building-interest-rate-markets-in-defi

Building Interest Rate Markets in Decentralized Finance: A Comparative Analysis with the Traditional Financial System

1. Introduction

Over the past year, I had the opportunity to speak with people who work on developing financial contracts for transacting digital assets peer-to-peer, and I realized that in these peer-to-peer financial markets, also called decentralized markets, there is no interest rate market as solid and generally accepted, which prevents, among many other factors, the widespread use of this technology and similar ones.

The construction of interest rate markets and their application in peer-to-peer financial contracting represents a necessary area of research in the context of the growing integration of blockchain technologies into the financial system.

Decentralized Finance (DeFi) promises greater transparency, inclusion, and efficiency. By exploring how interest rate markets and yield curves are built and operate, solid foundations will be established for evaluating the interest rates available in the market, as well as their determinants.

Interest Rate Markets

Interest rate markets play a crucial role in the economy, affecting the savings, investment, and consumption decisions of individuals and businesses. The construction of these markets revolves around benchmark interest rates, such as the Federal Funds Rate in the United States, established by the central bank. These benchmark rates serve as the base cost of money, influencing all other interest rates in the economy, from mortgage loans to corporate bonds.

The monetary policy transmission mechanism, through which the central bank influences the economy, involves changes in the benchmark rate to affect inflation and economic growth. Commercial banks adjust their own lending and deposit interest rates in response to these changes, thus impacting the supply and demand for credit. Bond markets, where debts of different maturities are traded, reflect the market’s expectations about the future direction of monetary policy and the economy, thus forming yield curves.

The need for intermediation or central counterparties gives rise to the existence of banks, and the service they provide is also the reason why banks operate with a spread between funding and lending rates. In principle, peer-to-peer financial markets, supported by AMM (Automatic Market Makers) can reduce the need for these intermediaries, and the law of one price opens the possibility of offering consumers better terms for their financial contracts.

Decentralized Finance (DeFi)

Decentralized Finance (DeFi) represents a market that eliminates intermediaries in financial transactions through the use of smart contracts on public blockchains. Unlike traditional systems, in DeFi there is no central entity that dictates interest rates. Instead, these are determined through algorithmic mechanisms that may include the supply and demand of digital assets, the liquidity available on platforms, and the perceived risks associated with the loans and financial products offered.

Yield curves in DeFi, although more complex to infer due to cryptocurrency volatility and the diversity of protocols, offer a unique view of market participants’ expectations and the financial health of DeFi platforms. Given that blockchains are public and smart contracts transparent, there is unprecedented potential to analyze in real time how these rates and curves form, providing a window into the efficiency of decentralized financial markets.

Justification for the Study

Understanding how interest rate markets are built in this new environment, and how they compare and contrast with traditional financial systems, is fundamental for regulators, investors, and market participants. Additionally, this study could contribute to the development of policies and strategies to mitigate risks, ensure financial stability, and promote responsible innovation in the financial sector.

2. Literature Review

Theories on the Determination of Spot Interest Rates and Yield Curves

In traditional finance, several theories explain how spot interest rates and the shape of yield curves are determined:

1. Expectations Theory: Holds that the yield curve reflects the market’s expectations about future interest rates. According to this theory, an ascending yield curve indicates that future spot interest rate increases are expected.
2. Market Segmentation Theory: Proposes that debt markets are segmented by maturity, meaning that the supply and demand of funds for different terms are independent. This independence can explain the differences in interest rates for different maturities.
3. Liquidity Preference Theory: States that investors prefer more liquid assets (short-term) and, therefore, demand a premium for holding less liquid assets (long-term), which can generate an ascending yield curve.
4. Risk Premium Theory: Suggests that yield curves reflect an interest rate risk premium, which compensates investors for the risk of changes in interest rates that affect the value of long-term bonds.

Role of Asset Pricing Theories

Although certain explicit rates exist in the economy, these are not representative of the completeness of interest rates that are contracted. These are determined by other factors, for which an analysis of implicit interest rates is interesting.

The Lucas model, an example of asset pricing theories, plays a crucial role in understanding how asset prices and interest rates are determined in an equilibrium setting. This model uses rational expectations and marginal utility of consumption to derive asset prices as a function of their expected future payment or dividend flows. Under this framework:

• Prices and Discount Rates: Asset prices are determined by the discounted present value of their future payment flows, where discount rates reflect consumers’ time preferences, risk aversion, and future economic expectations.
• Yield Curves and Asset Pricing: In this context, yield curves can be seen as reflecting expectations about the future evolution of the economy and interest rates, as well as the risk premiums that investors demand for holding assets with different maturities.

3. Theoretical Framework

I. On Financial Contracts

Financial contracts are legal agreements between two or more parties that establish the conditions and terms for conducting financial transactions. These contracts may include loan agreements, derivatives contracts, futures contracts, financial options, among others. Their main objective is to establish the rights and obligations of the parties involved in the transaction, as well as the payment terms, deadlines, interest rates, and other relevant details.

The execution of financial agreements is guaranteed through different mechanisms. In the case of decentralized financial contracts (DeFi), execution is based on automation through smart contracts on a blockchain. Smart contracts are computer programs that execute automatically when certain predefined conditions are met.

These smart contracts ensure compliance with the terms and conditions established in the financial contracts. Being based on decentralized technology such as blockchain, the need for intermediaries is eliminated and the risk of fraud or manipulation is reduced. Once the agreed conditions are met, such as the maturity of a loan or the price of a derivative reaching a certain level, the smart contract is activated and automatically performs the corresponding actions, such as transferring funds or liquidating positions.

This automated and transparent execution of decentralized financial contracts provides trust and efficiency in transactions, as it eliminates the need to rely on third parties and reduces the time and costs associated with traditional intermediation.

According to generally accepted accounting principles, the characteristics that define a right and an obligation of a financial contract are the following:

1. Right: A right in a financial contract implies that one of the parties has the power to obtain future economic benefits as a result of the contract. This economic benefit can be in the form of cash, goods, or services. The right may arise due to a contractual agreement or as a result of applicable laws or regulations.
2. Obligation: An obligation in a financial contract implies that one of the parties has the responsibility to perform a future action or transfer economic resources to another party. This obligation may arise due to a contractual agreement or as a result of applicable laws or regulations. The obligation may involve the payment of cash, the delivery of goods, or the provision of services.

It is important to note that the rights and obligations in a financial contract must be measurable and have a reasonable probability of occurrence. Additionally, they must be properly recognized and recorded in the financial statements in accordance with applicable accounting principles.

Decentralized financial contracts (DeFi) do not imply a different emergence or origin compared to traditional financial contracts. In both cases, contracts may arise in formal or informal markets, and they establish the terms and conditions for conducting financial transactions.

The difference lies in the method of execution. In decentralized financial contracts, execution is based on automation through smart contracts on a blockchain. This eliminates the need for intermediaries and reduces the risk of fraud or manipulation. Smart contracts guarantee compliance with established terms and conditions and are automatically activated when predefined conditions are met.

In summary, decentralized financial contracts do not change the emergence or origin of contracts but rather offer a more efficient and transparent form of execution through blockchain technology and smart contracts.

e.g. 1

The most common financial contract is the loan contract. This type of contract establishes the terms and conditions for lending or borrowing money. It includes details such as the loan amount, interest rate, repayment term, and associated guarantees. Loan contracts are widely used in financial transactions to finance projects, acquire goods, or cover liquidity needs.

A simple loan contract is defined as one that contains the necessary legal elements for the contract’s validity. These elements include:

1. Consent: Both parties, the lender and the borrower, must give their free and voluntary consent to establish the loan contract. This means that both parties agree with the terms and conditions established in the contract.
2. Object: The loan contract must have a determined and lawful object. In this case, the object is the loan of a specific amount of money from the lender to the borrower.
3. Cause: The cause refers to the reason or motivation behind the loan contract. In this case, the cause is the borrower’s interest in obtaining an amount of money and the lender’s interest in receiving repayment with interest.
4. Legal capacity: Both the lender and the borrower must have the legal capacity to enter into the loan contract. This means they must be of legal age and have the mental capacity necessary to understand and assume the terms and obligations of the contract.
5. Written form: Although not strictly necessary in all cases, it is recommended that the loan contract be made in writing to avoid misunderstandings and future conflicts. The written form provides clear evidence of the terms and conditions agreed upon by both parties.

It is important to mention that these elements may vary according to the laws and regulations of each jurisdiction. Therefore, it is advisable to consult with a legal professional to ensure compliance with the specific requirements of each country or region.

In the case of decentralized financial contracts, the written form can be augmented with the programming of a contract on a blockchain. By using smart contracts on a blockchain, the ability to guarantee execution conditions can be enhanced. This is achieved by programming the transfer of assets upon fulfillment of the obligations established in the contract. In this way, the execution of decentralized financial contracts is automated, eliminating the need to trust third parties and reducing the risk of manipulation or non-compliance.

The way this contract is programmed is not the main object of analysis of this text; rather, it seeks to theoretically explain the implications of its use based on how they are observed in practice, and to financially explain how much value it generates compared to a traditional financial contract.

II. On Interest Rates

1. Fundamentals of Interest Rate Determination

Interest rates are determined by multiple factors that reflect economic conditions, market expectations, and monetary policies. In this context, interest rates can be modeled as a function of:

• Inflation expectations: Future inflation expectations affect nominal interest rates, according to Fisher’s theory.
• Monetary policy: Central bank decisions on benchmark rates have a direct impact on the market.
• Supply and demand of funds: The interaction between the supply of savings and the demand for loans determines interest rates in a free market.
• Credit risk: The perception of default risk affects the interest rates demanded by lenders.

2. Multifactor Model for Interest Rates

A multifactor model for interest rate determination could incorporate macroeconomic variables (such as GDP, inflation, and unemployment), financial variables (such as differences in short-term and long-term interest rates, and risk premiums), and DeFi market-specific variables (such as protocol liquidity and digital asset volatility). This model can be expressed as:

$[r_t=\alpha +{\beta }_1{X}_{1t}+{\beta }_2{X}_{2t}+\cdots +{\beta }_n{X}_{nt}+{\epsilon }_t]$

t

=

α

β

1

X

1

t

β

2

X

2

t

+⋯+

β

n

X

n

t

ε

t

where $(r_t)$ is the interest rate at time $(t),(\alpha )$ is the intercept, $({\beta }_i)$ are the coefficients of the independent variables $(X_{it})$, and $({\epsilon }_t)$ is the error term.

3. The Lucas Model

The Lucas model, centered on the optimal allocation of consumption under uncertainty, provides a theoretical basis for understanding how rational expectations and intertemporal decisions affect asset prices and interest rates. In the context of interest rates, the model can be adapted to reflect how expectations about the future economy and risk preferences influence interest rates through the asset pricing mechanism.

4. Stochastic Processes in Interest Rate Determination

Stochastic processes, such as Brownian motions and Poisson jumps, can be used to model the uncertainty and dynamic behavior of interest rates over time. These processes allow incorporating risk and volatility into interest rate modeling, providing a deeper understanding of their behavior in uncertain environments.

5. Econometric Application

To estimate the multifactor model, econometric techniques such as multiple linear regression, vector autoregressive models (VAR), or error correction models (ECM) can be used, depending on the nature of the data and the relationship between variables. The choice of method depends on the stationarity of the time series, the existence of long-term relationships between variables, and the temporal dynamics of interest rates.

Theoretical Framework Conclusion

This theoretical framework provides a solid foundation for investigating interest rate determination, integrating classical economic theories with advanced modeling and econometric analysis methods. By applying this framework to DeFi markets, one can explore how the unique characteristics of these markets affect interest rate determination and how they compare to financial markets.

4. Hypotheses on the Structure and Functioning of Interest Rate Markets in DeFi

The development and evolution of Decentralized Finance (DeFi) present a distinct paradigm from traditional financial markets, particularly in the determination and management of interest rates. This paradigm shift suggests that market dynamics in DeFi may require significant theoretical adjustments to apply traditional concepts such as benchmark rates and yield curves. Based on this premise, we formulate the following hypotheses:

Hypothesis 1: Effect of Digital Asset Collateralization on Interest Rates

“In DeFi markets, interest rates for loans collateralized with digital assets will be lower than in traditional markets due to the greater liquidity and ease of liquidation of digital assets, along with the possibility of automatic execution of contractual clauses for collateral management.”

Justification:

• Digital assets offer intrinsic liquidity and liquidation capabilities that surpass those of traditional assets, which reduces risk for the lender.
• Smart contract automation enables the efficient execution of clauses such as automatic liquidation, margin maintenance, and collateral reloading, further reducing risk and, therefore, the required interest rates.

Hypothesis 2: Rate Adjustment to Reflect the Legal Nature of Tokens

“Interest rates in DeFi will need to be higher to compensate for the legal risks and transaction costs associated with converting tokens to fiat currency, given the lack of recognition of tokens as legal tender in most jurisdictions.”

Justification:

• Legal and regulatory uncertainty surrounding tokens and crypto-assets adds significant risk, which is reflected in higher interest rates.
• Transaction costs associated with conversion between crypto-assets and fiat currency can be substantial, depending on market liquidity, volatility, and exchange platform fees.

Additional Considerations for Research

These hypotheses suggest a research approach that encompasses both technical aspects of smart contracts and collateral management in DeFi, as well as broader legal and economic considerations affecting interest rates. Validating or refuting these hypotheses will require detailed empirical analysis of DeFi market data, comparisons with traditional financial markets, and an evaluation of the legal frameworks applicable to cryptocurrencies and digital assets.

This multifaceted approach will not only enable understanding the differences between DeFi and traditional markets in terms of interest rates but will also offer insights into how decentralized financial infrastructures can be more effectively integrated into the global financial system, addressing legal, regulatory, and market challenges.

5. Methodology

To validate your hypotheses on how the structure and functioning of interest rate markets in DeFi might differ from traditional markets, and what theoretical adjustments are necessary to apply concepts such as benchmark rates and yield curves in the DeFi context, it is crucial to adopt a rigorous and well-structured methodology. The methodology must allow you to collect and analyze data in a way that lets you empirically test the claims of your hypotheses. Here are the key components you should consider and develop in your methodology:

1. Data Selection

Identify and define the types of data you need to test your hypotheses. For DeFi, this could include lending and deposit interest rates, information on automatic liquidations, transaction volumes, and data on transaction costs for conversion between crypto-assets and fiat currency. For traditional markets, you might need interbank interest rates, mortgage lending rates, and other relevant data.

2. Data Sources

Specify the sources from which you will obtain the data. In the case of DeFi, blockchain platforms and cryptocurrency data aggregators are primary sources. For traditional financial market data, you can turn to institutional economic and financial databases such as the Central Bank, the IMF, or the Federal Reserve.

3. Analysis Methodology

Define how you will analyze the data to test your hypotheses. This may include:

• Descriptive Analysis: To obtain an overview of interest rates and other relevant indicators in both markets.
• Empirical Comparison: Compare interest rates and market conditions between DeFi and traditional financial systems using statistical methods.
• Econometric Modeling: Use econometric models to investigate the relationship between interest rates and the determinant factors identified in your hypotheses. Regression models, VAR models, or time series models may be appropriate depending on the nature of the data and research questions.

4. Ethical and Data Quality Considerations

Ensure you consider ethics in data collection and use, especially with sensitive or personal data. Also, evaluate the quality and representativeness of the data to ensure that the results are valid and reliable.

5. Hypothesis Testing

For Hypothesis 1: Effect of Digital Asset Collateralization on Interest Rates

• Automatic Liquidation Rate: Data on the frequency and conditions under which automatic liquidations are triggered in smart contracts. This may indicate the efficiency and security of digital collateral.
• Volatility of Digital Assets Used as Collateral: Measuring the volatility of digital assets can help understand the perceived risk and its impact on interest rates.
• Average Collateral Liquidation Time: A proxy for the liquidity and ease of liquidation of digital assets.
• Interest Rates for Collateralized Loans in DeFi vs. Traditional: Directly compare interest rates for collateralized loans in both systems to evaluate the difference attributable to digital asset collateralization.

For Hypothesis 2: Rate Adjustment to Reflect the Legal Nature of Tokens

• Transaction Costs for Token-to-Fiat Conversion: Data on the fees and costs associated with exchanging crypto-assets for fiat currency.
• Price Spread Between Exchange Platforms: This may indicate market frictions and implicit conversion costs.
• Token Regulations and Legal Status in Different Jurisdictions: An index or classification of the legal status of tokens can serve as a proxy to measure the regulatory impact on interest rates.
• Legal Risk Premium: Difference in interest rates that could be attributed to the legal risk associated with using tokens not recognized as legal tender.

6. Methodology Limitations and Considerations

Acknowledge the limitations of your methodology and how these might affect the interpretation of your results. This may include limitations in data availability, the applicability of statistical methods, and the generalization of your findings.

When developing your methodology, it is important to maintain a critical perspective and be prepared to adapt your approach based on data and preliminary findings. Clarity and transparency in your methodology are essential for the credibility of your research.

6. Analysis and Results

Evaluate how differences in interest rate determination affect the behavior of market participants, price formation, and risk in both systems.

7. Discussion

Discuss whether it is necessary or beneficial to have direct equivalents to REPO rates and yield curves in DeFi, and how these could be implemented technically and theoretically.

8. Conclusions and Recommendations

Conclude on the theoretical adjustments necessary for the application of benchmark rates and yield curves in DeFi, and how these adjustments could influence the future development of decentralized financial markets.

9. Future Lines of Research

Suggest areas for future research, such as the development of more sophisticated economic models for rate setting in DeFi or the practical implementation of liquidity management instruments similar to REPO on decentralized platforms.

This research approach would not only contribute to the academic understanding of decentralized finance in relation to the traditional financial system but could also offer practical insights for DeFi developers, regulators, and market participants.