Data Collection
How are they calcualted?
The foundation of our risk parameter calculation lies in the comprehensive aggregation of data from various sources. Specifically, our Oracle Service systematically collects data from:
Decentralized Exchanges (DEX): Platforms that facilitate peer-to-peer trading without a central authority.
Centralized Exchanges (CEX): Traditional exchanges managed by centralized entities.
Other Providers: Additional data sources CoinMarketCap and CoinGecko.
This aggregation occurs periodically, ensuring that our data pool remains up-to-date and reflective of current market conditions. By continuously sourcing data from both DEX and CEX, alongside other providers, we capture a wide spectrum of market activities, enhancing the accuracy of our risk assessments.
Data Processing
Once collected, the data undergoes a rigorous processing pipeline within the Oracle Service:
Data Cleaning: Eliminating inconsistencies, duplicates, and errors to maintain data integrity.
Normalization: Standardizing data formats to facilitate seamless analysis.
Storage: Securely storing the processed data in our centralized repository for easy access during subsequent analysis phases.
This meticulous data handling ensures that our risk calculations are based on reliable and consistent information.
2. Correlation Matrix Calculation
Building the Correlation Matrix
With the aggregated and processed data at hand, the next step involves constructing a Correlation Matrix. This matrix quantifies the relationships between different financial instruments or assets within our data set. The process includes:
Identifying Variables: Selecting relevant financial metrics and indicators from the aggregated data.
Calculating Correlations: Using statistical methods to determine the degree to which these variables move in relation to one another.
The correlation matrix serves as a foundational tool for understanding how various assets interact, which is crucial for accurate risk assessment.
Averaging and Risk Parameter Derivation
After establishing the correlation matrix, we compute the average correlations to derive meaningful risk parameters. This involves:
Averaging Correlation Coefficients: Calculating the mean correlation values across different asset pairs to identify overall market trends and dependencies.
Risk Parameter Calculation: Translating these average correlations into quantifiable risk parameters that reflect the collective risk profile of the portfolio or market segment under consideration.
Data Push Mechanism
Once the risk parameters are calculated, the data is pushed to relevant systems and stakeholders. This single, consolidated data push ensures that all parts of the organization have access to the latest risk assessments, enabling informed decision-making and proactive risk management.
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