Score-weighted vs equal-weight allocation

What equal weighting actually assumes

An equal-weight basket of ten leaders implicitly asserts that you have no ability to distinguish between them. If that were true, equal weighting would be correct — it is the right answer under total ignorance, and it is why index construction often starts there.

But a copy-trading basket is not drawn at random. Every member has already passed a selection filter, which means you do have information about them: how long their record is, how consistent it is, how much of it came from a handful of outsized trades. Discarding that information at the allocation step wastes the only work that distinguishes one system from another.

• Equal weight maximises exposure to the marginal qualifier — the trader who barely cleared the floor.
• It ignores record length, so a 90-day sample and a 900-day sample are treated identically.
• It cannot express partial conviction: a leader is either fully in or fully out.

How composite scoring produces a weight

HyperMirror scores each candidate on realized PnL consistency, win rate, profit factor, position discipline and account survivability. Each dimension has a floor; failing any floor removes the trader from consideration entirely rather than reducing their weight. Only survivors are scored, and capital is then distributed in proportion to that composite score.

The practical effect is monotonic but bounded: a leader with twice the score does not receive twice the risk in an unbounded way, because per-leader notional ceilings cap any single allocation. Weighting decides relative conviction; the ceilings decide absolute exposure.

The failure modes of score weighting

Score weighting is not free of assumptions. It assumes the scored dimensions remain predictive, that the sample behind them is long enough to be meaningful, and that the market regime the score was earned in has not disappeared. All three can break.

The mitigations are structural rather than clever: floors that reject short or thin records, continuous rescoring so decay shows up quickly, probation and replacement when it does, and caps that limit what any single mistaken weight can cost. None of that removes the possibility of loss.

• Scores are backward-looking; a regime change can invalidate a high score without warning.
• Concentration risk rises as one leader's score pulls away from the field — caps exist for exactly this.
• Frequent reweighting increases turnover, and turnover costs money in fees and slippage.

What this means for your account

You do not set weights manually. The basket and its weights are published on the leaderboard, and the model portfolio shows what that allocation produced over recent windows. Both are estimates derived from public trader history, not a record of your account.

Past performance is not indicative of future results. Perpetual futures are leveraged instruments and carry a substantial risk of loss, including the loss of your entire position.