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Blockchains (L1)

Aleo

# Aleo Token trading volume Methodology

## 1. Overview

Token trading volume measures the total USD value of all tokens traded within the Aleo ecosystem across centralized and decentralized exchanges on a daily basis. This metric aggregates trading activity from multiple exchanges to provide a comprehensive view of liquidity and market activity for Aleo-related tokens. The calculation relies on CoinGecko's market data aggregation, which combines trading volumes from major exchanges to create a unified daily volume metric.

## 2. Data sources

The calculation uses the following data sources:
- **CoinGecko market data feeds**: Daily trading volume and price data aggregated from multiple centralized and decentralized exchanges
- **Token metadata**: Token identification, categorization, and Aleo ecosystem classification from CoinGecko
- **Exchange trading data**: Raw trading volumes from various exchanges that CoinGecko aggregates
- **End-of-day price feeds**: USD conversion rates for accurate volume calculation in base currency

## 3. Step-by-step calculation

### Component A: Token trading volume aggregation
- **Purpose**: Aggregate daily trading volumes for all Aleo ecosystem tokens from CoinGecko data feeds
- **Logic**: The system identifies all tokens categorized as part of the Aleo ecosystem through CoinGecko's classification system. For each token, daily trading volumes are collected from CoinGecko's aggregated exchange data, which combines trading activity across multiple centralized and decentralized exchanges. Volume data is normalized to USD using end-of-day exchange rates to ensure consistent currency reporting across all tokens.
- **Key fields**: Token identifiers, daily trading volumes in USD (`volume_usd`), trading dates (`date`), and token metadata for ecosystem classification

### Component B: Metric standardization and formatting
- **Purpose**: Standardize the output format and ensure complete daily time series coverage
- **Logic**: The aggregated volume data is processed through a standardization framework that applies consistent formatting, metadata tagging, and time series completeness checks. The system implements a zero-filling strategy where dates with no trading activity are populated with zero values rather than being omitted, ensuring a continuous daily time series. The output includes proper metric metadata with `data_id` set to 'aleo' for identification and categorization purposes.
- **Key fields**: Standardized date boundaries (`date`), total volume amounts (`volume_usd`), metric metadata (`data_id`, `metric_type`), and time series flags

### Final aggregation
- **Combining components**: Individual token volumes are summed daily to create a total Aleo ecosystem trading volume, preserving token-level granularity while providing ecosystem-wide totals
- **Currency conversion**: All volumes are converted and reported in USD using end-of-day exchange rates for consistency across different base currencies
- **Time aggregation**: Data is aggregated on daily boundaries using UTC timezone, with each day representing a complete 24-hour trading period
- **Final calculation**: The metric represents the sum of all USD-denominated trading volumes for Aleo ecosystem tokens on each given day, with zero values filled for days with no trading activity to maintain complete time series continuity

*This methodology was automatically generated by Token Terminal's methodology analyzer.*

Total trading volume of the project's native token across spot venues.

AleoALEO

Token trading volume

Token trading volume

Competitive landscape