Fibonacci Martingale

Fibonacci sizing sits between linear and exponential: consecutive rungs approach the golden ratio, roughly 1.618×, so growth is faster than polynomial but materially slower than doubling. It is the choice for operators who want recovery speed closer to exponential while keeping the ramp inside a fundable envelope.

Size at level i is the i-th Fibonacci number. The implementation caps the table at index 14 (610×), so ladders deeper than fifteen levels stop growing and become flat at that multiplier — a detail that changes the capital profile of very deep configurations.

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.

Growth is geometric-ish with ratio ≈1.618, so ten levels already cost a couple of hundred times base. The index-14 cap means the marginal cost of depth beyond fifteen levels is constant rather than compounding, which makes deep Fibonacci ladders behave like a very expensive flat ladder.

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 91.53 against a base of 100 and a deepest rung of 90.00 — so the average sits 85% of the way down the covered range. Getting back to flat from the bottom therefore needs a 1.70% bounce, against 5.00% for a flat ladder of the same depth — 3.30% less work.

Growth sits between linear and exponential, and the ratio between consecutive rungs converges on the golden ratio (~1.618). The multiplier table is capped at index 14 (610×), so extremely deep ladders stop growing there.

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 231× base to collect 0.4 bps of it when the first rung completes.

Trend pullbacks on instruments where you already read structure in Fibonacci terms, and any setting where linear recovery is too slow but doubling is unfundable.

Sizes follow the Fibonacci sequence. Grows faster than linear but far safer than exponential, and aligns with the Fibonacci levels many traders watch. The table is capped at index 14 (610×).

Convex, but bounded in a way exponential is not — both by the ratio and by the table cap. The practical hazard is that the curve looks familiar and benign because of the name, while the capital ramp is much closer to exponential than to linear.

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.

• Trend pullbacks where you want faster-than-linear recovery without doubling.
• You have already backtested the curve on the instrument and funded the measured requirement.

• Capital is tight — ten levels still cost roughly two hundred times base.
• You need a predictable marginal cost per level; the ratio makes each addition materially more expensive than the last.

• Geometric martingale with r ≈ 1.6 gives nearly the same shape with an explicit, adjustable dial — prefer it when you expect to tune.
• Keep depth at or below fifteen levels so you are working with the real curve rather than its capped tail.

• Note where the table cap begins for your depth; the plan's deepest rungs may all be the same size, which changes stop placement math.
• 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
   Name-driven comfort

   Fibonacci reads as natural and moderate. The measured ladder cost says otherwise. Run the comparison below before adopting it.
2. 2
   Cap discontinuity

   At depths beyond fifteen the curve flattens at 610×, so capital scales linearly from there while the operator may still be modelling geometric growth — or vice versa.

• 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
   Does the golden ratio matter mechanically?

   No. The ratio determines the capital ramp and the averaging speed; there is no market property that responds to Fibonacci sizing. Treat it as a geometric curve with r ≈ 1.618.

• 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 Fibonacci 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