🇺🇸 English version
This article proposes a new mechanism to integrate Real World Assets (RWA) into decentralized finance (DeFi) protocols. Using liquidity pools based on tokenized RWAs, we present a system that allows continuous valuation of RWAs on the blockchain, while providing a market-based source of variability for DeFi protocols. This mechanism aims to solve the problems of self-referentiality and excessive dependence on new entrants that affect many current DeFi protocols. We explore different implementations for various types of RWAs, including services, consumable goods, and unique assets. Finally, we discuss the implications of this system for the stability and efficiency of DeFi ecosystems.
- Introduction
Decentralized finance (DeFi) has emerged as a transformative force in the financial world, promising democratization of access to financial services and a redesign of traditional economic paradigms. However, as the DeFi ecosystem develops, it becomes evident that many protocols suffer from fundamental problems, notably self-referentiality and excessive dependence on new entrants to maintain their viability.
Self-referentiality manifests when the value generated by a DeFi protocol is primarily based on its own internal activity, without direct connection to value creation in the real economy. This phenomenon can lead to speculative bubbles and systemic instability. Dependence on new entrants, on the other hand, creates an unsustainable economic model that resembles a Ponzi scheme, where returns for existing participants are paid by investments from newcomers.
To address these issues, this article proposes a new mechanism that integrates real world assets (RWAs) into DeFi protocols. Using liquidity pools based on tokenized RWAs, we present a system that allows continuous valuation of RWAs on the blockchain, while providing a market-based source of variability for DeFi protocols.
The objective of this approach is twofold:
- Anchor the value of DeFi protocols in the real economy, thus reducing self-referentiality.
- Create a sustainable economic system that does not depend on a constant influx of new participants to maintain its viability.
In the following sections, we will explore in detail the functioning of this mechanism, its different implementations for various types of RWAs, and its implications for the DeFi ecosystem as a whole.
- Theoretical Foundations
2.1 The Theory of Liquidity Pools
Liquidity pools are at the heart of many DeFi protocols, allowing decentralized exchange of assets without requiring a direct counterparty. The most commonly used model is the Constant Product Market Maker (CPMM), popularized by Uniswap (Adams et al., 2020). In this model, the product of the reserves of two assets in a pool remains constant:
x * y = k
where x and y are the quantities of the two assets, and k is a constant.
This formula determines the relative price of assets in the pool and allows automatic exchanges based on supply and demand.
2.2 Tokenization of Real World Assets
The tokenization of RWAs involves creating digital representations of physical assets on a blockchain. This process allows traditionally illiquid or difficult-to-divide assets to become more accessible and tradable (Oliveira et al., 2018). Tokenization can apply to a wide range of assets, including real estate, artwork, infrastructure, and even services.
2.3 Theory of Liquidity and Price Formation
Liquidity plays a crucial role in asset price formation. According to Kyle's price impact theory (1985), market depth, which is a measure of liquidity, directly affects the sensitivity of prices to transactions. In our model, RWA-USDC liquidity pools serve as a price discovery mechanism for tokenized RWAs.
- The RWA Liquidity Pool Mechanism
3.1 Basic Structure
The proposed mechanism relies on creating liquidity pools for each type of tokenized RWA. Each pool is composed of a trading pair between the RWA token and a stablecoin (e.g., USDC). The basic structure includes:
- An RWA-USDC pool
- An initial ratio set by a market mechanism
- An Automated Market Maker (AMM) mechanism based on the CPMM model
3.2 Pool Operation
The pool operation can be described by the following equations:
- Constant product conservation equation: RWA_reserve * USDC_reserve = k
- RWA price in USDC: P_RWA = USDC_reserve / RWA_reserve
- Quantity of USDC received for a quantity Δx of RWA sold: Δy = (y * Δx) / (x + Δx)
where x is the RWA reserve and y is the USDC reserve.
- Slippage calculation: Slippage = (P_effective - P_spot) / P_spot where P_effective is the average price obtained for the transaction and P_spot is the price before the transaction.
3.3 Interaction with the Pool
Participants can interact with the pool in several ways:
a) Provide liquidity: Users can add RWA-USDC pairs to the pool in exchange for LP (Liquidity Provider) tokens.
b) Withdraw liquidity: LP token holders can exchange them for their proportional share of the pool's assets.
c) Exchange assets: Users can exchange RWAs for USDC and vice versa, paying fees that are redistributed to liquidity providers.
- Specific Implementations for Different Types of RWAs
4.1 RWA Representing a Service or Reusable Good
In this case, the RWA token represents usage rights for a service or reusable good. The mechanism works as follows:
a) Each RWA token gives the right to one unit of use of the service or good.
b) The token supply is limited, corresponding to the maximum capacity of the service.
c) Users must buy RWA tokens in the pool to access the service.
d) Service providers receive USDC in exchange for their service.
This system creates a natural market dynamic where demand for the service directly determines the price of the RWA token. The scarcity of tokens, limited by the service capacity, ensures that the price faithfully reflects the balance between supply and demand.
Mathematical modeling:
Let C be the maximum capacity of the service, U(t) the number of uses at time t, and P(t) the price of the RWA token at time t. We can model the price dynamics as follows:
dP/dt = α * (U(t)/C - β)
where α is an adjustment factor and β is a target utilization threshold (e.g., 0.8 for 80% utilization).
This differential equation captures the idea that the price increases when utilization approaches maximum capacity and decreases when it is well below the target threshold.
4.2 RWA Representing a Consumable Good
For consumable goods, we propose an auction mechanism integrated into the liquidity pool. The system works as follows:
a) Each RWA token represents one unit of the consumable good.
b) Producers put lots of goods up for sale via the pool.
c) Buyers bid in USDC to obtain RWA tokens.
d) Once the auction is over, winners receive their RWA tokens and can exchange them for the physical good.
This mechanism allows dynamic price discovery for consumable goods, reflecting fluctuations in supply and demand.
Mathematical modeling:
Let B(t) be the number of ongoing auctions at time t, H(t) the current highest bid, and D(t) the total demand (measured by the number of unique bidders). We can model the price evolution as follows:
dP/dt = γ * (H(t)/P(t) - 1) + δ * (D(t)/B(t) - ε)
where γ and δ are adjustment factors, and ε is a target ratio of bidders per auction.
This equation captures the idea that the price tends to increase when bids are high relative to the current price and when demand is strong relative to the supply of auctions.
4.3 RWA Representing a Unique Asset
For unique assets such as a building or a work of art, the token represents an associated service, such as rental or exhibition rights. The mechanism works as follows:
a) The RWA token represents a fraction of time of use or exposure of the unique asset.
b) Users buy RWA tokens to reserve usage periods.
c) The token price fluctuates based on demand for these periods.
Mathematical modeling:
Let T be the total number of periods available per year, R(t) the number of periods reserved at time t, and S(t) the seasonality (a factor between 0 and 1 representing the relative attractiveness of the current period). We can model the price as follows:
P(t) = P_base * (1 + μ * (R(t)/T) + ν * S(t))
where P_base is a base price, and μ and ν are adjustment factors for scarcity and seasonality respectively.
This equation captures the idea that the price increases with the occupancy rate and during periods of high seasonal demand.
- Integration into DeFi Protocols
The integration of these RWA liquidity pools into existing DeFi protocols can be done in several ways:
5.1 Source of Variability for Interest Rates
Price variations of RWAs in the pools can be used as a source of variability to adjust interest rates in DeFi lending protocols. For example:
r(t) = r_base + λ * (dP_RWA/dt)
where r(t) is the interest rate at time t, r_base is a base rate, and λ is an adjustment factor.
5.2 Collateral for Loans
RWA tokens can be used as collateral in lending protocols, with collateralization ratios adjusted based on the observed volatility in RWA pools.
LTV_max = θ * (1 - σ_RWA)
where LTV_max is the maximum allowed loan-to-value ratio, θ is an adjustment factor, and σ_RWA is the observed volatility of the RWA price.
5.3 Diversification of Reserves
DeFi protocols can diversify their reserves by including RWA tokens, thus reducing their exposure to purely cryptographic assets.
- Advantages of the System
6.1 Reduction of Self-Referentiality
By anchoring the value of DeFi protocols in real-world assets, this system significantly reduces self-referentiality. The generated returns are directly linked to the actual use and demand for tangible goods and services.
6.2 Increased Stability
The connection with the real economy can help mitigate the excessive volatility often observed in pure DeFi ecosystems. Price fluctuations of RWAs are generally less dramatic than those of speculative cryptocurrencies.
6.3 Attractiveness for Traditional Investors
The integration of familiar RWAs can make DeFi protocols more attractive to traditional investors, thus facilitating mainstream adoption of DeFi.
6.4 Real Value Creation
Unlike some DeFi protocols that merely redistribute value among participants, this system encourages real value creation by facilitating efficient access and use of RWAs.
- Challenges and Limitations
7.1 Regulatory Complexity
The tokenization of RWAs raises complex regulatory questions, particularly regarding the ownership and transfer of real assets via blockchain tokens.
7.2 Oracle for Initialization
Although the system aims to eliminate dependence on oracles for continuous price updates, an oracle may be necessary for the initial initialization of RWA liquidity pools.
7.3 Initial Liquidity
Attracting sufficient initial liquidity to RWA pools can be challenging, particularly for lesser-known or more niche assets.
7.4 Manipulation Risks
Like any system based on liquidity pools, there is a risk of price manipulation, particularly in less liquid pools.
- Implications for Monetary Policy in DeFi
The integration of RWAs into DeFi protocols via this mechanism has significant implications for conducting "monetary policy" in these ecosystems.
8.1 Natural Interest Rates
Interest rates in DeFi protocols can be more naturally aligned with real economic rates of return. For example, for a lending protocol using real estate RWAs as collateral, the interest rate could be modeled as:
r_DeFi = r_RWA + π + ρ
where r_RWA is the real yield observed in the real estate RWA pool, π is an estimate of inflation, and ρ is a risk premium.
8.2 Automatic Stabilization
RWA price fluctuations can act as an automatic stabilization mechanism for the DeFi ecosystem. For example, a decrease in demand for RWAs would lead to a decrease in DeFi interest rates, potentially stimulating economic activity.
8.3 Transmission of Monetary Policy
Actions of traditional central banks could have a more direct impact on DeFi ecosystems via their influence on RWAs. For example, an increase in interest rates could affect tokenized real estate prices, in turn influencing DeFi rates.
Conclusion
The proposed mechanism for integrating RWAs into DeFi protocols via liquidity pools offers a promising solution to the problems of self-referentiality and excessive dependence on new entrants. By anchoring the value of DeFi protocols in the real economy, this system can contribute to greater stability and efficiency of the DeFi ecosystem.
The different implementations for services, consumable goods, and unique assets demonstrate the flexibility of the mechanism. The integration of this system into existing DeFi protocols can improve price discovery, risk management, and asset diversification.
Although challenges remain, particularly in terms of regulation and initial liquidity, the potential benefits in terms of reducing self-referentiality, increased stability, and attractiveness to traditional investors are significant.
Future work:
- Develop more detailed mathematical models for each type of RWA
- Conduct simulations to test the robustness of the system under different market conditions
- Explore the legal and regulatory implications of RWA tokenization
- Study appropriate governance mechanisms to manage these systems in a decentralized manner
This mechanism represents an important step towards deeper integration between DeFi and the traditional economy, paving the way for a more inclusive, efficient financial system anchored in real value creation.