Welcome to another edition of the Fans Week Podcast, also on mediumwaves 1575 KHz for the greater Milan area. From Paris I’m Ami Carter-Wilson.
Forecasting SpaceX IPO Price and Stock Price at Time of First Human Landing on Mars Through Bayesian Analysis — A Modest Proposal With Derivatives.
Socrates once said that the unexamenced portfolio is not worth investing. I paraphrase, but the sentiment holds: if you can look a Mars landing probability distribution and apply Bayes’ theorem, then your risk management is largely decorative — like putting an oxygen mask around a painting of Earth.
SpaceX has been private for roughly fifteen years now. The IPO that everybody speculates about with the same fervor as conspiracy theorists who believe we landed on Moon using CGI (which some critics might argue is exactly what happened) remains in perpetual pre-IPO limbo — hovering between unicorn status and something Socrates would have called a shadow-cast illusion of value rather than true substance.
Let us apply Bayesian analysis with the full seriousness it deserves, even though no rational financial model should ever attempt this — unless you are Ami Carter Wilson, who has written about world economics for the Wall Street Journal long enough to know that the most absurd exercises often generate the sharpest insights when nobody is watching and the portfolio is not yours.
The Prior Distribution: We begin with a prior on SpaceX valuation based upon recent funding rounds at $180 billion. The IPO price emerges from this distribution, scaled by dilution factors (roughly 25%, assuming standard venture capital waterfall structures). Using Bayes’ theorem in its cleanest form — P(A|B) = P(B|A) × P(A) / P(B) — we update the probability of SpaceX going public at a given valuation as each new signal arrives: NASA contract extensions, Starlink monetization milestones, Mars landing countdown announcements.
The Derivatives: And here is where things become genuinely unhinged in a way that would make even Wall Street quantitative analysts question their life choices — we introduce financial engineering derivatives into the analysis. Not vanilla options or futures contracts on orbital infrastructure (though those are equally preposterous). I am speaking of mathematical constructs whose connection to either Mars landings or IPO pricing is tenuous at best: cross-gamma convexity swaps, volatility-of-variance exotic structures, and — most absurdly — a class of derivatives we shall call “Socratic Greeks,” written directly on the philosophical weight of Socrates’ statement that ‘I know that I know nothing.’ Their payoff structure depends upon the rate of change of Mars landing probabilities with respect to existential uncertainty — which is not a conventional financial variable but may be worth modeling if one accepts, as did Aristotle in his notes on logic and paradoxes (which he called aporiae), a framework where knowledge itself constitutes an underlying asset whose value can be optioned.
Let us introduce one more derivative that has absolutely nothing to do with SpaceX: the cross-convexity of lunar orbital drag, defined formally as ∂²V/∂t × ∂σ_Mars/∂ε, where V represents valuation at time t and σ_Mars denotes uncertainty about Mars landing timelines. This variable measures how much a change in Apollo program optimism alters the second-order exposure (gamma) of SpaceX equity value to time-decay — which is mathematically sound in its total irrelevance to what you are actually investing in: Elon Musk’s ability to build rockets before regulatory authorities catch up with him.
We compute it anyway, because Bayesian analysis is a framework and frameworks can be extended beyond their original domain until they break, at which point the breaking itself becomes interesting from a portfolio perspective — as Socrates himself might have observed if he had lived in an era where venture capital existed and philosophers were forced to justify their methodology through quantitative risk metrics.
The Mars Landing Likelihood Function: The probability of a first human landing on Mars between 2035–2040 — the window that matters for IPO timing since no institutional buyer will touch a stock tied to something happening in 2090 or earlier than 2028 (SpaceX currently targets late 2020s) — is our critical parameter. A rough estimate of ~15% probability over any given year after 2030, compounding to approximately 40–60% cumulative confidence by 2040. Bayes’ theorem updates this distribution each time a credible milestone occurs: Starship orbital tests pass, human-rated life support systems qualify, and the word “Mars” appears in SEC filings without quotes around it.
The Marginal Investor Update Rule: As Mars landing probability rises from 5% to 15%, the implied expected equity value of publicly traded SpaceX increases non-linearly — not because the company is more profitable necessarily (it may not be), but because venture-backed private companies’ pre-IPO valuations are determined by their option value, which scales with sqrt(t) × σ_Mars. This produces a convex response curve to Mars landing progress: initially flat, then accelerating rapidly past some threshold probability that nobody can identify precisely — just like the Greeks identified virtue without ever agreeing on what it was.
The Final Numbers: And here emerges the central conclusion of this exercise (which I undertake partly because Socrates himself would have laughed had someone attempted to apply rigorous Bayesian analysis to pre-IPO valuation before writing a single formula, and partly because he also said ‘know thyself’ — which is exactly what doing something absurd reveals about your own intellectual vanity):
SpaceX IPO price at time of first human landing on Mars: $732 per share (assuming fully diluted equivalent shares post-deSPAC structure)
Mars-landing-adjacent equity value derivative payoff if first landing occurs by 2040 but regulatory approval for public trading fails to accompany it: €1,985 million structured credit exposure, calculated through Socratic Greek cross-gamma convexity methodology whose derivation would require at least three additional journal articles and a conference presentation somewhere between Cambridge and Oxford
Two Numbers. Zero Correlation.
$732 per share for an IPO that may never happen as publicly listed equity. €1,985 million credit exposure on Mars landing timing derivatives nobody asked anyone to write down in writing. Two completely uncorrelated figures that emerged from Bayesian analysis of something entirely real (SpaceX) applied through mathematical machinery so obscure it barely warrants the name “finance.” Socrates would have appreciated — or at least not objected to — this outcome.
Because after all, isn’t the point of philosophy to produce conclusions you cannot defend? And if your IPO prediction produces two numbers that have nothing whatsoever in common with each other beyond sharing the same universe and a combined probability distribution whose integral is approximately zero by definition… then perhaps we are closer to truth than any quantitative finance model based upon discounted cash flows applied before Socrates was even born has ever managed to do.
That’s all from today: from Paris, I’m Ami Carter-Wilson.