State what this study measures
The question is deliberately narrow: how does notional × percentage / 100 × legs change when its three inputs change? The exercise models percentage trading fees only. It does not compare realized outcomes, recommend an exchange or estimate the cost of qualifying for a tier.
Calling the inputs “tiers” is shorthand for alternative assumed rate levels, not verified account eligibility. Actual products may use criteria, pair rules and cost components outside this model. The dataset contains no customer data or market-price observations.
Reproduce the 24-row dataset
Use notionals of $100, $1,000 and $10,000; invented rates of 0.1%, 0.2%, 0.4% and 0.6%; and either one or two legs. The Cartesian product contains 3 × 4 × 2 = 24 rows.
For every row, multiply notional by rate divided by 100 and by the selected leg count. Round the resulting fee to cents for the CSV. A two-leg row holds entry and exit notional equal; it does not model a changed exit price.
Evidence: CryptoTrades editable fee comparator · Download the 24-row synthetic fee dataset (CSV)
Read the $1,000 slice
At $1,000, one-leg fees range from $1 at the assumed 0.1% to $6 at 0.6%. Two equal-notional legs produce $2 to $12. Doubling legs doubles the model because no other input changes.
Changing an assumed rate from 0.4% to 0.2% reduces the percentage-fee result by half: $4 to $2 for one leg, $8 to $4 for two. Those are conditional arithmetic differences, not savings established for a real reader.
| Invented rate | One leg | Two equal-notional legs |
|---|---|---|
| 0.1% | $1 | $2 |
| 0.2% | $2 | $4 |
| 0.4% | $4 | $8 |
| 0.6% | $6 | $12 |
Check scale before interpreting a dollar difference
At the invented 0.2% rate, one-leg fees are $0.20 on $100, $2 on $1,000 and $20 on $10,000. The tenfold changes follow from the formula’s linear dependence on notional, not from a measured relationship between market size and execution quality.
Greater activity can create greater total fees even at a lower percentage. As another fictional example, one $1,000 execution at 0.4% costs $4, while ten at 0.2% cost $20. This is why the exercise is not a reason to increase trading volume.
Keep the exclusions visible
The model excludes spread, slippage, conversion, funding, borrowing, payment, withdrawal, network charges and taxes. It does not model changing rates, account-specific discounts, rebates or the opportunity cost of assets held to qualify for a tier.
A different exit notional requires a separate leg calculation. Two equal-leg rows cannot establish round-trip P&L. Use the P&L guide for its separate entry/exit-price example, while recognizing that its current interface also uses one fee percentage on both sides.
Reproduce and check the dataset
The downloadable CSV linked in Sources & method contains all 24 synthetic rows. Choose the three notionals, four invented rates and one or two equal-notional legs described above; calculate notional × rate / 100 × legs and round the output to cents.
The deterministic calculation does not fetch market data or assign a rate to a provider. Keep the invented-rate label with any excerpt, table or chart, and use the disclosed exclusions when interpreting a result.
Sources & method
- CryptoTrades editable fee comparator
Model uses notional × fee percentage / 100 × legs. The two-leg estimate assumes equal notionals; rates in the study are invented. Checked 2026-10-28.
- Download the 24-row synthetic fee dataset (CSV)
Generated arithmetic only. Four invented rates, three notionals and one or two equal-notional legs; no observed market data or customer records. Checked 2026-10-29.
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