Geometric Martingale

Exponential growth with a dial. Size is base × rⁱ, so r is a single, legible control over aggression: r = 2 reproduces doubling, r between 1.2 and 1.6 produces a curve that recovers noticeably faster than linear while remaining fundable. This is the mode to use when you intend to tune a curve rather than pick one.

Every rung is r times the previous one, so the ladder is a geometric series and its total cost is base × (rⁿ⁺¹ − 1)/(r − 1). Small changes in r move that total a great deal — the sensitivity is the point, and the trap.

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.

Geometric in depth. Raising r from 1.5 to 1.8 roughly doubles the ten-level cost; raising it to 2 turns the mode into exponential martingale. Always re-read the capital table after changing r, never assume the previous funding still applies.

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 91.82 against a base of 100 and a deepest rung of 90.00 — so the average sits 82% of the way down the covered range. Getting back to flat from the bottom therefore needs a 2.03% bounce, against 5.00% for a flat ladder of the same depth — 2.97% less work.

A constant ratio r between rungs, so the curve is exponential with a dial. r = 2 reproduces doubling; r between 1.2 and 1.8 gives a controllable middle ground.

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 170× base to collect 0.9 bps of it when the first rung completes.

Any mean-reverting instrument you have measured. Because r is continuous, the mode adapts to the instrument rather than the other way round: a low-volatility pair can carry a higher r at the same depth than a violent one.

Each level multiplies by a constant ratio r. r=2 is exponential; r between 1.2 and 1.8 gives a controllable middle ground so you dial recovery speed against capital risk precisely.

The same convex tail as exponential, scaled by r. The operational risk is unique to this mode: r is easy to nudge, and a change that looks cosmetic on the curve chart is a large change to the worst case.

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 exponential-style recovery but softer than 2×.
• You are fitting a curve to measured behaviour on a specific instrument.
• You need one parameter to express aggression in a review or a mandate.

• You have not checked the cumulative cost at your level count — small changes in r move it a lot.
• The strategy will be edited by people who will not re-read the capital table after touching r.

• Move r in steps of 0.1 and re-read the ladder cost each time. Treat 1.8 and above as exponential in all but name.
• If you want the ratio behaviour with a hard ceiling, use capped martingale and set the cap instead.
• Depth and r trade off directly: a higher r with fewer levels can be safer than a lower r with many.

This mode is parametric. The wizard and the settings panel show only the dial(s) it actually uses, and changing one is a structural edit — the resting ladder is cancelled and re-placed at the new sizes.

• Record r alongside the mode in every deployment note. The mode name alone does not describe the strategy.
• Alert on peak notional, because r makes the relationship between depth and exposure non-obvious at a glance.
• 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
   Silent re-aggression

   An edit raises r modestly and the funding plan is not revisited. The ladder is now a different strategy with the same name.
2. 2
   Tail at r ≥ 2

   At r = 2 this is exponential martingale, including its funding wall. Nothing about the mode label warns you.

• Changing r is a structural edit: the resting ladder is cancelled and re-placed at the new sizes.
• 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
   What r should I start from?

   Start at 1.2–1.3, measure, and raise only if the measured recovery benefit justifies the measured capital increase. The sweep below shows you both sides of that trade on real candles.
2. 2
   How is this different from `geometric_ratio`?

   It is not — `geometric_ratio` is an alias that exists so dashboards can group the curve under the geometric family.

• 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 Geometric 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