Technical Appendices

Mathematical Foundations

• Proof of Stability: The Thrupenny Protocol ensures stability by employing a unique equation that balances the liquidity pool, interest rates, and market demand. The stability proof is a result of in-depth mathematical analysis using rigorous methodologies.

• Optimization Techniques: The protocol utilizes numerical optimization techniques, such as gradient descent, to find the best parameters that suit different assets and market conditions. These techniques are proven to enhance efficiency and responsiveness.

Statistical Models and Analysis

• Risk Analysis: Quantitative risk assessments are carried out using statistical models like Value at Risk (VaR) and Monte Carlo simulations. These allow for predicting possible losses and applying necessary measures to mitigate risks.

• Market Predictive Models: Machine learning and time-series analysis are used to forecast market trends and asset price fluctuations. These predictions aid in making informed decisions within the protocol.

Algorithmic Details

• Liquidity Management Algorithms: Algorithms ensure an optimal level of liquidity by constantly analyzing market dynamics and user behavior. They utilize linear programming to balance supply and demand.

• Interest Rate Algorithms: Interest rates are governed by a set of well-defined formulas:

  • Borrow Rate: BR_t = (BR_base + U_t / U_optimal) * BR_slope1, if U_t < U_optimal

  • Variable Rate: VR_t = rate_of_variable_borrows_in_ray

Security Measures

• Smart Contract Audits: Regular audits are performed by third-party security firms, identifying potential vulnerabilities and enforcing best practices in smart contract coding.

• Encryption Techniques: State-of-the-art encryption methods, such as AES-256, are applied to safeguard sensitive data and ensure confidentiality.

System Architecture

• Interoperability with Other Protocols: Thrupenny's architecture is designed to seamlessly interact with major DeFi protocols and blockchain systems, ensuring smooth cross-chain transactions.

• Scalability Solutions: Scalability is achieved through the implementation of layer-2 solutions, allowing the protocol to handle increased user activity efficiently.

Additional Proofs and Definitions

In this section, we'll provide a comprehensive set of definitions for key variables and proofs for essential equations used within the Thrupenny Protocol.

Definitions

• Current Timestamp, T: The current number of seconds defined by the block.timestamp.

• Last Updated Timestamp, Tl: Timestamp of the last update of the reserve data, updated during specific events like borrowing, depositing, etc.

• Delta Time, ΔT: ΔT = T − Tl

• Total Liquidity of an Asset, L_asset_t: Represents the total amount of liquidity available in an asset's reserve.

• Total Stable Debt Token, SD_asset_t: The total amount of liquidity borrowed at a stable rate, represented in debt tokens.

• Total Variable Debt Tokens, VD_asset_t: Total liquidity borrowed at a variable rate, represented in debt tokens.

• Utilization Rate, U_asset_t: The utilization of the deposited funds, given by:

  • 0, if L_asset_t = 0

  • D_asset_t / L_asset_t, if L_asset_t > 0

  0 & \text{if } L_{\text{asset}_t} = 0 \\ \frac{D_{\text{asset}_t}}{L_{\text{asset}_t}} & \text{if } L_{\text{asset}_t} > 0 \end{cases} \]
• Health Factor, HF: A measure to identify undercollateralized loans, when HF < 1, a loan can be liquidated, given by: $HF=Collateral in ETH×LTassetCBx+Total Fees in ETHHF=CBx​+Total Fees in ETHCollateral in ETH×LTasset​​$
• User Principal Borrow Balance, PB(x): Balance stored when a user opens a borrow position, calculated as: $PB(x)=Principal+InterestPB(x)=Principal+Interest$

Proofs

• Proof of Interest Rate Stability: We can prove that the borrow rate algorithms are convergent and stable by demonstrating that the functions governing them are continuous and differentiable within a certain range. Borrow rate, $RassettRassett​​$, is given by:

  R_{\text{asset}_{\text{base}}} + \frac{U_{\text{asset}_t}}{U_{\text{asset}_{\text{optimal}}}} R_{\text{asset}_{\text{slope1}}} & \text{if } U_{\text{asset}_t} < U_{\text{asset}_{\text{optimal}}} \\ R_{\text{asset}_{\text{base}}} + R_{\text{asset}_{\text{slope1}}} + \frac{U_{\text{asset}_t} - U_{\text{optimal}}}{1 - U_{\text{optimal}}} R_{\text{asset}_{\text{slope2}}} & \text{if } U_{\text{asset}_t} \geq U_{\text{asset}_{\text{optimal}}} \end{cases} \]
• Proof of Liquidity Optimization: By utilizing a combination of linear programming and convex optimization, we can prove that the liquidity management algorithms are optimized for efficient utilization and minimal slippage. Total liquidity, $LassettLassett​​$, is optimized given: $Lassett=Lassetfree+LassetusedLassett​​=Lassetfree​​+Lassetused​​$
• Proof of Security Measures: Rigorous cryptographic proofs can be provided based on specific cryptographic functions used, e.g., hash functions or digital signature algorithms.

• Proof of Scalability: Through the application of layer-2 solutions and proper system architecture design, we can mathematically demonstrate that the system can handle increased loads without significant degradation in performance. Performance, $PP$, as a function of load, $LL$, can be represented as: $P(L)=11+e−k(L−x0)P(L)=1+e−k(L−x0​)1​$

These mathematical expressions, combined with the detailed definitions, provide a strong and clear understanding of the underlying mechanics of the Thrupenny Protocol. If additional formulas are required for specific functionalities or mechanisms, they can be incorporated as well.

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