Overcollateralized borrowers deposit funds into Sky and receive DAI stablecoin.

Sky is a non-custodial stablecoin protocol built on Ethereum. Sky (previously MakerDAO) was founded by Rune Christensen and launched in 2015.

SKY tokenholders own and govern the protocol. They currently take all of the total interest and PSM fees paid by borrowers (revenue). Sky’s investors include a16z, Polychain, IOSG Ventures, etc.

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Sky | Fees and revenues breakdown

# Sky Operating expenses Methodology

## 1. Overview

Operating expenses represents the total daily operational costs incurred by the Sky protocol (formerly MakerDAO) in USD. This metric captures various expense categories including workforce payments, oracle costs, DAI Savings Rate payments, liquidation losses, and other operational expenditures. The calculation combines different expense types from blockchain transactions, categorizes them by purpose, and aggregates them into a comprehensive daily operating expense figure.

## 2. Data sources

- **Sky protocol smart contract events**: Parsed Ethereum events from Sky's core contracts including DAI mint/burn functions, vault operations, and liquidation events
- **Ethereum transaction traces**: Function call data from Sky protocol contracts including `Vat_move`, `Vat_suck`, `Dai_mint`, and `Dai_burn` functions
- **Token transfer events**: ERC20 transfer events for DAI and MKR tokens from Ethereum blockchain
- **Liquidation events**: Parsed `Dog_Bark`, `Cat_Bite`, and legacy liquidation events from Sky's liquidation system
- **Account management data**: Sky ChainLog contract events that track system account addresses and their purposes
- **End-of-day price feeds**: Token price data for USD conversion of expenses
- **RWA and JAR events**: Real World Asset and JAR contract toss events for expense tracking

## 3. Step-by-step calculation

### Component A: Direct DAI expenses

- **Purpose**: Captures DAI minted directly for operational expenses
- **Logic**: Identifies transactions where DAI is minted from the balance sheet address and sent to known direct expense accounts. Filters for successful `Dai_mint` function calls where the destination matches accounts in the direct expense accounts dimension table. Categorizes expenses based on the destination account type using DAO accounts mapping - accounts with 'GAS' become 'Oracle' expenses, 'GELATO' accounts become 'Other direct (DAI)', known DAO accounts become 'Workforce', and others default to 'Other direct (DAI)'
- **Key fields**: Uses `block_timestamp` for timing, `amount` converted from wei to DAI units, and `dai_destination_address` for expense categorization

### Component B: DSR expenses

- **Purpose**: Tracks DAI Savings Rate payments as operational costs
- **Logic**: Captures DAI flows using internal accounting functions (`Vat_move` and `Vat_suck`) where DAI moves from the balance sheet address to the DAI Savings Rate contract. These represent interest payments to DAI holders
- **Key fields**: Uses internal accounting `amount` field converted from ray units (10^45), categorized as 'DAI savings rate' expense type

### Component C: Direct MKR expenses

- **Purpose**: Captures MKR token expenses for operational costs
- **Logic**: Identifies MKR token transfers from direct expense accounts to external addresses using parsed `Transfer` events. Filters for transfers originating from known direct expense accounts but excluding internal transfers between expense accounts
- **Key fields**: Uses `value` field converted from wei to MKR units, categorized as 'Other direct (MKR)' expense type

### Component D: Returned workforce payments

- **Purpose**: Accounts for workforce payment returns as negative expenses
- **Logic**: Identifies DAI burn transactions originating from DAO team wallets and tracks the corresponding DAI flows back to the balance sheet. Uses `Dai_burn` function calls where the burning address matches known DAO accounts, then captures the associated DAI movement using internal accounting functions
- **Key fields**: Uses negative `amount` values to represent expense reductions, sourced from internal DAI flow tracking

### Component E: Other liquidation expenses

- **Purpose**: Captures miscellaneous liquidation-related costs
- **Logic**: Identifies unbacked DAI mints (using `Vat_suck` function) from the balance sheet that don't fall into other expense categories. Excludes flows to direct expense accounts and DSR contract, capturing remaining liquidation-related expenses
- **Key fields**: Uses `amount` from internal accounting functions, categorized as 'Liquidations' expense type

### Component F: Vault resolved liquidations

- **Purpose**: Tracks net losses from vault liquidation processes
- **Logic**: Combines two types of liquidation data - seized liquidations (collateral captured by the system) and settled liquidations (debt pushed to auction). For seized liquidations, captures DAI flows to the balance sheet from system accounts, excluding certain accounts and transactions. For settled liquidations, uses `Dog_Bark` and `Cat_Bite` events to track debt amounts sent to auction. Only includes liquidations where Sky incurs net losses (negative amounts)
- **Key fields**: Aggregates `amount` fields from both seized and settled liquidations, filtering for negative net amounts only

### Final aggregation

- **Combining components**: All expense components are unioned together and aggregated by day, chain, and expense type using sum aggregation
- **Currency conversion**: Joins with end-of-day price feeds to convert token amounts to USD. For DAI expenses, uses price feed data when available or assumes 1:1 USD parity as fallback using coalesce logic
- **Time aggregation**: Truncates all timestamps to daily boundaries and groups expenses by day
- **Final calculation**: Sums all categorized expenses by day to produce total daily operating expenses in USD, with expense categorization preserved for breakdown analysis

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

Total operating expenses borne by the protocol, excluding token incentives.

SkySKY

Operating expenses

Operating expenses

Competitive landscape

Chain breakdown