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CustomPartialFillModelAlgorithm.py
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79 lines (61 loc) · 2.99 KB
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# 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 clr import AddReference
AddReference("QuantConnect.Algorithm")
AddReference("QuantConnect.Common")
from QuantConnect import *
from QuantConnect.Algorithm import QCAlgorithm
from QuantConnect.Orders import OrderStatus
from QuantConnect.Orders.Fills import FillModel
import numpy as np
### <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.SetStartDate(2019,1,1)
self.SetEndDate(2019,3,1)
equity = self.AddEquity("SPY", Resolution.Hour)
self.spy = equity.Symbol
self.holdings = equity.Holdings
# Set the fill model
equity.SetFillModel(CustomPartialFillModel(self))
def OnData(self, data):
open_orders = self.Transactions.GetOpenOrders(self.spy)
if len(open_orders) != 0: return
if self.Time.day > 10 and self.holdings.Quantity <= 0:
self.MarketOrder(self.spy, 100, True)
elif self.Time.day > 20 and self.holdings.Quantity >= 0:
self.MarketOrder(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.absoluteRemainingByOrderId = {}
def MarketFill(self, asset, order):
absoluteRemaining = self.absoluteRemainingByOrderId.get(order.Id, order. AbsoluteQuantity)
# Create the object
fill = super().MarketFill(asset, order)
# Set this fill amount
fill.FillQuantity = np.sign(order.Quantity) * 10
if absoluteRemaining == fill.FillQuantity:
fill.Status = OrderStatus.Filled
self.absoluteRemainingByOrderId.pop(order.Id, None)
else:
fill.Status = OrderStatus.PartiallyFilled
self.absoluteRemainingByOrderId[order.Id] = absoluteRemaining - fill.FillQuantity
price = fill.FillPrice
self.algorithm.Debug(f"{self.algorithm.Time} - Partial Fill - Remaining {absoluteRemaining} Price - {price}")
return fill