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Free lesson · On-chain markets

Transaction gas in a reporting currency

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Start with the idea

Gas is a resource charge paid in the chain’s native asset. Dollar cost depends on both the paid gas price and native-asset value.

Symbols, units & horizon
  • G: gas units actually used
  • g: effective gas price in gwei per gas
  • 10^-9: native token per gwei
  • P_N: USD/native token price at accounting time
  • C_USD: execution-gas cost USD

When and why to use this

Compare on-chain routes in net dollars and include reverted attempts in research accounting.

Gas is a resource charge paid in the chain’s native asset. Dollar cost depends on both the paid gas price and native-asset value.

Use actual gas used, not the maximum gas limit, when accounting for a completed transaction. Under a simple execution-gas model multiply gas used by effective gas price.

This example excludes additional data-availability or layer-specific fees; record them as separate charges when applicable. A reverted transaction may still consume paid execution resources, so failed attempts belong in strategy costs.

CUSD=Gg10−9PN
Model assumptions, derivation and arithmetic

Transaction gas in a reporting currency

  1. Multiply gas units by gwei per gas to get gwei paid.
  2. Convert gwei into native-token units using 10^-9.
  3. Multiply by native-token dollar price and add other fee types separately.
Work it by hand

150,000 gas at 20 gwei is .003 native tokens. At $2,000/native token the execution-gas bill is $6.

Apply it in a strategy

  • Compare on-chain routes in net dollars and include reverted attempts in research accounting.
  • Record the input timestamp, executable quantity, currency and horizon. Reconcile the result with a cash-flow or state table.
  • Stress this failure condition: Gas limit is not actual gas used, and execution gas may be only one part of total network fees.

Research deliverable

Build and explain a transaction gas in a reporting currency worksheet. Compare on-chain routes in net dollars and include reverted attempts in research accounting.

Evidence boundary: Synthetic arithmetic and scenarios illustrate mechanics. They are not historical returns, a paper replication, or evidence of an executable edge. Research sources and their access limitations are recorded at the end of this module.

Python implementation

Self-contained teaching example. Python 3.10+; dependencies and input conventions are shown in the code and notation. Run in your own Python environment.

# Python 3.10+; standard library unless NumPy is imported below.
# Inputs and outputs use the units defined in this lesson. Synthetic teaching example.
def gas_dollars(gas_used,gwei,native_usd):
    if min(gas_used,gwei,native_usd)<0: raise ValueError("Nonnegative gas inputs required")
    return gas_used*gwei*1e-9*native_usd

print(gas_dollars(150000,20,2000))

Continue learning

On-Chain Markets: Data, Oracles and Execution — all lessons
  1. Raw token amounts and economic event types
  2. Transaction gas in a reporting currency
  3. Minimum output and ordering risk
  4. Time-weighted reference prices
  5. Stale oracle health versus executable collateral value
  6. Bridge fragmentation and capital lock-up
  7. Inclusion, finality and conditional loss scenarios
  8. A reproducible on-chain economics study

Quantitative finance and development glossary · Python resources and libraries · Research sources and limitations