How to Build Yield-bearing Prediction Markets

Table of Contents

1. What Are Yield-bearing Prediction Markets?
2. On-Chain Lending Strategies for Prediction Markets
3. Common Vulnerabilities
4. A Better Design: Wrapped Collateral Vault
5. Summary
6. About Us
7. FAQ

What Are Yield-bearing Prediction Markets?

Yield prediction markets, or yield-bearing prediction markets, are prediction markets that deposit the underlying collateral used to pay out bets into yield-generating strategies.

They often represent one of the few ways a prediction market can achieve meaningful and sustainable revenue for the company operating it.

In most cases, the collateral is deposited into DeFi lending protocols, which generate yield by lending assets to traders who pay interest on borrowed funds. This approach is attractive because it is DeFi-native and can generate between 3% and 6% APY on deposited stable assets under normal market conditions.

Prediction markets that implement such features include Predict.fun and Probable. In Predict’s example, over $20M is earning yield, generating approximately $600k per year for the team.

Yield prediction markets can also benefit lending protocols by providing a consistent and predictable flow of retail liquidity, with withdrawals typically tied to known market resolution dates.

Different On-Chain Lending Strategies Suitable for Prediction Markets

When choosing a yield strategy, it is important to understand the differences between available products. For this reason, we briefly recap the main transaction flows and features of a prediction market.

Minting Outcomes

The user deposits collateral into the market. If the Gnosis Conditional Token Framework (CTF) is used (as in Polymarket and most other markets), the collateral is transferred to the CTF contract, and the user receives a full set of outcome tokens.

The most important requirement is maintaining the invariant:

Total underlying collateral = Total amount of YES shares = Total amount of NO shares (full sets)

For example: A user calls split on the conditional token contract with 100 USDC as collateral and receives exactly 100 YES tokens and 100 NO tokens.

When the market resolves, the winning side can be redeemed for the full 100 USDC of underlying collateral.

This invariant must hold at all times.

Redeeming / Burning Tokens

When a market resolves, or if a user wants to redeem collateral early, they can burn a full set of outcome tokens to withdraw the underlying collateral.

After resolution, users can claim winnings by burning the winning token to receive an equivalent amount of collateral. Most Polymarket forks hardcode a 1:1 payout ratio for winning tokens.

From this structure, several unique conditions emerge:

• Large, predictable withdrawals when markets resolve
• Smaller, consistent withdrawals when no high-TVL markets are active
• Long-duration markets (often months or years)
• Deposited and withdrawn tokens must always match outcome token supply
• Centralized orderbook with on-chain settlement

Choosing the right yield source is therefore critical for secure system design.

Yield Sources in DeFi

Yield sources generally fall into the following categories:

1. Crypto-based lending Lenders are exposed to crypto market volatility. Examples include Aave, Venus, and Morpho pools such as ETH/USDC.

2. RWA-based lending (Real-World Assets) Lenders are exposed to tokenized real-world assets such as treasury bills or private credit. Examples include specialized pools on Euler or Morpho integrating protocols such as Midas.

3. Stablecoin hedge funds / strategy vaults Lenders fund active trading strategies. These may also be deployed through Morpho or Euler vaults.

The choice of yield source ultimately lies with the development team. However, certain yield sources introduce structural risks that may amplify vulnerabilities discussed later in this article.

Comparison of Yield Sources

Yield Source	Typical APY	Liquidity Risk	Price Volatility Risk	Bad Debt Risk	Suitability for Prediction Markets
Crypto Lending Pools	2–8%	Medium–High	Medium	Medium	Moderate (careful monitoring needed)
RWA Lending Pools	3–6%	Medium	Low–Medium	Medium–High	Risky for strict collateral invariants
Strategy / Hedge Vaults	5–15%	High	Medium	High	Generally not recommended

Common Vulnerabilities

The unique structure of prediction markets introduces intrinsic risks when integrating yield strategies. These risks can vary in severity depending on implementation.

High-Risk: Liquidity Issues in Underlying Markets

Lending markets typically restrict withdrawals under two conditions:

• Bad debt
• Liquidity shortages (high utilization)

If bad debt occurs or protocol fees are activated, users may receive fewer assets than requested. This breaks the invariant that collateral must always equal the number of outstanding outcome tokens.

If utilization is high and all liquidity is borrowed, withdrawals may fail due to insufficient liquidity. Even if the lending protocol remains solvent, this temporarily blocks withdrawals and prevents efficient market making and claims, leading to poor user experience.

For this reason, RWA-based yield sources can be particularly risky. While they may promise steady returns, they can experience temporary price declines. For example:

• 1-year treasury bills may decline in mark-to-market value before maturity.
• Off-chain private credit strategies may incur bad debt that reduces vault share prices.

Similarly, on-chain hedge funds should be treated with caution, even if they offer higher APYs.

Medium Risk: Unpredictability of Future Lending Conditions

Lending protocol conditions can change drastically over time. Prediction markets may remain open for over a year (e.g., “What will the Bitcoin price be in 2026?”).

If the underlying lending protocol experiences liquidity stress or bad debt during this period, it can heavily impact trading, redemptions, and user confidence.

Medium Risk: Rounding Issues in Deposits and Withdrawals

Most lending protocols introduce rounding behavior:

• ERC-4626 vaults typically round minted shares down and burned shares down.
• Some protocols (e.g., Aave-style accounting) may round in the opposite direction.

While usually negligible, strict 1:1 collateral invariants make rounding significant. Over time, rounding discrepancies can:

• Cause temporary insolvency
• Allow value extraction in low gas environments
• Create revert conditions that affect order settlement
• Enable subtle price manipulation

This risk is increased when many small deposits are followed by one large withdrawal. For example, consider a vault that rounds every deposit down:

A user deposits 10 tokens and receives 9 shares per deposit, repeating this 5 times. Later, the user attempts to withdraw 50 tokens. Due to rounding, the required shares are calculated as 49, but the user only holds 45 shares.

In the case of conditional tokens, where the exact balance must be withdrawn, this mismatch would cause the transaction to revert.

General Integration Risks

Integrating lending protocols introduces additional attack vectors:

• Access control misconfigurations
• Incorrect token or pool selection
• Empty market exploits
• Curator risks in vault-based systems (read more)
• Deployment configuration mistakes

Different chains may introduce additional risk due to:

• Low gas fees (amplifying rounding exploits)
• Higher TPS
• Chain-specific features

Minor Risks

Prediction markets were originally designed to be decentralized. Even though centralized orderbooks and resolution already introduce trust assumptions, yield integration adds further risks:

• Rebalancing authority
• Emergency withdrawal permissions
• Disabling yield strategies
• Treasury yield claims

Improper governance design can increase protocol risk.

Medium Severity Risk for Lending Protocols

Large, single-day withdrawals can temporarily stress lending markets.

For example, if a 2028 presidential election market holds $200M in TVL, the lending protocol could experience up to $200M in withdrawals on the resolution day.

The advantage is that resolution dates are known in advance, allowing institutional borrowers to prepare by repaying loans. This may, however, become an important consideration for borrowers in the future, as approximately 10% of the USDT pool on Venus is expected to originate from prediction markets.

A Better Design

Oot2k has audited multiple prediction markets in collaboration with Sherlock DeFi, Bailsec Security, and independently, including two projects ranked among the top five in TVL and volume. The inspiration for this design originated from trying to fundamentally fix issues found in both audits.

He proposes a new design that mitigates many of the risks above without modifying the original Polymarket core contracts.

Wrapped Collateral Vault

Most issues described above stem from accounting mismatches:

• CTF assumes a fixed 1:1 exchange rate.
• Vaults issue shares that fluctuate in value.

This mismatch forces prediction market implementations to manually account for rounding errors and yield fluctuations.

The Solution

Deploy a wrapped collateral vault that:

• Wraps yield-bearing tokens
• Returns a stable, non-value-increasing token
• Internally manages exchange rate and accounting

This removes the need to modify Polymarket contracts and isolates risk management to the wrapper vault.

Enforced Invariants

The wrapped vault enforces:

1. Exchange rate can never increase above 1, but can decrease → Prevents bank runs or accounting breaks if underlying protocols activate fees or incur losses.

2. Yield claims can never reduce principal below deposited collateral → Prevents the protocol from withdrawing user principal.

3. Liquidity buffer is maintained → Allows controlled exposure to underlying strategies and smoother withdrawals.

Losses, if they occur, are correctly passed to users instead of breaking invariants.

Simplified Pseudo-Implementation (ERC-4626 Based)

Not production-ready. For illustration only.

... 
    /// @notice Total assets reported to ERC4626, capped at `principalDeposited` to keep the share price stable.
    function totalAssets() public view virtual override returns (uint256) {
        uint256 assets = totalAssetsWithYield();
        if (assets > principalDeposited) {
            assets = principalDeposited;
        }
        return assets;
    }

    /// @notice Withdraws `assets`, pulling from the yield source if idle liquidity is insufficient.
    function withdraw(
        uint256 assets,
        address receiver,
        address owner
    ) public virtual override returns (uint256) {
        uint256 availableLiquidity = idleAssets();

        if (availableLiquidity < assets) {
            uint256 missing = assets - availableLiquidity;
            _withdrawFromSource(missing);
            //Might burn more shares due to rounding, should be balanced by previewWithdraw as it rounds up
        }

        return super.withdraw(assets, receiver, owner);
    }

function rebalance() external onlyOwner {
    ....
}

function claimYield() external onlyOwner {
  ...
  require(totalAssetsWithYield() > principalDeposited, "Insolvent");
}

For the full implementation view: https://github.com/Oot2k/PrincipalOnlyVault

The exact implementation requires careful consideration of rounding, share accounting, yield harvesting, and loss scenarios. It should not be deployed without extensive audits and formal verification.

For detailed design and security considerations, contact oot2k.
Special thanks to ihtishamSudo for the valuable suggestions and feedback on this article and code.

Summary

Yield-bearing prediction markets can significantly improve protocol revenue and capital efficiency. However, they introduce complex risks related to liquidity, accounting invariants, rounding behavior, and lending protocol instability.

A properly designed wrapped collateral vault can:

• Preserve 1:1 collateral invariants
• Isolate yield-related risk
• Prevent accounting mismatches
• Improve long-term protocol safety

Careful architecture and thorough audits are essential before deploying such systems in production.

About Us

SCAS is a smart contract security and research firm focused on DeFi security audits and economic attack modeling.

We specialize in lending protocols, prediction markets, vault systems, and complex cross-protocol integrations.