ResearchApril 2026~7 min read

Why the Bid Disappears

One of three reasons capital moves on chain is the promise of easier exit. Right now the exit is broken. Secondary markets for tokenized real world assets are thin, wide, or empty. This paper explains why.

1. How Market Making Works

A market maker posts two prices: a bid to buy and an offer to sell. The gap between them is the spread. Profit comes from flipping inventory: buy at the bid, sell at the offer, repeat. The faster the flip, the less time the market maker holds risk.

For the flip to work, the market maker needs balanced flow from counterparties who are not trading on private information. This is uninformed flow. A retail investor buying a BDC because the yield looks attractive is making a considered decision, but it is “uninformed” in that it is not based on undisclosed loan defaults or early delinquency data.

Informed flow is the opposite. A hedge fund selling ahead of a credit event it has already identified. An insider exiting before bad earnings. When a market maker trades against informed flow, it loses. The informed seller dumps at $10, the market maker buys, and by the time it tries to sell the price has dropped to $8. The informed trader captured the difference.

The business model depends on having enough uninformed trades to absorb the losses from informed ones. In liquid markets, this works. A market maker on the S&P 500 loses on a handful of informed trades but earns the spread on thousands of uninformed ones. The wins cover the losses.

2. Why Tokenized RWAs Kill the Bid

Most tokenized real world assets are offered under Regulation D, which limits participation to accredited investors. This is the structural feature that determines whether a liquid market can exist.

Accredited investors are, almost by definition, informed traders. They have access to research, relationships with issuers, and the sophistication to analyze credit risk. In a pool of exclusively accredited participants, the probability of any given trade being informed is well above the threshold where market makers start losing money.

The adverse selection spiral
1
Reg D restricts participation to accredited investors only.
2
The entire participant base is sophisticated and informed.
3
Toxic flow probability exceeds 30 to 40%. Realized spread turns negative.
4
Market makers lose money on average. They widen to stub quotes or leave.

Academic research measures this through PIN, the probability of informed trading. PIN estimates what fraction of trades come from participants with a private information advantage. When PIN exceeds roughly 30 to 40%, the cost of trading against informed counterparties exceeds spread revenue from uninformed flow. The realized spread turns negative. The market maker loses money on every trade on average. No business survives that.

There are no uninformed traders to offset the losses. No velocity from a broad base of participants buying and selling for rebalancing, income, or allocation changes. The market maker buys, holds, and hopes.

3. Silence as Signal

Standard detection tools like VPIN (volume synchronized probability of informed trading) measure order flow imbalance in volume buckets. PIN estimates informed trader proportion from order arrival rates. Both require thousands of trades to produce a meaningful result. In a market with three trades per day, the analysis is noise.

Why standard detection methods fail for low volume assets
VPIN
Measures order flow imbalance in volume buckets.
Buckets take hours or days to fill. Lags the event.
PIN
Estimates informed trader proportion from arrival rates.
Backward looking. Yesterday's estimate, not today's.
Amihud
Price impact per unit of volume.
Measures fragility, not intent.
Realized spread
Actual profit after post trade price movement.
Only measurable after the loss.

There is a signal that does not require volume at all: the gap between trades. In thin markets, the only reason someone shows up after hours of silence is that something changed. An off chain NAV updated. A credit event occurred. A redemption gate was announced. Prolonged silence followed by sudden activity is itself the indicator.

A smart contract can measure this directly. Time since the last trade is on chain state. Order size relative to pool depth is computable at execution. Both are available the moment the trade is submitted. The mechanism: scale the trading fee based on these two inputs. Long silence plus large order means higher fee. Recent activity plus small order means baseline fee. The elevated fee goes directly into the liquidity pool, compensating depositors for the higher probability that the trade is informed.

How the fee responds to context

Small trade, recent activity. Normal fee. Nothing unusual.

Large trade, recent activity. Elevated. Size carries risk, but the pool is turning over.

Large trade, long silence. Highest fee. This is the signature of informed flow in thin markets.

4. What Listed Wrappers Get Right

BDCs, CEFs (closed end funds), and mREITs (mortgage real estate investment trusts) hold the same loans and mortgages as tokenized products. They trade daily with real volume. The difference is structural.

Anyone with a brokerage account can buy a share. No accreditation check. No minimum investment beyond the share price. No platform specific onboarding. That open access brings retail flow, which is what keeps the bid tight.

But access alone is not enough. Retail shows up because the structural rules make the product trustworthy enough to hold.

Structural protections that bring retail to the table
Leverage caps
Prevent managers from taking outsized levered bets with investor capital.
Mandatory distributions
Force cash back to shareholders rather than letting managers reinvest indefinitely.
Independent valuation
A third party checks the marks. The issuer does not grade its own homework.
Public disclosure
SEC filings (10-K, 10-Q, 8-K) mean investors can see what they own and how it performs.

Without those protections, retail stays out. Without retail, the market maker has no one to flip to. The bid disappears.

5. What Tokenized RWAs Need

The exit path remains broken until tokenized products adopt the same structural protections that make listed wrappers work. Independent valuation that does not rely on the issuer marking its own book. Enforceable constraints on leverage and manager behavior. Transparent data on holdings and performance.

On chain infrastructure can deliver some of these. Observable state means anyone can verify holdings and positions without waiting for quarterly filings. Smart contracts can cap leverage, trigger distributions, and restrict manager actions programmatically. Validator networks can provide independent pricing from multiple parties rather than a single appointed valuation agent.

The access question is separate. Technology can solve trust. Access requires regulatory change, or a willingness to bear the cost of full SEC registration. Reg A+ opens the door to non accredited investors with a $75M cap and ongoing reporting. Full registration provides the widest access at the highest compliance cost. Both paths exist. Neither is free.

The problem is not that on chain markets lack technology. The problem is that Reg D products cannot generate the uninformed flow that market making requires. Until the participant base broadens, the bid will remain absent or priced at a discount steep enough to compensate for permanent adverse selection. Building the structural protections (leverage caps, independent verification, mandatory distributions) is how the participant base broadens. That is what makes exit possible, and exit is what makes lending against these assets viable at lower cost.

Sources

Easley, D., Kiefer, N., O'Hara, M., Paperman, J. (1996). “Liquidity, Information, and Infrequently Traded Stocks.” Journal of Finance, 51(4), 1405-1436.

Glosten, L. and Milgrom, P. (1985). “Bid, Ask and Transaction Prices in a Specialist Market with Heterogeneously Informed Traders.” Journal of Financial Economics, 14(1), 71-100.

Easley, D., Lopez de Prado, M., O'Hara, M. (2012). “Flow Toxicity and Liquidity in a High Frequency World.” Review of Financial Studies, 25(5), 1457-1493.

Hendershott, T. and Menkveld, A. (2014). “Price Pressures.” Journal of Financial Economics, 114(3), 405-423.

Amihud, Y. (2002). “Illiquidity and Stock Returns: Cross Section and Time Series Effects.” Journal of Financial Markets, 5(1), 31-56.

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