Portfolio DCA Builder

Design a diversified portfolio with custom allocations across crypto, stocks, and commodities. Backtest your combined DCA strategy using real historical data.

· Interactive · Portfolio DCA

4 assets · Monthly

Loading historical data…

Allocation100%

40%

30%

20%

10%

Contribution per period$500

≈ $500 / month

Frequency

Start date

End date

· How it's calculated

Per-asset DCA, then weighted aggregation

for asset i: amount_i = total × weight_i / 100 → simulateBacktest(asset_i, amount_i, ...) → portfolio_value(t) = Σ asset_value_i(t)

The builder splits your total contribution by allocation weight, runs an independent DCA backtest on each asset, then merges the results by date. Dates where one asset doesn't trade (e.g., a weekend for equities) carry forward the most recent value of that asset so the portfolio sum stays continuous.

· Assumptions

01Allocations are static and must sum to 100%. No rebalancing logic — each scheduled buy uses the same target weights.
02The common backtest date range is the intersection of all selected assets' data ranges, so adding a coin with a 2020 listing date will cap the start of an otherwise long backtest.
03Crypto trades every day; equities and commodities only on trading days. The merge uses forward-fill so weekends don't drop the portfolio value.
04No fees, slippage, or taxes. Multi-asset DCA in practice incurs multiple trades per period.
05No drift correction. After a run, real allocations will not match target weights — running rebalances is out of scope.

· Limitations

01There is no rebalancing. A real portfolio with 50% BTC and 50% SPY where BTC runs 5× will end up ~85% BTC. The model does not show this drift visibly.
02Correlation between assets is implicit in the historical data; the model does not surface diversification metrics like portfolio volatility or Sharpe ratio.
03Survivorship bias is even stronger in a portfolio context: choosing a basket today is also choosing the names that survived to today.
04The common-window restriction means a portfolio with newer assets (e.g., SOL since 2020) starts the backtest in 2020 even for assets that have data back to 2014.

· Questions people ask

Does a DCA portfolio rebalance automatically?

Not in this calculator. Each scheduled buy uses the target weights, so each buy is implicitly a small rebalance toward target. But existing holdings drift with price action — winners grow relative to losers over time.

What's a sensible starting allocation?

A common conservative crypto-curious split is 80% broad-market equities (SPY or QQQ), 10% gold, 10% Bitcoin. Higher-risk variants push the Bitcoin share to 20–40%. There is no universally right answer; the calculator lets you A/B test how different splits would have performed.

Why does my portfolio start date jump forward when I add an asset?

The backtest uses the intersection of available data across all selected assets. If you add Solana (data from 2020) to a Bitcoin portfolio that previously started in 2014, the common window shrinks to 2020 onwards.

Should I include more assets to diversify?

Diversification helps when assets are uncorrelated. Bitcoin and Ethereum move together more than 80% of the time, so holding both does less than the position counts suggest. Mixing across asset classes (crypto + equities + commodities) is more meaningful diversification than mixing within one class.

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