Geometric Ratio

Ratio-based sizing presented under the geometric family rather than the martingale one. Behaviourally identical to geometric martingale: size is base × rⁱ with r as the single aggression dial. The separate value is a labelling decision, not a behavioural one.

Each rung is r times the previous one. Ladder cost is the geometric series base × (rⁿ⁺¹ − 1)/(r − 1), so cost is highly sensitive to r and moderately sensitive to depth.

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. Re-read the capital table after every change to r; nothing else in the configuration moves the worst case as much.

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.

Identical to geometric martingale — a constant ratio between rungs, with r as the aggression dial.

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.

Mean-reverting instruments you have measured, where you want one parameter to express how hard the ladder leans into the move.

A category-explicit alias for ratio scaling, provided so dashboards can group ratio strategies under "geometric". Behaves identically to geometric martingale.

The convex tail of any multiplicative curve, scaled by r. At r = 2 it is exponential martingale.

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 ratio-based ladder design grouped under the geometric family for reporting.
• Your desk's vocabulary is ratios rather than martingale variants.

• Same cautions as any multiplicative growth curve — unfunded depth, unattended operation, r left near 2.

• See Geometric Martingale: r behaves identically here.
• Prefer one of the two names consistently across a desk so monitors aggregate correctly.

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.

• 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
   Split reporting

   Running some strategies as `geometric_ratio` and others as `marti_grid_geometric` fragments dashboards for no behavioural benefit.
2. 2
   Tail at r ≥ 2

   Identical to exponential martingale, including the funding wall.

• 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
   Which should I use?

   Whichever your reporting groups by; then keep it consistent. The engine cannot tell them apart.

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