Methodology & Data Notes

One page covering the formulas, assumptions and data sources behind every calculator, so you can verify the numbers and avoid misreading simulations.

Conventions

CurrencyUSDT throughout
Fee inputpercentage, where 0.1 means 0.1%
Fee applicationcharged on both the buy and the sell leg
Excludedslippage, funding, on-chain gas, withdrawal fees
Displayrounded to the coin precision; internal maths uses full precision

Profit and price-change maths

The price-change calculator ignores fees, while the profit calculator charges your fee rate on both legs — that is why the same price move shows different returns on the two pages.

Coins heldinvestment × (1 − fee rate) ÷ buy price
Net proceedscoins held × sell price × (1 − fee rate)
Net profitnet proceeds − investment
Returnnet profit ÷ investment × 100%
Value after a movecapital × (1 + % change)
CAGR(end value ÷ initial investment)^(1 ÷ years) − 1

Fee maths

Because both legs are charged, annual fees as a share of turnover always equal the fee rate, which makes the absolute cost at different trading frequencies easy to compare.

Fee per tradeorder size × fee rate
Fees per dayfee per trade × 2 × trades per day
Annual feesfees per day × 365
Annual turnoverorder size × 2 × trades per day × 365

Compounding

Compounding is rolled period by period rather than continuously: balance = previous balance × (1 + return per period), with any contribution added before interest is applied.

Frequency and rate must match: "daily" expects a daily rate, "monthly" a monthly rate. The output is a mathematical demonstration and does not imply any asset can sustain a fixed periodic return.

DCA (linear price model)

The model assumes price moves evenly between the start and end values. It explains how averaging works, uses no real historical prices, and must not be read as a return forecast.

Price at period istart + (end − start) × i ÷ (periods − 1)
Coins accumulatedΣ (contribution ÷ period price)
Average costtotal contributed ÷ coins accumulated
End valuecoins accumulated × end price

DCA backtest assumptions

ItemRule
Data sourceBinance spot daily candles
Fetch pathCloudflare Worker edge proxy with caching
Fill priceclose of the corresponding trading day
End valuecoins accumulated × final close in the window
Costsno fees and no slippage
Max drawdown(peak value − trough value) ÷ peak value

Backtest results depend heavily on the window: the same plan can look strong in one period and weak in another. Compare 3-year and 5-year windows before drawing conclusions.

Break-even and target price

Break-even assumes fees on both legs, so the fee rate enters squared; the target price calculation excludes fees, so the move you actually need is slightly larger.

Break-even priceinvestment ÷ [coins held × (1 − fee rate)] = buy price ÷ (1 − fee rate)²
Required gainbreak-even price ÷ buy price − 1
Target pricecurrent price × (1 + target profit ÷ investment)

Average cost

Average cost is weighted by amount and price, so it differs from simply averaging the entry prices — the gap widens when the buys are unevenly sized.

Coins heldΣ (amount ÷ price) for every buy
Average costtotal invested ÷ coins held
Floating P&Lcoins held × current price − total invested

FX conversion

Rates come from a public feed (open.er-api.com), cached at the Cloudflare edge with a visible update time, and can be replaced by manual rates. Stablecoins are treated as approximately 1:1 with USD, which may introduce a small deviation.

Precision and known limitations

Internal maths runs at full floating-point precision while the interface rounds to coin precision, so hand-checking may differ in the last digit.

Known limitations: slippage and order-book depth are not modelled; funding, gas and withdrawal fees are excluded; backtest fills use closes; price-change and scenario maths ignore corporate-style adjustments. If your real cost structure differs, re-run with your own fee rate.