Real-Time Private Market Price Discovery

The thesis that 24/7 continuous trading is the most accurate long-term mechanism for pricing private companies, and that the current regime of discrete, infrequent price events creates a fundamentally ambiguous, and often wrong, valuation.¹

The price ambiguity problem

A private company at any moment has at least three distinct correct prices that can diverge materially: the last fundraising round price, which is the most cited benchmark but may be years old and may not reflect progress made since; the secondary transaction price, what shares actually changed hands for privately, often significantly higher than the last round price for high-growth companies that have not needed to raise; and the hypothetical public price, what the market would pay if the company were public, shaped by public market multiples and sentiment.

Vlad Tenev flags this directly: is the proper value the price of the last round of fundraising, when sometimes there have been secondary transactions at a much higher price, and of course, if the company were public, the price would be different again.¹ None of these is the price. The ambiguity is structurally inherent to how private markets work.

The proposed solution

The preferred answer is that real-time, 24/7 price discovery is itself the most accurate mechanism, not as an approximation of some real price sitting elsewhere, but as the process that generates the price in the first place. This is the same logic behind public markets generally: there is no external correct price that the market approximates, the market price is the price. The problem is that private companies are exempt from this process by choice, and that choice generates the ambiguity described above.¹

The consent barrier

The solution has not been implemented because companies do not want it. Continuous real-time price discovery converts private status from a strategic choice, no disclosure requirements, no short-term market pressure, no volatility in the employee stock-price mental model, into something closer to public exposure without the formal transition. Real-time trading invites short sellers before a company has had the chance to manage its own narrative, volatility in a live price affects employee morale and compensation benchmarking, and disclosure pressure tends to follow price discovery once investors want to understand movements. This is why the project is treated as a five to ten year undertaking rather than a product launch: early adopters normalize it first, and eventually companies that have not done it start to look like they are hiding something.¹

The institutional route, on a calendar

Marc Rowan is executing a parallel version of the same thesis at the largest private credit manager in the world, and he has attached actual dates to it: daily estimated value across the investment-grade private credit suite by June 30, extended across the entirety of the credit business by the end of September, standardized information and identifiers, standardized data warehouses, and market making with regular public disclosure of prices.² "Value alone is not enough, this is about creating an ecosystem." And the strongest single statement of the underlying thesis: "I've never seen a market in the world where you have transparency and price discovery that is not 10 times its size. It may be uncomfortable for people, but it's coming." Equity convergence is explicitly next but not yet, in his words, not this year's business. Rowan had previewed the shift eighteen months earlier, in November 2024: "My gut tells me over the next 18 months investors will really coalesce around this idea of fixed income and dividing it between alpha and beta,"³ a forecast that lines up almost exactly with the dated commitments above.

Two things this route adds that the Tenev framing does not. Daily pricing is not daily liquidity: a daily mark without daily redemption is the entire safety margin, and conforming to public-market buyers must not create unacceptable mismatches between risk and reward. And it answers a structural objection to holding private, unpriced assets on an insurance-style balance sheet, marked by the entity that originated them, since a voluntary daily mark removes exactly the defense a critic would look for trouble in.

Why credit moves first, and what equity is waiting for

The reason convergence starts in credit rather than equity is external certification: credit has rating agencies that can tell a portfolio manager a given position is of a certain risk grade, which turns the remaining question into one of liquidity rather than valuation. Equity has no equivalent rating agency, which is why equity convergence sits years out, and why both routes to it, tokenization and institutional market-structure reform, are attempts to manufacture the missing certification by different means.³

The claim that reframes the comparison

The usual framing treats the private-markets pricing problem as ambiguity measured against a clean public-market benchmark. The stronger version of the argument is that the public benchmark is worse than assumed: there is little real liquidity in public fixed income markets today, with market-making capital at roughly 10 percent of its 2008 level against a market three times the size, and as long as five days required to sell even an investment-grade corporate bond in the best of conditions.³ The convergence predicted runs from both directions at once: private investment grade becomes continuously priced, public investment grade is revealed to have been less liquid than its quotes implied, and the two meet in the middle.

Relationship to other structures

Synthetic perpetual contracts on private companies are a crypto-native attempt at continuous price discovery, but a missing short side and thin liquidity mean persistent premiums, undermining accuracy relative to what genuine two-sided trading would produce. Prediction markets are a sibling structure: open continuous trading as a better epistemic engine than periodic expert estimates, applied to a different class of institutionally opaque questions.

Open questions

If real-time price discovery is the accurate solution, does the price still represent fair value when the market is thin, with few participants and low float, since thin markets can be manipulated more easily than deep public ones? Does a company's consent to real-time trading require simultaneous disclosure obligations, since trading without disclosure is trading without being fully informed? And at what point does the consent barrier actually flip from resistance to expectation?