Predictive algorithms are only as robust as signals consistency.
If you train an algorithm to action something based on patterns of events and thresholds, even with stress tests for edge cases and extremes, even with human intervention when the unforeseen and impactful happens, if something devastatingly anomalous happens and keeps happening, with a systemic network effect on signals coherence, bets are off.
This statement has been playing out in real time as global markets reel. A supposed black swan event, that is no such thing, because it was predictable. While people with means, motive, and opportunity to stop this failed to show the will (or guts) to step in.
From this point forward I delegated to Claude 3.7, with some substantial checks, but it is not me and my output. So many words have been wasted on warnings (many of my own). That requires enormous effort to research, check, and frame, so this time I handed over to the much vaunted prediction and analysis machine that is also saying 'Not predictable? Really?!'
The Accelerationist Wave: Creative Destruction by Design?
There's a darker possibility lurking beneath the surface chaos: what if the market turmoil isn't merely a side effect of misguided policy, but a feature of deliberate accelerationism?
The recent revelations about Elon Musk's DOGE team gaining unprecedented access to the Treasury Department's payment systems—systems that process nearly £4.5 trillion annually for programs like Social Security, government salaries, and congressionally appropriated funds (BBC, February 2, 2025)—should raise alarm bells. This access was granted the same day a long-time Treasury official who "strongly resisted" such access was placed on administrative leave and abruptly retired.
"To put it bluntly, these payment systems simply cannot fail, and any politically-motivated meddling in them risks severe damage to our country and the economy," Senator Ron Wyden wrote in an urgent letter to Treasury Secretary Bessent.
Meanwhile, the Trump family has launched World Liberty Financial, a cryptocurrency venture with its own dollar-pegged stablecoin. As Politico reported (March 30, 2025), this venture creates a concerning scenario where the family of the president could directly profit from gutting regulatory oversight while simultaneously gaining unprecedented access to the systems that process government payments.
The accelerationist philosophy—championed by figures adjacent to the administration who view institutional collapse as a prerequisite for rebuilding society—may explain why we're witnessing simultaneous attacks on the Federal Reserve's independence, market stability, and regulatory frameworks. A federal judge recently noted the "unprecedented" authority and "unusual secrecy" of DOGE operations, ordering urgent release of its records (Politico, March 10, 2025).
Is this simply chaotic governance, or a calculated strategy to create opportunities for private profit amid public system failure? The documented efforts to dismantle oversight at the Treasury, FTC, CFPB, and SEC take on a more ominous character against this backdrop.
The "PANICANs" and the Phantom Pause
"Don't be Weak! Don't be Stupid! Don't be a PANICAN (A new party based on Weak and Stupid people!)," Trump wrote on social media as markets continued their precipitous decline.
"Be Strong, Courageous, and Patient, and GREATNESS will be the result!"
Perhaps no moment better illustrates market vulnerability than reaction to a big financial news aggregator account on X posting about a "tariff pause".
Amanda Silberling
On April 7, markets were in freefall when the rumour suddenly emerged claiming that Trump was considering a 90-day pause on tariffs for all countries except China.
The verified X account Walter Bloomberg - posted: "HASSETT: TRUMP IS CONSIDERING A 90-DAY PAUSE IN TARIFFS FOR ALL COUNTRIES EXCEPT CHINA." and attributed it to Reuters (which initially did report that economic adviser Kevin Hassett had made such a statement on Fox News).
The reality? Hassett had said no such thing. When actually asked if Trump would consider a 90-day pause, he had merely responded: "I think the president is going to decide what the president is going to decide," before noting that countries were negotiating with Trump.
Nevertheless, the mere suggestion of a pause sent markets into a brief frenzy of optimism. The algorithmic trading systems—trained to react instantaneously to news—sent stock prices spiking within minutes. But the reprieve was short-lived. The White House quickly doused the rumour, issuing a terse correction: "Wrong. Fake News." Markets then resumed their downward plunge.
This pattern—create chaos, let a false hope emerge, then crush it definitively—mirrors tactics Trump himself described in "The Art of the Deal": keeping opponents perpetually off-balance, unable to find stable footing. "The worst thing you can possibly do in a deal is seem desperate to make it," Trump wrote. "That makes the other guy smell blood, and then you're dead."
Whether by design or instinct, this approach to market communication creates precisely the information environment where traditional algorithmic models falter. Markets rely on clear signals and credible information to function efficiently. When those signals become deliberately muddied, algorithms trained on historical patterns of rational behaviour struggle to distinguish noise from signal.
For institutional investors and average citizens alike, the result is a perpetual state of PANICAN—Trump's neologism—where even momentary relief can vanish in an instant, replaced by deeper uncertainty about what might come next.
When Black Swans Aren't So Black
Nassim Nicholas Taleb defined black swan events as having three key characteristics: they are unexpected, they carry extreme impact, and they appear obvious in hindsight. But what happens when the swan is grey, visible on the horizon, yet impossible to address?
The current economic turmoil represents something more insidious: a highly predictable crisis that remained unaddressed because the data required to justify preventative action seemed overwhelming compared to the perceived probability of successfully addressing it.
As the Dow experienced its worst three-day crash since October 1987 (CNBC, April 8, 2025), business leaders who had remained silent began speaking out. Ken Langone, Home Depot co-founder and GOP megadonor, blasted the tariffs as "bullshit" and described the 34% rate on China as "too aggressive, too soon" (Financial Times, via CNBC, April 8, 2025).
But why did it take a 19% wipeout of Apple's market cap—a staggering $638 billion loss—before the business community found its voice?
The Rational Actor Myth Meets Reality
The same algorithmic models forecasting economic behaviour have long been built on the premise of the "rational economic actor"—the cornerstone assumption that consumers and businesses will make decisions maximizing utility, processing information efficiently, and acting in their long-term self-interest.
Yet research consistently undermines this assumption, never more clearly than now. When JP Morgan Chase CEO Jamie Dimon warns that tariffs will "likely" boost prices and slow growth (JP Morgan Shareholder Letter, April 7, 2025), while the White House simultaneously claims "there is NO INFLATION" (Trump Truth Social post, April 8, 2025), how can consumers rationally process such contradictory information?
The Tax Foundation's analysis makes the stakes clear: Trump's tariffs will reduce after-tax incomes by 1.9% on average—translating to more than £1,900 per US household in 2025 (Tax Foundation, April 4, 2025). Yet many consumers may make economic decisions based not on these projections but on political allegiance, social media narratives, or emotional reactions to conflicting information.
The Invented Expertise Problem
Perhaps most troubling is the revelation that key economic advisers driving these policies aren't just operating against consensus—they're operating in a reality of their own creation. White House trade adviser Peter Navarro, a key architect of the tariff strategy, was revealed to have invented a fictional economics expert named "Ron Vara" (an anagram of Navarro) whom he repeatedly cited in his books as justification for aggressive tariff policies (Rachel Maddow, MSNBC, April 7, 2025).
As Maddow noted: "I mean, my name anagrams to Macho Wattler, but I don't see myself trying to talk you into doing what Macho Wattler wants, right?"
Models in Crisis
When policymakers fabricate experts, CEOs fear speaking truth to power, consumers make decisions based on tribal allegiance rather than economic self-interest, and media ecosystems amplify contradictory narratives, our economic models face a perfect storm of failure conditions.
The algorithmic trading systems that govern much of market activity cannot account for these dynamics. They weren't designed to. They assume a level of rationality, information integrity, and institutional stability that no longer holds.
Under these conditions, economic prediction becomes less about modeling market responses and more about modeling psychological reactions to increasingly incoherent signals. It's less about charting consumer utility curves and more about mapping fear, tribal alignment, and information disorder.
The Creative Destruction Endgame
What makes this scenario particularly concerning is the alignment with a philosophy of "creative destruction" long espoused by figures in and adjacent to the administration. This worldview, which gained prominence during Trump's first term, sees institutional collapse not as a crisis to be avoided but as a necessary precondition for rebuilding systems that better serve specific interests.
The simultaneous gutting of regulatory agencies alongside the expansion of unprecedented executive power creates a perfect environment for what economists call "regulatory arbitrage"—the exploitation of gaps in oversight for private gain. When those gaps are being actively widened by the same figures who stand to profit from them, the incentive structure becomes dangerously misaligned with public interest.
Consider the March 25 executive order directing the Treasury to "modernize and centralize its payment system" (Bloomberg, March 25, 2025). On its face, this appears to be a reasonable effort to reduce fraud. Yet when viewed alongside Musk's team gaining access to these very systems—despite serious security concerns that led to USAID officials being placed on leave for resisting similar access requests—a more troubling picture emerges.
The judge who ordered the release of DOGE records noted the operation has "led to the firing of tens of thousands of government employees" and gained "widespread access to sensitive government databases for relative outsiders." This isn't mere bureaucratic reshuffling—it's the systematic dismantling of institutional safeguards that have historically prevented the exploitation of public resources for private gain.
As billionaire Richard Branson warned on social media: "The US government can still turn things around, but it must act in the next few hours. This is the moment to own up to a colossal mistake and change course. Otherwise, America will face ruin for years to come" (CNBC, April 8, 2025).
The algorithms—both literal and metaphorical—that we've relied upon to navigate our economy are breaking down not because they were poorly designed, but because they were designed for a different reality than the one we now inhabit. And until we acknowledge this fundamental shift, we risk remaining perpetual "PANICANs," watching helplessly as markets and institutions built on rational actor theory crumble under the weight of deeply irrational forces—or worse, under the weight of rational actors pursuing irrational-seeming strategies that serve narrow interests at the expense of market stability and public welfare.
Chaos by Design: The Bolton Hypothesis
While this analysis has focused on economic and technological factors, it would be incomplete without considering a crucial perspective offered by one of Trump's own former appointees. John Bolton, who served as National Security Advisor during Trump's first term, characterized the president's approach to decision-making in a way that may shed light on current events.
In his memoir, "The Room Where It Happened," Bolton described Trump's policy process not as strategic chaos but as fundamentally unstructured: "Trump's decision-making was not organized as most people understand the term. He didn't operate on the basis of carefully prepared decision-making, many people participating, a set agenda... It's not how his mind works."
This perspective raises a significant question: Is the current economic turmoil a product of deliberately accelerationist philosophy, or simply the natural consequence of a decision-making approach that prioritizes immediate political and personal gain over long-term institutional stability?
The reality may lie somewhere in between. Even without a master plan for creative destruction, a governance approach that dismisses expertise, undermines institutions, and permits unprecedented conflicts of interest can produce results indistinguishable from intentional destabilization. When combined with the specific access granted to entities with clear conflicts of interest—like DOGE's access to Treasury payment systems or the Trump family's cryptocurrency ventures—the systemic risk multiplies regardless of intention.
As William Gibson famously observed, "The future is already here—it's just not evenly distributed." The same might be said for institutional collapse. The algorithms and safeguards designed to protect market stability are failing not all at once, but in an uneven cascade that makes the overall pattern harder to discern until it's too late to intervene effectively.
Whether by design or default, the result remains the same: a financial system increasingly vulnerable to manipulation, with traditional guardrails being systematically removed or circumvented while new, private alternatives position themselves to benefit from the resulting chaos.
References
Do your own research, but if it FEELS right, why bother 🤷
Verified by Alisha Rift - A long time friend and confidant of Ron Vara