Partial Market Order Fills

Article Strategy library · Author: QuantConnect

Summary

This example shows how to customize a trading algorithm’s fill model so a market order is completed in portions. It attaches a custom model to an hourly equity subscription, then overrides market-fill handling to cap each simulated fill at a fixed quantity. The model tracks the remaining absolute order quantity by order ID and marks each fill as partial or complete as appropriate.

The example also includes basic order logic that waits for existing open orders to clear before submitting new trades. It is an implementation template rather than a trading strategy or evidence of execution quality: it provides no comparison with real market fills, liquidity conditions, slippage, or exchange behavior. Its fixed-size fill assumption is simplified, so researchers should adapt it to the asset, order size, and execution conditions they want to simulate.

Key ideas

A custom fill model can override market-order fill handling.
The example limits each simulated fill to a fixed quantity.
Remaining order quantity is tracked separately for each order ID.
The fill status changes from partial to filled when the remaining amount is exhausted.
The example does not model real liquidity or validate its fill assumptions against market data.

Tags

Execution Market microstructure Backtesting

Full text

# CustomPartialFillModelAlgorithm


# CustomPartialFillModelAlgorithm









Basic template algorithm that implements a fill model with partial fills

Basic template algorithm that implements a fill model with partial fills

## Source (Apache-2.0)

```python
# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from AlgorithmImports import *

### <summary>
### Basic template algorithm that implements a fill model with partial fills
### <meta name="tag" content="trading and orders" />
### </summary>
class CustomPartialFillModelAlgorithm(QCAlgorithm):
    '''Basic template algorithm that implements a fill model with partial fills'''

    def initialize(self):
        self.set_start_date(2019, 1, 1)
        self.set_end_date(2019, 3, 1)

        equity = self.add_equity("SPY", Resolution.HOUR)
        self.spy = equity.symbol
        self.holdings = equity.holdings

        # Set the fill model
        equity.set_fill_model(CustomPartialFillModel(self))


    def on_data(self, data):
        open_orders = self.transactions.get_open_orders(self.spy)
        if len(open_orders) != 0: return

        if self.time.day > 10 and self.holdings.quantity <= 0:
            self.market_order(self.spy, 105, True)

        elif self.time.day > 20 and self.holdings.quantity >= 0:
            self.market_order(self.spy, -100, True)


class CustomPartialFillModel(FillModel):
    '''Implements a custom fill model that inherit from FillModel. Override the MarketFill method to simulate partially fill orders'''

    def __init__(self, algorithm):
        self.algorithm = algorithm
        self.absolute_remaining_by_order_id = {}

    def market_fill(self, asset, order):
        absolute_remaining = self.absolute_remaining_by_order_id.get(order.id, order. AbsoluteQuantity)

        # Create the object
        fill = super().market_fill(asset, order)

        # Set the fill amount
        fill.fill_quantity = np.sign(order.quantity) * 10

        if (min(abs(fill.fill_quantity), absolute_remaining) == absolute_remaining):
            fill.fill_quantity = np.sign(order.quantity) * absolute_remaining
            fill.status = OrderStatus.FILLED
            self.absolute_remaining_by_order_id.pop(order.id, None)
        else:
            fill.status = OrderStatus.PARTIALLY_FILLED
            self.absolute_remaining_by_order_id[order.id] = absolute_remaining - abs(fill.fill_quantity)
            price = fill.fill_price
            # self.algorithm.debug(f"{self.algorithm.time} - Partial Fill - Remaining {self.absolute_remaining_by_order_id[order.id]} Price - {price}")

        return fill

```

Shown in full with attribution under the source's licence. Licence: Apache-2.0

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

Simulating Partial Market Order Fills in a Trading Algorithm

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