Ramped DCA

Ramped accumulation: deployment rises linearly with depth, so lower prices receive more capital — the classic value-averaging instinct expressed as a grid. Crucially it is single-order, so it delivers linear martingale's capital profile without linear martingale's order count.

Size at level i is i base lots, with one order and one take-profit per level. The capital ramp is triangular, identical to linear martingale, but the ladder rests a fraction of the orders.

Below is the wizard's own ladder table and the trading terminal's chart engine, both driven by buildLadderPlan for this mode. Change the level count, spread or target and the rung prices, sizes, capital ramp and chart lines recompute exactly as they would in the grid designer.

Triangular in depth — the same escalation as linear martingale, so the same discipline applies: read the capital table before choosing depth.

Read the cost vs 5 levels column as the escalation test. A flat ladder doubles when the depth doubles; anything materially above that is a curve whose coverage has to be bought rather than simply configured.

With every rung filled, the volume-weighted average entry is 93.00 against a base of 100 and a deepest rung of 90.00 — so the average sits 70% of the way down the covered range. Getting back to flat from the bottom therefore needs a 3.33% bounce, against 5.00% for a flat ladder of the same depth — 1.67% less work.

Deployment increases linearly with depth — buy progressively more the cheaper it gets — but with a SINGLE order per level rather than i orders.

The last row is the metric that separates modes. Profit for a full cycle is the target percentage of deployed capital in every mode, so it cannot discriminate. What differs is how much capital has to sit reserved to earn one shallow cycle: this mode reserves 55.0× base to collect 1.8 bps of it when the first rung completes.

Conviction accumulation into weakness on instruments you want to own more of the cheaper they get.

Increases deployment linearly with depth, like linear martingale but with a SINGLE order per level instead of i orders. Classic "buy more as it drops" accumulation that lowers average cost faster than fixed DCA.

Convex commitment with an accumulation intent, which is a combination worth naming: the position is largest exactly when the thesis is least confirmed. A stop is the only structural answer.

This is the product's grid backtester, not a summary of one. It fetches public candles for the instrument you pick, rebuilds the ladder anchored on the first candle of the window, then applies the engine's own fill, take-profit, refill and stop-loss rules bar by bar. The caveat block inside the panel is part of the output — read it before trusting a number.

First the arithmetic, then the market. The table below is computed from the size curves alone; the sweep underneath replays every one of those ladders over the same real candle window, with grid_mode as the only variable.

• Conviction accumulation into weakness.
• Value averaging where lower prices deserve more capital.
• You want linear growth with far fewer resting orders than linear martingale.

• You want the multiple partial exits linear martingale provides.
• You have not funded the triangular ramp — the accumulation framing does not reduce the cost.

• Depth is the expensive dial here, exactly as in linear martingale. Coverage bought this way is not cheap.
• If the ramp is more than you want, capped linear gives the same instinct with a ceiling.

• Track average entry and peak notional together; ramped accumulation moves both faster than operators expect.
• Watch the deepest filled level, not the P&L. Depth is the leading indicator; P&L is the lagging one.
• Compare peak committed notional against the account, weekly. A growth curve that has never been deep has never been tested.
• Treat every level increase as a capital decision: adding levels to a growth curve is not a linear cost.

1. 1
   Triangular funding gap

   The accumulation narrative makes the capital ramp feel like a plan rather than a cost. It is a cost: twenty levels are about four times ten.
2. 2
   Maximum size at minimum confirmation

   The largest deployment happens at the deepest, least-confirmed prices. If the thesis was wrong, the ladder maximised the error.

• Spread sets how fast the ladder consumes depth. Widening it buys coverage for the same level count at the cost of fewer fills.
• Target sets what each cycle books. Below round-trip fees plus slippage, a grid is a fee generator regardless of the size curve.
• The stop loss is the only bound on the tail. Without it, the curve's worst case is whatever the market does, not what you planned.

1. 1
   Why choose this over linear martingale?

   When you want the ramp but not 210 resting orders at twenty levels. The sweep below shows the P&L difference is usually driven by exit granularity, not by sizing.

• Sizes and capital: levelMultiplier / gridModeCurve in lib/grid/gridModes.ts, mirrored from grid_modes.hpp and the Python engine's lot calculator.
• Rung and exit prices, capital ramp, init targets and the stop line: buildLadderPlan — the same builder the wizard and grid designer use.
• Backtest fills, cycles and P&L: runBacktest / runBacktestSweep over public broker candles, applying the engine's fill, exit, refill and stop rules.
• Price charts: the trading terminal's chart engine, with the ladder drawn through its own price-line API.

• 1.Grid Modes — Overview — The full taxonomy and how to choose
• 2.DCA family — What every curve in this family has in common
• 3.Capital Allocation — Sizing an account to a Ramped DCA ladder
• 4.Stop Loss — Bounding this curve's tail
• 5.Reading the Ladder Plan — Verifying the curve before deploying
• 6.Grid Structure — Levels, init batch and base size