🇺🇸 English version
Traditional monetary policy equations, when applied to the context of Decentralized Finance (DeFi), can offer insightful lessons on the specificities of the DeFi ecosystem and provide guidance on building more stable applications and incentives. By analyzing these traditional equations through the lens of DeFi, we can extract principles for stability, efficiency, and sustainability in a decentralized financial landscape.
Quantity Theory of Money: MV = PQ
- Lesson for DeFi: The relationship between the money supply (M), velocity of money (V), price level (P), and output (Q) highlights the importance of managing the supply and demand of DeFi tokens. For DeFi, maintaining stability might involve mechanisms to adjust the supply of tokens or to stabilize their velocity through staking or locking mechanisms, which can affect the overall stability and price level within the ecosystem.
- Application to DeFi: Implement algorithmic supply adjustments (similar to mechanisms used in stablecoins) or introduce utility that encourages the long-term holding of tokens to manage velocity and supply effectively.
Fisher Equation: i = r + π
- Lesson for DeFi: The relationship between nominal interest rates (i), real interest rates (r), and inflation (π) underlines the importance of considering inflationary pressures within the DeFi ecosystem. DeFi platforms can build more stable applications by incorporating expectations of inflation into the interest rates offered on lending and borrowing.
- Application to DeFi: Design interest rate models that are responsive to changes in the underlying asset’s value or the platform’s token, potentially through automated adjustment mechanisms that account for inflationary or deflationary trends.
Taylor Rule: i = r + π + 0.5(π−π) + 0.5(Y−Y)
- Lesson for DeFi: The Taylor Rule, which guides adjustments in interest rates based on deviations from target inflation and output levels, suggests that DeFi platforms could benefit from rules-based approaches to manage interest rates. Such approaches could help stabilize the DeFi ecosystem by making borrowing costs more predictable and aligned with market conditions.
- Application to DeFi: Develop smart contracts that adjust lending and borrowing rates based on real-time data regarding inflation in the token ecosystem and deviations from desired economic activity levels.
Liquidity Preference Theory: M/P = L(iY)
- Lesson for DeFi: The demand for money in relation to the interest rate and income levels (or in DeFi terms, the demand for liquidity in relation to yield opportunities and the platform’s economic activity) can inform how DeFi platforms structure incentives for liquidity providers. Balancing liquidity provision with attractive, yet sustainable, yields is crucial for long-term stability.
- Application to DeFi: Use dynamic yield strategies that adjust rewards for liquidity providers based on the total value locked (TVL) and current liquidity needs, ensuring that liquidity provision remains attractive but does not lead to excessive speculation.
Implications for DeFi Stability and Incentive Design
- Risk Management: Incorporate mechanisms for automatic risk adjustment, including overcollateralization rates and liquidation thresholds that respond to market volatility.
- Governance and Policy Rules: Adopt governance structures that enable responsive and flexible policy adjustments, akin to monetary policy adjustments by central banks, to maintain platform stability and user confidence.
- Transparency and Predictability: Emphasize the importance of transparency in monetary policies and algorithmic mechanisms, making it easier for users to understand the risk-return profile of participating in DeFi platforms.
- Incentive Alignment: Ensure that incentives for all participants (lenders, borrowers, liquidity providers, and governance token holders) are aligned with long-term platform health and stability, rather than short-term gains.
By drawing lessons from traditional monetary policy equations, DeFi can build a foundation for more stable and sustainable financial applications that better manage the complexities of a decentralized economy. These principles can guide the development of mechanisms that
promote stability, efficiency, and growth within the DeFi ecosystem.
Note on the Taylor rule for DeFi protocols :
Because in DeFi, there is no revenue mechanism, the production factor Y doesn’t exist. The incentive structure of the DeFi protocols makes the interest rate the sole product of the protocol : that is, in DeFi, the equation replaces Y-Y* by the difference between r* and the target interest rate.
The adaptation of the Taylor Rule for Decentralized Finance (DeFi) by replacing the output gap (Y − Y*) with the difference between the natural real interest rate (r*) and the target interest rate suggests an attempt to tailor monetary policy tools to the unique conditions of DeFi. In this adaptation, rather than focusing on the output gap typical of traditional economies, the focus shifts to aligning the DeFi ecosystem’s interest rates with an optimal or “natural” rate that balances supply and demand for funds without causing inflationary or deflationary pressures.
This approach, while innovative, does indeed risk becoming somewhat self-referential if the target interest rate itself becomes a primary variable in determining adjustments. The target rate, in this context, is both an outcome of policy and a determinant of policy actions, which could lead to circular reasoning or policy feedback loops that are difficult to stabilize.
Proposed Revision for a DeFi-Adapted Taylor Rule
To mitigate the self-referential nature and ensure a more stable and effective framework for setting interest rates in DeFi, the equation could be revised to incorporate external or additional economic indicators that reflect the health and stability of the DeFi ecosystem
as well as the broader cryptocurrency market. Considerations might include:
- Volatility Index: Incorporate a measure of the volatility of the platform’s primary asset or the broader cryptocurrency market. High volatility could signal the need for higher interest rates to curb speculative borrowing.
- Total Value Locked (TVL) Growth Rate: TVL can be a proxy for demand within the DeFi platform. A high growth rate might suggest increasing demand, justifying higher rates, while a stagnating or declining TVL might indicate lower demand, suggesting a need to lower rates to stimulate activity.
- Liquidity Ratios: Consider the ratio of available liquidity to outstanding loans. A lower ratio might indicate a tighter market, suggesting the need to increase interest rates to attract more liquidity providers.
- Market Sentiment Indexes: Incorporate broader market sentiment, possibly derived from social media analysis, trading volumes, or other indicators that reflect the general mood of the cryptocurrency market.
By integrating these or similar factors, a revised DeFi-adapted
Taylor Rule could look something like this:
Where: - it is the
target interest rate. - r* is the natural real interest rate, possibly estimated by long-term platform growth expectations or the risk-free return rate in the crypto market. - πt is the
current inflation rate in the platform’s token value or borrowing costs.
- π* is the target inflation rate, aiming for stability in token value. - Vt, TVLgrowth, Lratio, and St represent the new variables: Volatility at time t, TVL growth rate, Liquidity
ratio, and Sentiment index, respectively. - λ is a function defining how these additional factors adjust the interest rate, ensuring it reflects broader economic signals rather than relying solely on the internal target rate.
Implementing the Revised Rule
To implement this more nuanced approach, DeFi platforms would need robust data analytics capabilities to continuously monitor these indicators and adjust the target interest rate accordingly. This might involve:
- Automated Data Feeds: Utilizing oracles or other trusted data sources to provide real-time information on market conditions and sentiment.
- Smart Contract Algorithms: Developing smart contracts capable of interpreting these data points and automatically adjusting interest rates in response to changes.
- Governance and Oversight: Ensuring that there’s a mechanism for human oversight, possibly through decentralized governance, to adjust parameters, validate data sources, and intervene in case of market anomalies or manipulation.
By incorporating a broader set of economic indicators, DeFi platforms can create a more stable and responsive interest rate policy that supports sustainable growth and minimizes the risks associated with purely internal reference points.