I spent the first part of my career as an institutional fund manager, and the first thing that job teaches you (the thing no model teaches you) is that valuation and pricing are two different questions.

Valuation is theoretical. Given assumptions about future cash flows and a discount rate, what is this thing worth in present-value terms? That’s the exercise the last two posts were about (post 1 and post 2). Pricing is something else. Pricing is empirical, it’s what buyers and sellers are transacting at, right now, in the market in front of you. The model gives you the first number. The market gives you the second. And the gap between them is where most of the interesting things happen.

What the value trap taught me

In the fund management world, valuation was an input to the decision. It was never the decision. The textbook version is simple: buy when a stock is cheap against its valuation, sell when it’s expensive, wait for price to revert to value. The theory says reversion happens over time.

The theory is right. The problem is “over time.” Over time can be a very long time, and the model that tells you a gap exists tells you nothing about when it closes.

Price has its own momentum, and it can run away from value for years in either direction. Growth stocks had a habit of trading expensive against any defensible valuation and staying there, momentum carrying them well past the point a discounted-cash-flow model said was sensible, for far longer than anyone short of them could survive. And the mirror image: a stock could trade cheap against its valuation for years, the model insisting it was a bargain the whole way, the reversion never arriving on any timescale you could use. That second one has a name: the value trap. Being right about the valuation and wrong about the timing loses you money exactly as efficiently as being wrong about the valuation.

The lesson stuck. A valuation model is a statement about where price should end up. It is silent on the only question that pays you: when.

The decimal places are a lie

It gets worse, because the model meant to arbitrate all this isn’t even precise to begin with.

I made this point in the last post, but it stacks up across three independent layers. First, the valuation itself: every input is a wide band, the target return is a tail event, and the whole thing carries a factor-of-something sensitivity that no amount of computation removes. Second, pricing then diverges from even that wide range, persistently, on norms and anchoring and geography that have nothing to do with the discounted exit. Third, the reversion that’s supposed to discipline the gap runs on no schedule you can name.

So you have a number with a wide error bar, a market price floating free of even that, and no clock on the gap between them. And the model hands it all back as a single confident figure with decimal places. Worse than unhelpful: the precision actively misleads, dressing three stacked uncertainties as one tidy answer. As a fund manager you learn to distrust the decimal places. As an angel you learn it again, harder, because early-stage is where the gap between precision and reality is the widest.

Why startups are the worst case

A growth stock at least has earnings you can argue about and a sentiment cycle that eventually breaks one way or the other. The reversion is unreliable, but there’s a mechanism to point to.

An early-stage startup has neither. The entire value sits in a terminal event years out, and the probability of reaching it at all is a wide distribution, as the first post laid out. When the value being computed is that uncertain and that distant, pricing floats almost entirely free of it. What sets the number a founder and investor transact at isn’t a discounted exit. It’s the comparable deals visible locally, the accelerator’s standard terms, the recursive anchoring of whatever the last few rounds cleared at. The valuation model is in the room, but it isn’t setting the price. The market’s local habits are.

Which sounds like an argument for never acting on a price/value gap at all. And mostly it is, as most gaps fail you on timing, so you can’t trade them. But there’s one exception, and it’s the one the whole Australian angel opportunity has been built on.

The one gap with an address

The exception is a gap whose reversion has a known trigger: you can see the event that closes it coming rather than waiting on an unknowable sentiment shift.

Geographic arbitrage is that case. The same company, at the same stage, prices differently depending on where it raises. Early-stage companies in the United States have long priced well above equivalent companies in Australia, which in turn price above their New Zealand equivalents.

Part of that premium is real, and the last post explains exactly why. Large exits are the upward force on early-stage valuations: the fatter and more frequent the right tail, the more an early entry is worth. And the US tail is genuinely fatter: more acquirers, deeper capital, and bigger and more frequent large exits. So by the same mechanism that holds Australian valuations up, US valuations are held higher. That part of the premium reflects the fat-tail force from the last post, applied to a market with bigger exits: genuine value, not market inefficiency. The same company really is worth more there, because the distribution it’s being measured against has a heavier tail.

But only part of the premium is that. The rest is the local-anchoring effect from the section above, running at the level of whole countries. An Australian company prices off Australian comparables because that’s what the local market can see. This is not because its own potential exit distribution is genuinely smaller, but because the local market has never been shown the bigger one. That portion of the gap is pure pricing, not value. And it’s the portion you can arbitrage.

Here’s what makes this gap different from a value trap: you know exactly when it closes. It closes when the company raises a US round. It’s a locatable event, often one you can see coming at the point you invest. You’re holding an asset priced locally, with a clear repricing moment ahead of it. The reversion has an address.

What that’s worth and why the number survives

Recall the company from the last post, entered by an Australian syndicate at a $3.5M pre-money. Now it does the thing the strategy is built around: it crosses over and raises its Series A from US institutions. To do that credibly it reincorporates as a Delaware C-Corp and the founders relocate; the capital follows the founders, the founders follow the capital. It raises that round at $14M pre-money, priced off US comparables. A 4x repricing at the Series A alone, and the business has done little except change which market is looking at it.

Now follow two investors to the same $300M exit, both measured in their pocket, after dilution.

• The US Series A investor entered at $14M, late enough to suffer only modest further dilution, and keeps a healthy slice to exit. On a $300M exit they make something like 12x on their money. A very good result.
• The Australian angel entered at $3.5M, far earlier, and takes the full dilution of every round after — keeping, as the last post described, roughly a third of their original position by exit. On the same $300M exit they make something like 25x.

Same exit, same company, and same dollar of exit value. One makes 12x, the other 25x, and roughly half that difference is the geographic repricing, the rest is the earlier, cheaper entry. The Australian angel didn’t pick a better company. It’s the same company. They bought it in a market that couldn’t yet see what it would become.

And notice the thing that matters most, given everything in the last post about how little the precise valuation is worth. That 25x doesn’t depend on getting the discount rate right. It survives every bit of the model’s imprecision, because it isn’t computed from a valuation at all. It comes from two things you can actually know: the price you paid to get in, and the repricing event you could see coming. In a framework where almost nothing survives contact with a sensitivity band, those are the two facts that do.

A window that won’t stay open

Which brings the fund manager’s lesson back around. The aggregate gap between Australia and the US, as whole markets rather than this one company, is itself a pricing inefficiency. And every pricing inefficiency between two markets that can see each other reverts over time. This is the same mechanical reversion the theory always promised. The only question, as ever, is the timescale.

You can already watch it happening at home. The Brisbane-versus-Sydney gap that once put founders on planes has largely closed over the past decade: national syndicates, Zoom-era fundraising, and accelerators with national reach have all compressed the information asymmetry that held it open. A strong Brisbane company no longer reincorporates in Sydney to get Sydney pricing. The capital travels to it.

The Australia-to-US gap is on the same road, maybe a decade behind. As more Australian companies raise US rounds and post strong exits, US funds get more comfortable pricing them closer to domestic equivalents, and the spread narrows.

• Brisbane versus Sydney: largely closed already
• New Zealand versus Australia: still pricing cheap, the way Brisbane once did against Sydney
• Australia versus US: significant, narrowing, but a material gap still remaining

The value trap taught me that price reverts to value eventually, and that “eventually” is the whole problem. You can be right about the gap and still wait a decade for it to pay. Geographic arbitrage is the rare inversion of that: a gap you can act on, because for once you can see what closes it. The irony is that the same reversion working in your favour on each deal is, in aggregate, closing the opportunity itself. The angels who built their books while the differential was wide will have captured something the next generation won’t get on the same terms. The cheapest part of the whole opportunity was always the part the local market couldn’t yet see, and the moment everyone can see it, it’s already gone.

Richard Moore — MooCoo Ventures

Richard Moore is co-founder of MooCoo Ventures, an angel syndicate that co-invests alongside Brisbane Angels, one of Australia’s most active angel groups. He has made over eighty personal angel investments since 2013.

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