How it works
A volatile-asset DCA simulator tests the dollar-cost averaging thesis where it is actually stressed: on price paths that swing violently between your first buy and your last. Rather than projecting a smooth growth rate, this tool generates deterministic illustrative shapes — a linear crash to a chosen drawdown depth followed by recovery, a boom-bust-rebuild arc, or a steady grind with wobbles — each ending at whatever total return you set. Every month's contribution buys units at that month's price, so drawdowns mechanically load the portfolio with cheap units. The signature output is the average-cost discount: because you buy more units when prices are low, your average cost sits below the simple average of prices paid — on a −65% crash path that gap can exceed 20%. The lump-sum comparison keeps the result honest: DCA wins here precisely because the path dips below its endpoint, while in straight-line bull markets investing everything on day one wins instead. These shapes are illustrations for building intuition about sequence risk and discipline, not forecasts — real markets do not travel neat lines, and no simulator removes the hard part: actually buying during the crash.
Formula
units += monthly ÷ price(m) each month | avg cost = total invested ÷ units | discount = 1 − avg cost ÷ mean(price)
Tips
- Run every path twice — once ending high, once negative — before trusting any plan.
- DCA beats lump sum only when the path dips below its own endpoint.
- Automate purchases; manual DCA reliably fails at maximum pessimism.
- The deeper the drawdown input, the bigger the mechanical average-cost discount.
- Treat outputs as intuition-building scenarios, never as return predictions.
Frequently asked questions
- Does dollar-cost averaging work better for volatile assets?
- For assets that swing hard around their trend, yes — volatility itself becomes a small tailwind because fixed buys accumulate more units at lows. On the default −65% crash path, DCA's average cost lands far below the period's average price. The catch: if the asset simply grinds upward without deep dips, lump-sum investing has historically finished ahead.
- What is the average-cost discount in DCA?
- It is the gap between what you paid per unit on average and the simple average of prices you faced. Buying $500 monthly through a path that visits both extremes means heavy buying at lows, so average cost falls below mean price — often 10–25% on crash-style paths. That discount converts directly into extra units owned.
- Is DCA better than lump sum investing?
- Depends entirely on the path. Lump sum wins whenever prices rise more often than they fall from day one — which historically describes most broad-market periods. DCA wins after crashes and on V-shaped recoveries like the simulated default, where mid-horizon troughs let it stockpile cheap units. Neither strategy dominates; sequence decides.
- How much should I DCA into crypto or other volatile assets?
- Size it to survive the worst path you simulate, not the best. Many practitioners cap speculative volatile assets near 5% of investable assets and automate fixed monthly buys they can sustain through a multi-year drawdown. If the simulated −65% stretch would make you stop contributing, the amount is too large regardless of what any projection shows.
- Do these price paths predict what crypto will do?
- No — they are geometric illustrations with fixed endpoints and depths, chosen to stress-test mechanics rather than forecast anything. Real markets follow messy, non-linear sequences with regime changes no three-shape model captures. Use the simulator to understand how DCA behaves across conditions, and treat every output as hypothetical by construction.