Volume-Step Rounding Validator: Min, Max and Increment

Validate the complete quantity grid

The validator above tests whether (desired quantity − grid origin) ÷ step is a whole number and whether the desired quantity lies between the entered minimum and maximum. It also displays the result of the selected round-down, nearest or round-up policy. A policy result outside the entered limits is shown as unavailable instead of being forced to a boundary.

Copy the audit line into a test record with the dated destination specification. It preserves the requested quantity and every constraint used in the result. That evidence is more useful than a rounded value with no explanation of how it was produced.

A decimal result is not necessarily a valid order

A sizing formula may return 0.037 lots, but a broker can require steps of 0.01 lot. The desired quantity then falls between accepted amounts. MetaQuotes defines separate minimum, maximum, step and aggregate directional-volume properties in its symbol reference. All relevant constraints need checking.

On a simple grid of multiples of step s, rounding down a nonnegative quantity q gives floor(q ÷ s) × s. This formula assumes that grid convention; it is not a substitute for the actual platform's validation. Spotware's normalization method explicitly accepts a rounding mode.

Measure the consequence of the choice

Use a hypothetical desired quantity of 0.037 lot with a 0.01-lot increment. Suppose the planned stop-distance calculation gives $1,000 of risk per lot before execution differences and charges.

Illustrative rounding effect on quantity and planned risk

Choice	Quantity	Planned money risk	Difference from desired quantity
Unrounded target	0.037	$37	0%
Round down	0.03	$30	−18.92%
Round up	0.04	$40	+8.11%

The nearest allowed quantity is 0.04, yet it exceeds the assumed $37 ceiling. If the intent is never to exceed the calculated quantity, nearest rounding does not preserve that intent. The table also shows why “only one hundredth of a lot” can be a material change for a small account.

The minimum-size trap

Now suppose the calculated amount is 0.007 lot. Rounding down to the 0.01 grid gives zero, below the minimum. Automatically changing it to 0.01 increases quantity by about 42.86% relative to the target. The right response must be an explicit policy, such as skipping the trade or reviewing an instrument with a smaller permissible size.

Check the maximum and aggregate limits too. A per-order maximum and a maximum total position are different restrictions. Splitting one large request into several requests does not necessarily avoid an aggregate limit and introduces separate execution events.

Keep the residual visible

Log the calculated amount, normalization policy, final submitted quantity and accepted result. In a copying workflow, repeated small rounding differences can make an intended proportional relationship drift. Do not hide the difference by displaying only the multiplier.

For a partial close, validate both the closing quantity and any remaining position. A technically valid close size can leave a residual that the account's rules handle differently. Reconcile the final position after execution instead of assuming that subtraction alone describes the account.

Use lots and units before rounding, and margin headroom after determining the final size. The site's lot-limit guide discusses the related operational checks; no rounding formula can establish actual destination acceptance in advance.

A useful test set includes a quantity exactly on the grid, one just below the minimum, one just above the maximum and one close to a step boundary. Verify the intended policy for each case before relying on it for copied quantities.