The article at a glance: We offer novel insights into borrowing, leveraged trading and price dynamics of real asset-backed tokens on the blockchain, resulting from the interaction between on-chain lending platforms and tokenized asset markets. We document the credit channel in Decentralized Finance (DeFi) as a potential source of short-term price fluctuations in tokenized real asset markets.
Credit Cycles in Tokenized Real Estate Asset Markets
By Daniel Ruf, CERF/CCFin Fellow, Department of Land Economy, University of Cambridge
Tokenization of traditional real word assets
In a new research project, which is a joint work with Wenqian Huang from the Bank for International Settlements (BIS) and Valerie Laturnus from Durham University Business School, we study how DeFi lending markets impact leveraged trading behaviour and price dynamics in tokenized real estate markets. Tokenization of traditional real-world assets (RWAs), such as stocks, bonds, commodities, or real estate has gained momentum, due to growing interest from Wall Street, reaching a current on-chain market value of around $30billion ($4billion of real estate) by the end of September in 2025. Furthermore, the integration with DeFi lending platforms allows investors to deposit real asset-backed tokens as collateral for customized leverage. Yet, no formal empirical analysis exists on the transmission mechanism between DeFi lending and tokenized RWA markets.
Comparison with Traditional Finance
We draw comparisons with traditional finance in real estate markets, where looser credit conditions can lead to inflated house prices - further magnified when property values are used as collateral (Favara and Imbs, 2015; Adelino et al., 2025). As seen during the global financial crisis, negative feedback effects resulting from house price declines can then lead to market instability (e.g., DiMaggio and Kermani, 2017).
Tokenized Real Estate: A blockchain ecosystem as a laboratory
Our dataset contains the full sample of on-chain real estate token transactions from RealT. Typically, RealT as tokenizing company purchases buy-to-let properties, such as single family homes or condominiums, and creates for each asset a separate limited liability company (LLC) as legal owner. Fractional ownership of the LLC is then sold as digital token on the blockchain, allowing investors to obtain the rent income generated by the underlying asset (Baum, 2020). Often, rent collection is outsourced to external management companies. The property value is reappraised periodically, which can lead to corresponding changes in token prices. The buyback price accepted by RealT (adjusted for direct and indirect transaction costs) is tied to the most recent off-chain appraisal value of the property.
Investors can also trade their real estate tokens on secondary markets, such as digital decentralized exchanges (DEXs), e.g., Levinswap on the Gnosis blockchain. Investors can swap real estate tokens for stablecoins, such as wxDAI on multiple existing liquidity pools. Token prices are determined by an automated pricing algorithm (a so-called automated market maker) to keep a constant product of both types of assets available in the pool (see, e.g., Harvey et al. 2024; Lehar and Parlour, 2024). RealT also launched an offer-based peer-to-peer (P2P) marketplace, called YAM (You-and-Me), where investors can initiate buy or sell offers to exchange real estate tokens.
Integration with DeFi Lending
In April 2022, RealT also launched the RealT Money Market (RMM). This lending platform allows investors to deposit their real estate tokens as collateral to borrow stablecoins, while retaining their claim on the rental income. During the first RMM version, only 53 selected real estate tokens were eligible as collateral. Following the launch of the updated version in February 2024, all available real estate tokens can be used as collateral. The time-varying borrowing (and lending) interest rates are determined by demand and supply in the pool, i.e., by how much of the pool’s stablecoins, deposited by lenders as liquidity providers, are being borrowed by investors. When demand for loanable stablecoins increases, the borrowing interest rate rises. The lending rate adjusts accordingly as an incentive for potential lenders to deposit additional loanable stablecoins. When the pool has a large amount of loanable stablecoins, but a limited number of borrowers, borrowing and lending rates decrease to attract more potential borrowers. Borrowers must maintain a 120-150% overcollateralized position of their deposited collaterals. When the collateral value declines, relative to the outstanding debt, borrowers either repay part of their debt or must deposit additional real tokens as collateral. When the collateral value falls below the threshold value, the loan can be liquidated by other investors (Heimbach and Huang, 2023).
Transmission Mechanism between on-chain lending and real estate token prices
We document a credit channel resulting from the interaction between the DeFi lending platform and on-chain secondary market platforms, such as DEX liquidity pools and P2P trading. Our empirical findings suggest that borrowing activity is associated with increased trading volume and higher token prices. An increase in leveraged trading can result in temporary upward price pressures during trading days, with a significant price impact on DEX liquidity pools and price premiums relative to the dealer’s buyback price. Most notably, the value of the collateral that can be used to pledge against loanable stablecoins is tied to the most recent appraisal value of the underlying property. Exploiting exogenous variation, resulting from a positive appraisal change of the underlying asset, we show that large borrowers who observe an appraisal shock in their deposited collateral portfolio increase their borrowing activity compared to borrowers who do not own and hold the corresponding token as deposited collateral.
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Baum, A. (2021) “Tokenization – the future of real estate investment?” Journal of Portfolio Management, 47(10): 41-61.
DiMaggio, M. and A. Kermani (2017) “Credit-induced boom and bust” Review of Financial Studies, 30(11): 3711-3758.
Favara, G. and J. Imbs (2015) “Credit Supply and the Price of Housing” American Economic Review, 105(3): 958-992.
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