Trading fee calculator that shows costs in R (units of risk)

Mykyta Didichenko — Sat, 02 May 2026 21:15:19 +0000

Most trading fee calculators show you two numbers: the dollar amount and the percentage of notional. Both are correct. Neither is useful.

Here's the problem.

Dollar-denominated fees hide the real cost

Say you're trading Bitcoin perpetuals on Bybit. Taker fee is 0.055% each side. You buy $10,000 notional.

Entry fee: $5.50
Exit fee: $5.50
Round trip: $11.00

Does that matter? Impossible to say without knowing one more number: how much are you risking on this trade?

If your stop is $200 away (2% of position), your risk is $200. The $11 fee is 5.5% of your risk. That's 0.055R — acceptable for most strategies.

If your stop is $50 away (0.5%), your risk is $50. The $11 fee is 22% of your risk. That's 0.22R. On a 1:2 trade, your effective R:R just became roughly 1:1.56. At 100 trades, you've given up 22R to the exchange.

Same fee, same position size, completely different impact depending on your actual risk.

What R multiples expose

The R multiple framework comes from Van Tharp's work on expectancy. 1R = your defined risk on a trade. A 1:2 trade means you risk 1R to make 2R.

When you express fees in R terms:

R_fee = round_trip_fee_dollars / risk_per_trade_dollars

Example:
- Account: $10,000
- Risk per trade: 1% = $100 (1R)
- Position: $5,000 notional
- Bybit taker both sides: 0.055% x 2 = 0.11% = $5.50
- R_fee = $5.50 / $100 = 0.055R

Now you can do expectancy math that actually means something:

Expected value per trade = (Win% × Avg_Win_R) - (Loss% × Avg_Loss_R) - R_fee

Example with 45% win rate, 1:2.2 R:R, 0.055R fee:
EV = (0.45 × 2.2) - (0.55 × 1.0) - 0.055
EV = 0.99 - 0.55 - 0.055
EV = 0.385R per trade

Without the fee term, you'd estimate 0.44R. Over 500 trades, that's the difference between 220R profit and 192.5R profit — a 12.5% overestimate from ignoring fees.

Funding rates compound silently

For crypto perpetuals, commission isn't the only cost. Funding rates charge (or pay) you every 8 hours based on your position size. Typical rate on BTC perps is 0.01%/8h when longs pay shorts.

If you hold a $10,000 long for 3 days:

Funding periods = 3 days × 3 periods/day = 9 periods
Funding cost = $10,000 × 0.01% × 9 = $9.00

Add that to the $11 round-trip commission: total cost is $20. If your 1R is $100, that trade cost you 0.20R before it made a tick.

For swing traders holding positions 2-5 days, funding rate cost routinely exceeds commission cost. Most calculators either ignore it or show it as a separate, disconnected number.

What I built

The calculator at dtsystems.dev/tools/trading-fee-calculator lets you set:

Asset class (crypto spot, crypto perps, stocks, forex)
Exchange (Bybit, Binance, Hyperliquid, OKX, MEXC, Kraken, Coinbase, Bitget, IBKR, Schwab)
Position size and account size
Risk per trade (dollars or percentage)
Maker vs. taker
Hold time (for funding rate accumulation on perps)

Outputs: all costs in dollars AND as fractions of 1R.

Fee schedules are pre-loaded. I kept it static rather than pulling live exchange API data — the standard tier rates are accurate for most users, and live API integration adds a maintenance surface I didn't want for a free tool. I'll revisit that for a v2.

One thing it doesn't cover: slippage. For liquid pairs (BTC/ETH) at normal sizes, slippage is small. For mid-cap altcoins or larger size, slippage will exceed commission. That's a harder problem — it requires order book data or historical fill data — and it's on the roadmap.

Who this is for

The R multiple framing is most useful for directional traders: trend followers, momentum strategies, discretionary + automated hybrids. If you're market-making or running statistical arbitrage, you probably already think in basis points of notional, and this framing adds less value for you.

For everyone else running a strategy with defined entries, stops, and targets: knowing your fee overhead in R before you size a position changes how you think about minimum viable R:R for a given strategy.

Try it: https://dtsystems.dev/tools/trading-fee-calculator