Risk Management and Market Integrity
Data Feed Categories
At eOracle, we've implemented a comprehensive categorization system for our data feeds. This system is designed to inform users about the intended use cases of each feed and highlight potential market integrity risks associated with data quality. Our goal is to provide you with the information needed to make informed decisions when integrating eOracle feeds into your applications.
It's important to note that all feeds published in eOracle's documentation undergo rigorous monitoring and maintenance, adhering to the same high standards of quality. Each feed is subject to a thorough assessment process during implementation. The specific assessment criteria may vary depending on the type of feed being deployed and may evolve over time as our understanding of market integrity risks deepens.
We group our data feeds into the following categories, ranked from lowest to highest level of market integrity risk:
✅ Low Market Risk
🟡 Medium Market Risk
⭕ High Market Risk
⚙ Custom Feeds
🔭
This categorization serves as a guide to help you understand the relative risk profile of each feed. However, we encourage users to conduct their own due diligence and risk assessment when integrating any data feed into their smart contracts or applications.
By providing this transparent categorization, eOracle aims to empower developers and projects with the knowledge they need to build robust, risk-aware decentralized applications. Remember, the appropriate use of a feed depends on your specific use case and risk tolerance.
Key Risk Factors by Market Integrity Risk
| Market Integrity Risk - Key Factors | ✅ Low Market Risk Feeds | 🟡 Medium Market Risk Feeds | ⭕ High Market Risk Feeds |
|---|---|---|---|
Market Events | Highly resilient to disruption | Ongoing market events (e.g., token migrations) | Significant market events (e.g., hacks, bridge failures, major exchange delistings) |
Price Feeds Stability | Use numerous data sources | The price spread between trading venues | Asset/project market deprecation |
Trading Volume | Consistent price discovery due to high volumes across many markets | Low/inconsistent volume causing liquidity issues and price volatility | Extremely low trading volumes |
Centralization | X | Concentrated trading on a just few exchange | Concentrated trading on a single exchange |
Data Inconsistency | X | x | High spread between data providers |
⚙ Custom Feeds
Custom Feeds are designed for specific purposes and may not be appropriate for general usage or align with your risk parameters. It's essential for users to examine the feed's characteristics to ensure they match their intended application.
Custom feeds fall into these categories:
Onchain single source feeds: Utilize data from one onchain source, with only one provider currently supporting the feed.
Onchain Proof of Reserve Feeds: Employ a large, diverse group of vetted node operators to obtain and confirm onchain reserve data.
Exchange Rate Feeds: Access exchange rates from external onchain contracts for token conversions. eOracle doesn't own or manage these contracts.
Total Value Locked Feeds: Assess the total value locked in particular protocols.
Custom Index Feeds: Calculate values based on multiple underlying assets using predetermined formulas.
Offchain Proof of Reserve Feeds: Verify offchain reserves through custodian attestations.
LP Token Feeds: Combine decentralized feeds with calculations to value liquidity pool tokens.
Wrapped Calculated Feeds: Specific feeds that are pegged 1:1 to underlying assets, but may deviate from market price given that the price is a derivative formed from a calculated method.
Evaluating Data Sources and Risks
Liquidity and its Distribution
When integrating price data for an asset into your smart contract, ensure the asset maintains adequate market liquidity to prevent price manipulation. Low-liquidity assets can experience high volatility, potentially harming your application and users. Unscrupulous actors may exploit volatility or low trading periods to manipulate smart contract execution.
Some feeds source data from single exchanges rather than aggregated services. These are identified in the feed's documentation. Evaluate the specific exchange's liquidity and reliability.
Liquidity migrations, where tokens move between providers (e.g., DEX to CEX), can temporarily deplete the original pool's liquidity, increasing manipulation risk. If planning a migration, collaborate with stakeholders (liquidity providers, exchanges, oracle operators, data providers, users) to maintain accurate pricing throughout.
Low-liquidity assets may show price oscillations between points at regular intervals, especially when data providers show unusual price spreads. To manage this risk, continuously assess the asset's liquidity quality. Low-liquidity assets may also experience erratic price movements from incorrect trades.
Develop and test your contracts to manage price spikes and implement protective measures. For instance, create tests simulating various oracle responses.
Single Source Data Providers
Certain data providers rely on a single source, which may be unavoidable when only one source exists, either onchain or offchain, for specific data types. It's crucial to thoroughly evaluate these providers to ensure they deliver reliable, high-quality data for your smart contracts. Be aware that any errors or omissions in the provider's data could adversely affect your application and its users. Careful assessment of single-source providers is essential to mitigate potential risks associated with data inaccuracies or inconsistencies.
Crypto and Blockchain Actions
Price data quality can be affected by actions taken by crypto and blockchain project teams. These "crypto actions" are akin to corporate actions but specific to the crypto sphere. They include token renaming, swaps, redenominations, splits, reverse splits, network upgrades, and other migrations initiated by project teams or governing communities. Maintaining data quality depends on data sources implementing necessary adjustments for these actions. For instance, a token upgrade resulting in migration may require a new Data Feed to ensure accurate price reporting. Similarly, blockchain forks or network upgrades might necessitate new Data Feeds for data continuity and quality. Projects considering token migrations, forks, network upgrades, or other crypto actions should proactively engage relevant stakeholders to maintain accurate asset price reporting throughout the process.
Periods of High Network Congestion
Data Feed performance is dependent on the blockchain networks they operate on. During times of high network congestion or downtime, the frequency of eOracle Data Feeds may be affected. It's recommended that you design your applications to detect and appropriately respond to such chain performance or reliability issues. Implementing measures to handle these network fluctuations can help maintain the stability and accuracy of your data-dependent applications.
DEX Volumes
Assets with significant presence on decentralized exchanges (DEXs) face unique market structure risks. Market integrity may be compromised by flash loan attacks, volume shifts between exchanges, or temporary price manipulation by well-funded actors. DEX trades can also experience slippage due to liquidity migrations and trade size. The impact of high-slippage trades on market prices depends on the asset's trading patterns. Assets with multiple DEX pools, healthy volumes, and consistent trading across various time frames generally have lower risk of deviant trades affecting aggregated prices.
Backed and Bridged Asset Considerations
Pricing Considerations for Backed or Bridged Assets
When evaluating a eOracle Data Feed for backed or bridged assets (e.g., WBTC), users should weigh the pros and cons of using a feed specifically for the wrapped asset versus one for the underlying asset.
Decisions should be made individually, considering:
Liquidity
Market depth
Trading volatility of the underlying asset compared to its derivative
Users must also assess the security mechanism maintaining the peg between the wrapped asset and its underlying counterpart. Regularly review these factors as asset dynamics evolve over time.
Price Divergence in Extreme Events for Backed Assets
eOracle Data Feeds are designed to report market-wide prices of assets using aggregated prices from various exchanges. For backed or bridged assets, these feeds continue to report the underlying asset's price in addition to the wrapped token's price. This approach reduces manipulation risks associated with the typically lower liquidity of wrapped tokens.
However, users should be aware that extreme events, such as cross-chain bridge exploits or hacks, may cause significant price deviations between wrapped assets and their underlying counterparts. For instance, a bridge hack could lead to a collapse in demand for a particular wrapped asset.
To mitigate risks during such scenarios, users should implement safeguards in their applications. Circuit breakers, which can be created using eOracle Automation, are recommended to proactively pause functionality when unexpected scenarios are detected in data feeds.
Additionally, consider using eOracle Proof of Reserve for real-time monitoring of wrapped asset reserves. This enables protocols to ensure proper collateralization by comparing the wrapped token's supply against the Proof of Reserve feed.
Exchange Rate Feeds vs Market Rate Feeds
Exchange rate feeds differ fundamentally from standard market rate eOracle Price Feeds in their architecture and purpose.
Market rate feeds provide price updates based on aggregated prices from multiple sources, including centralized and decentralized exchanges. This approach offers a comprehensive view of an asset's market-wide price.
In contrast, exchange rate feeds are specific to particular protocols or ecosystems. They report internal redemption rates for assets within that ecosystem, sourcing data directly from designated smart contracts on a source chain and relaying it to a destination chain.
Exchange rate feeds are particularly useful for:
Pricing yield-bearing assets by combining the exchange rate with the underlying asset's market rate
Enhancing liquidity pool performance for yield-bearing assets by enabling programmatic adjustments to swap curves
It's crucial to note that both feed types have distinct risk profiles and mitigation strategies, which vary based on asset type and liquidity. Users are responsible for selecting the appropriate feed for their needs.
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