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Realized Prices

Goal

The goal of this script is to calculate, on a daily basis, the realized market price of CCD based on on-chain account balances and historical exchange rates.
By combining daily snapshots of account balances with historical CCD-USD exchange rates, we can derive both the realized capitalization (sum of balances weighted by their acquisition basis) and the corresponding realized price (realized capitalization divided by total supply).

This metric reflects the average cost basis of all CCD in circulation — an indicator of how much capital has been effectively “invested” in the chain, adjusted for each account’s entry price over time.

Data used

The calculation uses three main data sources:

  1. Account balance snapshots — stored as CSV snapshots under data/balances/.
    Each file represents a full ledger state for a given date and is fetched via Git commits (get_polars_df_from_git(commits_by_day[date])).

  2. Historical CCD exchange rates — stored in the MongoDB collection
    utilities.exchange_rates_historical.
    Each document contains the fields token, date, and rate.
    If no matching rate is found for a given day, a default fallback value is used: 0.01703143 / 0.91 # CCD/EUR × EUR/USD average rate (June 2021–June 2022)

This fallback is a rough estimate of purchase levels in the PP sale.

Calculation steps

The script iterates chronologically (oldest → newest) through all available balance snapshots, performing the following steps per day:

  1. Load FX rate
    Retrieve the CCD/USD exchange rate for that date from MongoDB, or use the fallback.

  2. Load balance snapshot
    Convert the snapshot CSV to a Polars DataFrame, selecting only account and total_balance columns.
    Rename total_balance → balance and attach the day’s FX rate as a column fx.

  3. Merge with previous state
    Join the new snapshot with the previous day’s state (account, balance_prev, basis_prev) via an outer join to ensure that all accounts are retained.
    Missing values are filled with 0.

  4. Calculate balance delta
    delta = balance - balance_prev

  5. Update acquisition basis
    For each account:

  6. If the account is new (balance_prev == 0), set basis = fx (the day’s rate).
  7. If the balance increased, compute a weighted average: basis = ((balance_prev * basis_prev) + (delta * fx)) / balance

  8. Otherwise, retain the previous basis.

  9. Compute realized metrics

  10. Realized capitalization = Σ(balance × basis)
  11. Total supply = Σ(balance)

  12. Realized price = realized_cap / total_supply

  13. Update in-memory state Replace state with the merged DataFrame (account, balance, basis) to serve as the previous day’s state for the next iteration.

Example

For 2025-11-01, the following document is stored:

{
  "_id": "2025-11-01-statistics_realized_prices",
  "date": "2025-11-01",
  "type": "statistics_realized_prices",
  "realised_cap": 173928821.82226622,
  "realised_price": 0.012279167038748411
}

Notes

Note

This script treats each balance increase as a “purchase” at that day’s FX rate, and decreases (or exits) do not alter the historical basis. This yields an approximate cost-basis average for the circulating supply, not a true realized profit metric.

Where is this data used?

The realized price is used by in the Realized Price Graph.

Location

nightrunner – realized_prices