Files
quantconnect--lean/Algorithm.Python/SmartInsiderDataAlgorithm.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

65 lines
2.7 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>
### Example algorithm demonstrating usage of SmartInsider data
### </summary>
### <meta name="tag" content="using data" />
### <meta name="tag" content="custom data" />
### <meta name="tag" content="smart insider" />
### <meta name="tag" content="form 4" />
### <meta name="tag" content="insider trading" />
class SmartInsiderDataAlgoritm(QCAlgorithm):
def Initialize(self):
'''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
self.SetStartDate(2019, 7, 25)
self.SetEndDate(2019, 8, 2)
self.SetCash(100000)
self.symbol = self.AddEquity("KO", Resolution.Daily).Symbol
self.AddData(SmartInsiderTransaction, "KO")
self.AddData(SmartInsiderIntention, "KO")
def OnData(self, data):
'''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.'''
if not data.ContainsKey(self.symbol.Value):
return
has_open_orders = len(self.Transactions.GetOpenOrders()) != 0
ko_data = data[self.symbol.Value]
if isinstance(ko_data, SmartInsiderTransaction):
if not self.Portfolio.Invested and not has_open_orders:
if ko_data.BuybackPercentage > 0.0001 and ko_data.VolumePercentage > 0.001:
self.Log(f"Buying {self.symbol.Value} due to stock transaction")
self.SetHoldings(self.symbol, 0.50)
elif isinstance(ko_data, SmartInsiderIntention):
if not self.Portfolio.Invested and not has_open_orders:
if ko_data.Percentage > 0.0001:
self.Log(f"Buying {self.symbol.Value} due to intention to purchase stock")
self.SetHoldings(self.symbol, 0.50)
elif self.Portfolio.Invested and not has_open_orders:
if ko_data.Percentage < 0.0:
self.Log(f"Liquidating {self.symbol.Value}")
self.Liquidate(self.symbol)