Skip to content
All library documents

Optimizing FMEX Order-Book Allocation for Ranking-Based Unlock Rewards

Article FMZ digest · Author: 小草
Read the original

Summary

The document explains FMEX's ranking-based unlock allocation, where periodic snapshots divide rewards among users according to their share of posted size at specific bid and ask levels. It models each level's contribution as a function of the user's allocation, existing displayed volume, and the reward weight. The goal is to distribute a fixed total order amount across levels to maximize aggregate unlock rewards.

A small two-level example shows that placing all size at the currently thinnest level, or allocating each increment greedily by its immediate gain, can underperform a split derived from optimizing total reward. The proposed practical method ranks incremental allocations by their marginal contribution to the overall objective, assigns size to the best level, and repeats; batching allocations can reduce computation for larger totals. This is a mathematical allocation example tied to FMEX's stated reward rules, not a general market-making strategy. It assumes reward weights and observed book volumes are usable inputs and does not establish that the mechanism remains available or profitable after trading costs, queue effects, or rule changes.

Key ideas

  • FMEX ranking rewards are allocated across book levels in proportion to a user's posted size at periodic snapshots.
  • The allocation objective balances each level's reward weight against the user's size and existing displayed volume.
  • Concentrating all size at the thinnest level can yield less total reward than distributing it across levels.
  • Greedy allocation by immediate incremental gain may miss the allocation that maximizes the final total reward.
  • Repeatedly assigning size according to marginal contribution provides a practical approximation to the optimized allocation.
  • The method relies on platform-specific reward rules and omits trading costs and order-queue effects.

Tags

CryptoMarket makingPosition sizingStatistics

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.