Files
quantconnect--lean/Algorithm.Python/CustomBuyingPowerModelAlgorithm.py
T
Martin-Molinero 03f56481d4
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Refactor python algorithm import (#5657)
* Python research import improvements

- Improve start.py for research env
- Remove unrequired imports

* Centralize algorithm imports

* Add regression test GH action

* Unit test python import clean up

* Join research and main imports

* More python import clean up

* Fix failing skipped regression algorithm
2021-06-15 19:06:06 -03:00

57 lines
2.5 KiB
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>
### Demonstration of using custom buying power model in backtesting.
### QuantConnect allows you to model all orders as deeply and accurately as you need.
### </summary>
### <meta name="tag" content="trading and orders" />
### <meta name="tag" content="transaction fees and slippage" />
### <meta name="tag" content="custom buying power models" />
class CustomBuyingPowerModelAlgorithm(QCAlgorithm):
'''Demonstration of using custom buying power model in backtesting.
QuantConnect allows you to model all orders as deeply and accurately as you need.'''
def Initialize(self):
self.SetStartDate(2013,10,1) # Set Start Date
self.SetEndDate(2013,10,31) # Set End Date
security = self.AddEquity("SPY", Resolution.Hour)
self.spy = security.Symbol
# set the buying power model
security.SetBuyingPowerModel(CustomBuyingPowerModel())
def OnData(self, slice):
if self.Portfolio.Invested:
return
quantity = self.CalculateOrderQuantity(self.spy, 1)
if quantity % 100 != 0:
raise Exception(f'CustomBuyingPowerModel only allow quantity that is multiple of 100 and {quantity} was found')
# We normally get insufficient buying power model, but the
# CustomBuyingPowerModel always says that there is sufficient buying power for the orders
self.MarketOrder(self.spy, quantity * 10)
class CustomBuyingPowerModel(BuyingPowerModel):
def GetMaximumOrderQuantityForTargetBuyingPower(self, parameters):
quantity = super().GetMaximumOrderQuantityForTargetBuyingPower(parameters).Quantity
quantity = np.floor(quantity / 100) * 100
return GetMaximumOrderQuantityResult(quantity)
def HasSufficientBuyingPowerForOrder(self, parameters):
return HasSufficientBuyingPowerForOrderResult(True)