Crypto DCA (Dollar Cost Averaging) Calculator

Everything runs locally in your browser for privacy. Create a recurring schedule, add prices, and get your average cost.

Plan your DCA

Default amount per buy; can be overridden per row.
Applies to each purchase; reduces units bought.
Inclusive; we’ll generate occurrences on/within the range.
Used for unrealized P/L and portfolio value.
We’ll match by date (exact) if the date exists in the schedule; otherwise we append new rows.

Schedule & Prices

Date Amount Price Units (calc) Remove

Amount defaults to the recurring investment. Units are computed as amount × (1 − fee%) ÷ price.

Results

Results will appear here after you click Calculate.

Let \(A_i\) be the gross amount for buy \(i\), \(f\) the fee rate, and \(P_i\) the price.
Net invested \(= \sum A_i(1-f)\).   Total units \(= \sum \dfrac{A_i(1-f)}{P_i}\).   Average cost basis \(= \dfrac{\sum A_i(1-f)}{\sum A_i(1-f)/P_i}\).

What Dollar-Cost Averaging (DCA) Does — and Doesn’t — Do

Dollar-cost averaging spreads purchases over time using a fixed recurring amount. In volatile markets like crypto, this smooths the entry price: you buy more units when price is low and fewer when price is high. The resulting average cost basis depends on the sequence of prices, the buy frequency, and fees. This calculator computes your total invested (gross and net of fees), total units, and the implied average cost.

Why DCA is popular in crypto

  • 24/7 markets: No market close; a schedule keeps discipline.
  • Volatility: Frequent price swings mean timing the top/bottom is hard; spreading buys reduces regret.
  • Simplicity: Fixed amounts are easier to budget and automate.

Know the limits

  • Fees matter: Per-buy fees reduce units; fewer, larger buys may lower cumulative fees on some platforms.
  • Execution spread: Real fills can differ slightly from reference prices due to spread and slippage.
  • Taxes & accounting: Jurisdictions vary; this tool is educational and not tax advice.

Everything runs locally in your browser. No price feeds, accounts, or storage.

Crypto-Specific Considerations for Dollar-Cost Averaging (DCA)

Dollar-cost averaging (DCA) means investing a fixed amount on a regular schedule, regardless of price. The core math is universal, but crypto adds unique variables: 24/7 markets, on-chain fees, multiple quote currencies, and deep decimal precision. This section explains how those factors affect your average cost and practical outcomes when DCA’ing into Bitcoin, Ethereum, or other digital assets.

24/7 Markets, Higher Volatility

Unlike equities with market hours, crypto trades around the clock, including weekends and holidays. That means your scheduled buys can hit during thin liquidity or high-volatility windows. Volatility can enhance the “buy more when it’s cheaper” effect that DCA relies on, but it can also widen spreads and increase slippage at execution. If your platform lets you choose a time of day, test a consistent hour that aligns with deeper liquidity for your pair.

Quote Currencies, FX Layers, and Stablecoins

Many users DCA with a quote currency other than their local fiat: USD, USDT, USDC, or BTC itself (e.g., buying an altcoin in a BTC pair). Your realized cost basis is therefore layered: local currency → on-ramp/stablecoin → target asset. Each conversion may add fees or spreads. If you DCA via a stablecoin, remember peg risk (rare, but non-zero) and withdrawal costs when moving between venues.

Fees: Trading, Funding, and On-Chain

  • Trading fees: Charged as a percent or fixed amount, often in the base or quote asset. They reduce units or increase effective cost.
  • Deposit/withdrawal fees: Networks like Bitcoin and Ethereum have variable on-chain costs; batching fewer, larger transfers can be cheaper than many small ones.
  • Payment-token discounts: Some exchanges discount fees if you pay with their token. That lowers cost but introduces a small exposure to that token’s price.

Effective units per buy \(= \dfrac{A_i(1-f_i)}{P_i}\).   Average cost basis \(= \dfrac{\sum A_i(1-f_i)}{\sum \frac{A_i(1-f_i)}{P_i}}\).

Precision, “Dust,” and Minimums

Crypto assets support many decimal places, which is great for micro-DCA. Still, exchanges enforce minimum order sizes and step sizes. Very small recurring amounts can create “dust” balances you cannot trade or withdraw economically. If your DCA amount is tiny, consider less frequent but larger buys to reduce cumulative fees and dust creation.

Liquidity, Slippage, and Venue Choice

Pairs with lower liquidity can produce larger deviations between the reference price and your actual fill. Slippage compounds if your schedule triggers during volatile periods. If you DCA across multiple venues or automated brokers, monitor execution quality—the difference between a benchmark index price and your net fill after fees.

Automations, Outages, and Schedule Drift

Auto-DCA features are convenient, but crypto platforms sometimes pause withdrawals, undergo maintenance, or face regional outages. Missed or delayed orders cause “schedule drift,” altering your average cost. Consider setting notifications, and periodically reconcile that automations executed as planned.

Custody and Transfer Strategy

Many DCA workflows buy on an exchange and periodically move holdings to self-custody. Consolidating multiple small buys into a single periodic withdrawal can reduce on-chain fees. On networks with surge pricing (e.g., Ethereum gas), choosing off-peak times can materially lower costs.

Stacking Yield or Rewards? Mind the Accounting

If your asset earns staking yield, protocol rewards, or airdrops, your unit count may increase over time. That improves the effective average cost but complicates tax and recordkeeping. Keep separate records for principal DCA units versus accrual units and know your jurisdiction’s rules.

Behavioral Benefits—and Limits

DCA is popular because it imposes discipline and reduces the stress of trying to time entries. It does not guarantee profits or outperform lump-sum investing in every scenario—especially in strong uptrends where buying earlier would have captured more upside. The right approach depends on risk tolerance, horizon, and fees.

Practical Tips

  • Use a consistent frequency (daily/weekly/monthly) and review totals monthly.
  • Track total fees and experiment with amount vs. frequency to minimize them.
  • Prefer liquid pairs and test execution around deeper-liquidity hours.
  • Batch withdrawals to self-custody where it saves on fees and aligns with your security model.
  • Export fills periodically for auditing and tax records.

This page provides education only. It does not fetch prices or provide financial advice. All calculations run locally in your browser.

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