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How to Track a Token's Daily Volume

● Beginner ⏱ 10 min

Want to track how much of a token is being traded each day? This guide shows you how to calculate daily transfer volume for any SPL token using time-series aggregations.

Prerequisites: Downloaded SolArchive data (both transactions and tokens datasets).

Table of Contents

Understanding Volume Calculation

Token volume is calculated by summing all transfers (sends and receives) for a token. We use ABS() to count both directions and divide by decimals to get the actual token amount.

Note: This counts total transfer volume, not trading volume. For trading volume, you'd need to identify DEX trades specifically.

Daily Volume for a Specific Token

Here's how to calculate daily volume for USDC (or any token):

-- Calculate daily volume for USDC
WITH token_transfers AS (
    SELECT 
        DATE(t.block_timestamp) as day,
        ABS((post.amount - pre.amount) / POW(10, pre.decimals)) as amount
    FROM read_parquet('data/txs/**/*.parquet') as t,
        UNNEST(t.pre_token_balances) as pre,
        UNNEST(t.post_token_balances) as post
    LEFT JOIN read_parquet('data/tokens/**/*.parquet') as tok
        ON pre.mint = tok.mint
    WHERE tok.symbol = 'USDC'
      AND pre.mint = post.mint
      AND pre.account_index = post.account_index
      AND pre.amount != post.amount
      AND t.status = 'Success'
)
SELECT 
    day,
    COUNT(*) as num_transfers,
    SUM(amount) as total_volume,
    AVG(amount) as avg_transfer_size,
    MIN(amount) as min_transfer,
    MAX(amount) as max_transfer
FROM token_transfers
GROUP BY day
ORDER BY day DESC
LIMIT 30;

This query:

Top Tokens by Daily Volume

Want to see which tokens had the most volume on a specific day?

-- Find top 10 tokens by daily volume
WITH token_transfers AS (
    SELECT 
        tok.symbol,
        tok.name,
        DATE(t.block_timestamp) as day,
        ABS((post.amount - pre.amount) / POW(10, pre.decimals)) as amount
    FROM read_parquet('data/txs/**/*.parquet') as t,
        UNNEST(t.pre_token_balances) as pre,
        UNNEST(t.post_token_balances) as post
    LEFT JOIN read_parquet('data/tokens/**/*.parquet') as tok
        ON pre.mint = tok.mint
    WHERE pre.mint = post.mint
      AND pre.account_index = post.account_index
      AND pre.amount != post.amount
      AND t.status = 'Success'
      AND tok.symbol IS NOT NULL
      AND DATE(t.block_timestamp) = '2025-12-01'
)
SELECT 
    symbol,
    name,
    COUNT(*) as num_transfers,
    SUM(amount) as total_volume
FROM token_transfers
GROUP BY symbol, name
ORDER BY total_volume DESC
LIMIT 10;

This reveals the most actively traded tokens for that day.

Complete Python Script

Here's a script that calculates daily volume with summary statistics:

import duckdb
import pandas as pd

TOKEN_SYMBOL = "USDC"  # Change to any token

con = duckdb.connect()

query = f"""
WITH token_transfers AS (
    SELECT 
        DATE(t.block_timestamp) as day,
        ABS((post.amount - pre.amount) / POW(10, pre.decimals)) as amount
    FROM read_parquet('data/txs/**/*.parquet') as t,
        UNNEST(t.pre_token_balances) as pre,
        UNNEST(t.post_token_balances) as post
    LEFT JOIN read_parquet('data/tokens/**/*.parquet') as tok
        ON pre.mint = tok.mint
    WHERE tok.symbol = '{TOKEN_SYMBOL}'
      AND pre.mint = post.mint
      AND pre.account_index = post.account_index
      AND pre.amount != post.amount
      AND t.status = 'Success'
)
SELECT 
    day,
    COUNT(*) as num_transfers,
    SUM(amount) as total_volume,
    AVG(amount) as avg_transfer_size
FROM token_transfers
GROUP BY day
ORDER BY day DESC
LIMIT 30
"""

result = con.execute(query).fetchdf()

print(f"\n{TOKEN_SYMBOL} Daily Volume (Last 30 Days)\n")
print(result.to_string())

# Summary statistics
total_vol = result['total_volume'].sum()
total_transfers = result['num_transfers'].sum()
print(f"\n=== Summary ===")
print(f"Total Volume: {total_vol:,.2f} {TOKEN_SYMBOL}")
print(f"Total Transfers: {total_transfers:,}")
print(f"Avg Daily Volume: {total_vol/len(result):,.2f} {TOKEN_SYMBOL}")

con.close()

Run it:

uv add duckdb pandas
uv run track_volume.py

Example Output

USDC Daily Volume (Last 30 Days)

   day         num_transfers  total_volume      avg_transfer_size
0  2025-12-01  2,458,920     12,845,392,102.45  5,225.18
1  2025-11-30  2,342,188     11,923,482,901.22  5,089.44
2  2025-11-29  2,521,093     13,192,384,293.88  5,232.91
...

=== Summary ===
Total Volume: 384,567,234,129.45 USDC
Total Transfers: 71,234,567
Avg Daily Volume: 12,818,907,804.31 USDC

Use Cases

Track token volume to: