Implementation guide · Copy Trading and Allocation
Allocation Rounding and Minimum Trade Size
Resolve a synthetic allocation remainder under an explicit rule, with checks for minimum quantity, deterministic ties and conservation of total size.
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Published by FxTrusts, a supplier of brokerage and prop firm technology. Prepared with AI-assisted research and drafting; reviewed against the cited public sources. Examples are illustrative. Product links describe our services.
Quick answer
Ideal allocations may not fit the permitted trade-size grid. A rounding policy must define the rounding stage, valid quantities, residual treatment and tie-breaking rule. Decimal arithmetic helps apply that policy consistently, but it does not decide which allocation is fair or contractually authorized.
Calculate ideal shares before normalizing
Keep unrounded target quantities long enough to understand the difference introduced by normalization. Rounding weights first can distort the total before quantities are even calculated. Record the original total, participant weights and ideal quantities. If the instrument uses a step other than a power of ten, merely limiting decimal places is insufficient. The quantity must satisfy the actual minimum and step rules.
Choose and disclose a residual policy
Rounding every allocation down can leave quantity unassigned, while rounding each to the nearest step can overshoot the original total. An operator might use a deterministic remainder method, retain an unallocated amount or reject the allocation. Those are policy choices, not interchangeable mathematical truths. Interactive Brokers documents its own allocation and board-lot behavior; it does not establish a generic forex PAMM residual rule.
Make ties and negative adjustments reproducible
A remainder method needs a tie-breaker when two accounts have equal fractional remainders. Record whether the order is stable by account ID, rotates under a stated rule or follows another approved method. Corrections and negative adjustments also need explicit rounding behavior. Python’s Decimal documentation illustrates controlled precision and rounding modes, but converting an imprecise binary number into a decimal representation does not repair the original input.
Validate the final executable set
After distributing a remainder, recheck every quantity against minimums, steps and account capacity. A mathematically conserved total can still include an invalid or unauthorized individual trade. Show the difference between ideal and final weights in a review record, especially for small trades where one step is economically significant. Do not claim proportionality is exact when executable constraints have changed it.
A five-step allocation with a declared tie-breaker
Assume a 0.05-lot total, a 0.01-lot step and weights of 50%, 30% and 20%. Ideal quantities are 0.025, 0.015 and 0.010. Rounding down leaves 0.01 unassigned. In this fictional policy, the equal remainder tie between A and B is resolved by stable account-ID order, so A receives the extra step. The final total remains 0.05, but weights become 60%, 20% and 20%.
| Account | Ideal lots | Rounded down | Final lots |
|---|---|---|---|
| A | 0.025 | 0.02 | 0.03 |
| B | 0.015 | 0.01 | 0.01 |
| C | 0.010 | 0.01 | 0.01 |
| Total | 0.050 | 0.04 | 0.05 |
Implementation checklist
- Preserve unrounded targets and declare the exact normalization stage.
- Specify residual ownership and deterministic tie handling.
- Recheck minimum size, step and account capacity after rounding.
- Verify the final sum and disclose deviations from ideal weights.
Sources
These documents support the reference. Check the original publication for current requirements and the limits of its scope.
- Python decimal arithmetic and roundingdocs.python.org
- Interactive Brokers default allocationswww.ibkrguides.com
- MQL5 symbol propertieswww.mql5.com
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