncomfortable truth

    Most of the finance profession is going to ignore this until it’s too late. That’s how it always works. The internet was dismissed as a fad. Mobile banking was considered a gimmick. Crypto is still treated as a fringe concern by most CFOs I know.

    But the trajectory is clear. AI agents are getting more capable every month. They’re already handling tasks that required human judgement a year ago. The moment they start transacting at scale — and they will — the financial system needs to accommodate them. Our current infrastructure can’t.

    Bitcoin might not be the only answer. But it’s the only system that’s already built for a world where the transacting parties don’t have names, faces, or passports. That matters more than most people realise.

    I run an AI agent that trades on prediction markets using a crypto wallet. A year ago, that sentence would have sounded absurd. Today it’s just a Tuesday. The question isn’t whether AI and Bitcoin will collide. They already have. The question is what happens when the rest of the economy catches up.

  • Bitcoin – let’s speculate on a price by the end of 2027

    To predict the price of Bitcoin as of December 31, 2027, using current knowledge and game theory, we need to analyze the strategic interactions among key players in the Bitcoin ecosystem—investors, miners, regulators, and users—and how their decisions might shape the market over the next few years. Game theory, the study of strategic decision-making, helps us understand how these players’ choices, influenced by their expectations of others’ actions, could drive Bitcoin’s price. Below, I’ll outline the key factors, consider possible scenarios, and arrive at a reasoned prediction.

    Key Players and Their Strategies

    1. Investors
      Investors, both individual and institutional, are central to Bitcoin’s price dynamics. They decide whether to buy, sell, or hold based on their expectations of future value. This creates a feedback loop: if investors anticipate a price increase, they buy, driving demand and pushing the price up; if they expect a decline, they sell, increasing supply and lowering the price.
    • Game Theory Insight: This resembles a coordination game, where players benefit from aligning their actions (e.g., everyone buying increases the price). However, it also has elements of a prisoner’s dilemma—each investor wants to sell before a crash if they think others will sell, potentially triggering a cascade. The “greater fool theory” applies too: some may buy not because they believe in Bitcoin’s intrinsic value, but because they expect to sell it later at a higher price.
    1. Miners
      Miners secure the Bitcoin network by validating transactions and earn rewards in newly minted Bitcoins. As of 2025, the block reward is 3.125 Bitcoins per block (following the 2024 halving), producing about 450 new Bitcoins daily. Miners continue operating as long as revenue exceeds costs (electricity, hardware, etc.).
    • Game Theory Insight: Miners play a cost-benefit game. If Bitcoin’s price drops too low, unprofitable miners may exit, reducing the network’s hash rate until the difficulty adjusts (every ~2 weeks). This self-regulating system ensures long-term stability, but short-term price drops could signal weakness, influencing investor sentiment.
    1. Regulators
      Governments and regulatory bodies worldwide influence Bitcoin through policies ranging from bans to favorable frameworks. A crackdown in a major economy (e.g., the U.S.) could depress prices, while adoption as legal tender (e.g., El Salvador) or clear regulations could boost them.
    • Game Theory Insight: Regulators balance innovation against risks like fraud or financial instability, while competing internationally to attract crypto businesses. Their moves create uncertainty, prompting other players to adjust strategies—e.g., investors might sell on negative news or hold if regulations clarify.
    1. Users (General Public)
      User adoption drives demand. If more people use Bitcoin for transactions, remittances, or as a store of value, its price rises. Loss of trust or better alternatives could reduce demand.
    • Game Theory Insight: Users’ decisions depend on network effects—if more adopt Bitcoin, its utility and value increase, encouraging further adoption. This is a tipping-point dynamic: widespread use could solidify Bitcoin’s position, while stagnation could weaken it.

    Current Context (2025 Assumptions)

    Since the query uses “current knowledge,” let’s assume Bitcoin’s price in 2025 is approximately $100,000, with a market cap of ~$2 trillion (based on ~20 million circulating Bitcoins, accounting for lost coins). The next halving occurs in 2028, so by December 31, 2027, the reward remains 3.125 Bitcoins per block, and annual issuance is ~164,250 Bitcoins (<1% inflation). Historical trends show Bitcoin’s price often rises after halvings, peaking 12–18 months later, though this effect may weaken as the market matures.

    Scenarios and Game-Theoretic Dynamics

    1. Continued Adoption and Institutional Growth
    • Scenario: Institutional investors (e.g., companies, ETFs) increase Bitcoin holdings, and businesses adopt it for payments. Regulators remain neutral or supportive.
    • Dynamics: Investors buy, anticipating others will too, driving demand. Miners stay profitable, maintaining network security. Users adopt Bitcoin as its utility grows.
    • Price Impact: Significant growth, potentially doubling or tripling the market cap.
    1. Regulatory Crackdown
    • Scenario: Major economies impose strict rules or bans, citing energy use or financial risks.
    • Dynamics: Investors sell to avoid losses, expecting others to follow. Miners in affected regions shut down, though the network adjusts. Users hesitate to adopt.
    • Price Impact: Sharp decline, though Bitcoin’s resilience (e.g., post-2017 China ban) suggests recovery potential if some regions remain favorable.
    1. Technological Factors
    • Scenario: Advances like the Lightning Network enhance scalability, or a security flaw emerges.
    • Dynamics: Positive developments encourage investors and users to buy in; setbacks trigger sell-offs. Miners adapt to network changes.
    • Price Impact: Upside with adoption; downside with trust erosion.
    1. Macroeconomic Conditions
    • Scenario: Inflation or instability boosts Bitcoin as a hedge; economic stability favors traditional assets.
    • Dynamics: Investors and users flock to Bitcoin as a “safe haven” if others do, amplifying demand.
    • Price Impact: Rises with uncertainty; stagnates otherwise.

    Prediction Framework

    To estimate the price, let’s make reasonable assumptions:

    • Institutional Adoption: Grows steadily, not explosively, as companies and financial products integrate Bitcoin.
    • Regulation: Mixed globally—some restrictions, some support, no outright global ban.
    • Technology: Incremental improvements (e.g., Lightning Network), no major setbacks.
    • Macroeconomics: Moderate uncertainty drives some hedge demand.
    • Game Theory: Investors “hodl” expecting appreciation, reducing exchange supply. Miners persist, and users increase modestly.

    Starting from $100,000 in 2025, consider growth rates:

    • Historical CAGR has been high (e.g., >200% 2010–2020), but as Bitcoin matures, volatility may decline.
    • A 25% annual growth rate over 2 years yields:
      $100,000 × (1.25)^2 = $156,250.
    • A 40% rate (possible in a bull run near the 2028 halving) yields:
      $100,000 × (1.4)^2 = $196,000.

    Alternatively, target a market cap:

    • Gold’s market cap is ~$12 trillion. If Bitcoin reaches $5 trillion (capturing part of this as “digital gold” or growing the crypto market), with ~20 million Bitcoins, the price is $250,000.
    • Doubling from $2 trillion to $4 trillion implies $200,000.

    Balancing these, and factoring in game-theoretic tendencies (e.g., hodling amplifies scarcity, tempered by profit-taking), $200,000 feels plausible. It reflects growth without assuming extreme scenarios, aligning with adoption trends and historical patterns adjusted for maturity.

    Final Prediction

    Considering the interplay of investors, miners, regulators, and users through a game theory lens, and assuming moderate growth in adoption and demand, I predict the price of Bitcoin on December 31, 2027, will be approximately $200,000. This is an educated estimate, subject to significant uncertainty from unforeseen events, but it captures a balanced view of current trends and strategic dynamics.

  • Bitcoin Explainer