LST Yield Parameters and Collateral Composition

LST Yield Distribution

The protocol provides the flexibility to distribute the LST yield of the stablecoin reserves across different smart contracts. This enables targeted incentives for liquidity based on the protocol's objectives (e.g., increasing USC and CHI liquidity). The current parameters are configured as follows and can be adjusted to align with the protocol's specific goals.

CHI Stakers USC Stakers CHI Lockers CHI Vesters USC/ETH LP CHI/ETH LP







Example: Allocating 0.25 of the LST yield to CHI stakers means that 25% of the total LST yield is sent to stCHI.

Securing Funds and Conducting Diligence: The Foundation of Chi Protocol

The Chi Protocol allows the use of various Liquidity Staking Tokens (LSTs) as collateral to mint USC, the world’s first scalable stablecoin with intrinsic yield. To ensure that the collateral of USC is safe and diversified, Chi Protocol has established a robust framework for safeguarding funds, facilitating the expansion of asset diversity, and preparing for unforeseen events.

Chi's Comprehensive Due Diligence Process for Onboarding New LSTs

Adding new LST assets as collateral in Chi Protocol carries inherent risks that require due diligence and management. Despite the minting process and dual stability mechanism, vulnerabilities or incompatibilities within the collateral assets can potentially introduce complexities. Chi Protocol has implemented a dual-layer due diligence process to address these challenges involving the core Chi Protocol technical team and the Chi DAO. This process consists of two pivotal stages:

  1. Due Diligence by the Chi Protocol Core Team: Every LST undergoes an exhaustive due diligence examination led by Chi's core team members. This evaluation includes a comprehensive assessment of various asset aspects, including reward mechanisms, security, safety track record, market measures and technical specifications. The objective is to ensure the asset's security and compatible integration with Chi Protocol.

  2. DAO Voting Process: The ultimate decision rests with the Chi DAO, ensuring transparency, accountability, and democratic involvement. LST providers are required to submit thorough proposals, which undergo subsequent discussions. Subsequently, the DAO votes to determine whether to accept the asset and establish the percentage of the protocol's reserves (reserves portion) to be allocated to the LST. Through the establishment of diversification, the DAO effectively manages the associated risk for each asset.

Post-launch, the DAO retains the flexibility to continually adjust the reserves fraction of each LST or take measures such as deactivation or asset removal should unforeseen risks materialize. This dynamic approach ensures that risk management remains adaptable and responsive to emerging information and circumstances.

Risk Analysis and Methodology

The DeFi's composability allows Chi Protocol to integrate with the broader ecosystem. Nevertheless, this interconnectedness also exposes the protocol to various ecosystem-related risks. The tokens accepted as collateral are pivotal in determining the protocol's financial stability. Evaluating whether an asset introduces excessive risk to Chi Protocol involves considering at least three key aspects: smart contract risk, counterparty risk, and market risk.

Initially, the Chi community should focus on assessing the security of smart contracts and the potential risks arising from counterparties. If these risks are perceived to be unacceptably high, it is advisable to disqualify the tokens in question from usage within the Chi Protocol. Subsequently, the Chi community should maintain ongoing vigilance in monitoring risks, particularly market-related ones, which can be effectively managed through the protocol's adjustable reserves parameters.

Risk Assessments and Quantification Criteria

The Chi Protocol team has developed the following risk assessment scale as a helpful reference tool for the Chi community when conducting asset risk analysis.

The risk scale spans from the lowest risk (A), representing the safest assets within the protocol (e.g., ETH), to the highest risk (C). Assets exposed to elevated risk factors (C) should not qualify as collateral.

Asset Scale Final Score


14 - 21


7 - 13


1 - 6

Quantitative Risk Assessment

Historical data can be quantified in three distinct dimensions of risk as outlined below:

  • Smart Contract Risk and Activity: Measured by the number of days and transactions.

  • Counterparty Risk: Quantified based on the number of holders and permission settings.

  • Market Risk: Assessed through metrics such as market capitalisation, average trading volume, and normalised volatility.

  • Other Inherent Risks: Based on the type of asset. If this is an LST, it is important to analyze the performance of the price with respect to its underlying asset.

These ratings are computed for each sub-factor and then aggregated using a rounded-up average to account for diversification benefits

Score Days (Maturity) Transactions (Activity)1 Month Average Volume ($)Holders (Decentralisation)Market Cap ($)Liquidity ($)Volatility vs ETH (7 Days)Volatility vs ETH (30 Days)Volatility vs ETH (1 Year)









































Smart Contract Risk and Activity

The maturity of any code is assessed based on the number of days and transactions with a particular smart contract. These proxies can be used to quantify how battle-tested the code is.

Smart contract risk measures the technical security of the underlying code for any asset. Only codes for assets that have undergone rigorous audits by well-respected auditors are appropriate for Chi protocol. Beyond audits, smart contract risk remains (i.e., it can never be eliminated), and users must be vigilant in assessing such risk. Bug bounties can be used to help reduce smart contract risk.

The one-month average volume ($) is used as an indicative figure to assess the trading activity of single assets. Volume can also be used as a complementary measure of liquidity risk.

Counterparty Risk

Counterparty risk is determined by the level of centralisation, measured by the number of parties that control a token's protocol, as well as the number of holders and the level of trust in the entity, project, community or processes.

Counterparty risk assesses qualitatively how and by whom the asset is governed. Different degrees of governance decentralisation may give direct control over funds (e.g., as backing and number of node operators) or attack vectors to the governance architecture, which could expose control over funds. All risks must be carefully considered and analyzed when proposing a new asset.

Market Risk

Market risks are linked to the size of a particular asset and fluctuations in supply and demand. The markets need sufficient liquidity for efficient trade execution within the pool (i.e., exchange LST assets for ETH to meet the ETH buffer).

We compute volatility risk for each asset based on normalised fluctuations of the token price, and it is calculated as the standard deviation of logarithmic returns: σ(ln (close(t+1)/ close(t)). These values are assessed over different time intervals (one week, one month, and one year), with the volatility of ETH used as a benchmark.

Tokens scoring one or below in any of these categories are very risky, making them poor-quality collateral, and they should not qualify as valid collateral assets.

History of De-pegs

De-peg history is an essential factor in evaluating market risks of synthetic assets, as it functions as both quantitative (number of de-pegs) and qualitative (economic reason for de-pegs) measure of assets performance over time. Negative scoring rules are applied to this factor, and careful consideration should be given to assets with a de-peg history. For assets with no history of de-pegs, no points are deducted; for those with one and more than one de-peg, 3 and 6 points are respectively deducted.

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