Additive Martingale

Additive martingale: each level adds a flat increment rather than a multiple. The result is a curve that is barely distinguishable from flat in relative terms — deliberately so. It exists for operators who want a nod toward averaging down without accepting any of the capital convexity that makes martingale dangerous.

Size at level i is the base plus i units of a fixed increment, evaluated against a nominal base of 100 so the shape stays honest at any grid size. Because the increment is absolute rather than proportional, its relative weight shrinks as the base lot grows.

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.

Almost linear. The ladder costs marginally more than flat sizing at the same depth, and the deepest rung is only slightly larger than the first — which is exactly why deep ladders remain affordable.

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 94.42 against a base of 100 and a deepest rung of 90.00 — so the average sits 56% of the way down the covered range. Getting back to flat from the bottom therefore needs a 4.91% bounce, against 5.00% for a flat ladder of the same depth — 0.09% less work.

Growth is additive, so in relative terms the curve is nearly flat. Capital is close to linear in depth and the average entry sits only marginally below where fixed would put it.

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 10.6× base to collect 9.6 bps of it when the first rung completes.

Any regime where you would otherwise run fixed but want the average entry to drift down slightly faster. It is a risk-controlled averaging curve, not a recovery engine.

Grows by a flat amount per level (base+1, base+2, …). Much gentler than multiplicative martingales; capital requirement stays modest while still averaging down a little faster than fixed.

Essentially the risk profile of fixed: coverage exhaustion rather than capital escalation. The specific hazard is expectation — operators sometimes choose it believing they have martingale recovery, and then find the averaging effect is negligible.

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.

• You want fixed-mode predictability with a slight bias toward averaging down.
• Deep ladders where any real growth curve would be unaffordable.
• Conservative mandates that still want to show some adverse-move response.

• You expect the extra size to meaningfully speed recovery — measure it in the comparison run below before assuming it will.
• Your base lot is large, which makes the fixed increment proportionally irrelevant.

• If the averaging effect looks too small to matter, the honest options are square-root martingale (real but gentle growth) or capped linear (real growth with a ceiling) — not a bigger increment on a curve designed to be flat.
• Treat depth and spread as the primary dials, exactly as with fixed.

• Compare the average entry against a fixed run on the same window. If the two are within a rounding error, the mode is doing nothing for you.
• Track realised cycles per day. Decay curves earn from frequency, so a falling cycle count is the signal that the market has left the window.
• Check the gap between average entry and mark. Decay curves keep it wide by design, so recovery expectations must be set from it, not from hope.

1. 1
   Illusory averaging

   On a large base lot the additive increment is a fraction of a percent per level, so the curve behaves as fixed while the operator plans as if it were martingale. Verify with the measured comparison rather than the label.
2. 2
   Coverage exhaustion

   Same as fixed: the ladder runs out of rungs and simply holds. Coverage, not curve shape, is the lever.

• 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
   When would I pick this over fixed?

   When you want the audit trail to show an adverse-move response and you are content for that response to be small. If you need measurable recovery, pick square-root or capped linear.

• 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.Martingale family — What every curve in this family has in common
• 3.Capital Allocation — Sizing an account to a Additive Martingale 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