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Read maker / taker on a fill

Every fill event carries a flag indicating whether the order acted as a maker (rested in the book and was consumed by an aggressive opposite trade) or a taker (arrived marketable and crossed the book).

What's exposed

For PARTIALLY_FILLED and FILLED events:

  • Python / Codon: ev.is_maker (bool), ev.fill_role ("maker" | "taker")
  • Node / QuickJS: ev.isMaker (boolean), ev.fillRole ("maker" | "taker" | null for non-fill events)
  • C ABI: FloxOrderEventData.is_maker (uint8, 0 = taker, 1 = maker)

Non-fill statuses always report is_maker = false / fillRole = null.

How the simulator classifies

  • A resting limit order whose queue position gets consumed by an aggressive trade in the opposite direction is maker.
  • A market order, or a limit order that arrived marketable and crossed the book on submission, is taker.
  • A marketable limit that partially crosses then rests will record the crossed fill as taker and any subsequent queue-consumption fills as maker.

Use in a fee model

import flox_py as flox

MAKER_BPS = 1.0   # 1 bp rebate or fee depending on venue
TAKER_BPS = 5.0

class FeeTracker(flox.Strategy):
    def on_fill(self, ctx, ev):
        notional = ev.fill_qty * ev.fill_price
        fee = notional * (MAKER_BPS if ev.is_maker else TAKER_BPS) / 10_000
        self._total_fees += fee

const strat = {
  onFill(ctx, ev) {
    const notional = ev.fillQty * ev.fillPrice;
    const bps = ev.isMaker ? 1.0 : 5.0;
    totalFees += notional * bps / 10_000;
  },
};

class FeeTracker extends Strategy {
  onFill(ctx, ev) {
    const notional = ev.fillQty * ev.fillPrice;
    const bps = ev.isMaker ? 1.0 : 5.0;
    this.totalFees += notional * bps / 10_000;
  }
}

from flox.strategy import Strategy

class FeeTracker(Strategy):
    def __init__(self, symbols):
        super().__init__(symbols)
        self.total_fees = 0.0

    def on_fill(self, ctx, ev):
        notional = ev.fill_qty * ev.fill_price
        bps = 1.0 if ev.is_maker else 5.0
        self.total_fees += notional * bps / 10_000

Notes

  • The classification is exposed as data; the simulator does not apply a fee model based on it. Strategies that need realistic fee bookkeeping should multiply through their own MAKER_BPS / TAKER_BPS values per venue tier.
  • For live executors that forward exchange-side maker/taker flags, the field reflects whatever the venue reports.