generated from QuantConnect/Lean.DataSource.SDK
-
Notifications
You must be signed in to change notification settings - Fork 0
/
EODHDUpcomingSplitsAlgorithm.py
51 lines (45 loc) · 2.75 KB
/
EODHDUpcomingSplitsAlgorithm.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
# 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 using the upcoming splits data as trade signal
### </summary>
class EODHDUpcomingSplitsDataAlgorithm(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.set_start_Date(2021, 10, 25) #Set Start Date
self.set_end_date(2021, 10, 30) #Set End Date
self.equity_symbol = self.add_equity("AAPL", Resolution.DAILY).symbol
self.add_data(EODHDUpcomingSplits, "splits")
def OnData(self, slice):
''' OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
:param Slice slice: Slice object keyed by symbol containing the stock data
'''
# Order based on the updated upcoming splits data.
data = slice.get(EODHDUpcomingSplits)
if data and self.equity_symbol in data:
# Open position 3 days before splits when the popularity is not developed yet.
# Increasing price will make unit share less liquid, so a company split its shares to lower price.
# We buy the stock if it splits into lower price shares.
upcoming_splits_data = data[self.equity_symbol]
if upcoming_splits_data.split_date <= slice.time + timedelta(3) \
and upcoming_splits_data.split_factor < 1:
self.set_holdings(self.equity_symbol, 1)
# Decreasing price will make the equity becomes penny stock, so a company merges its shares to higher price.
# We sell the stock if it merges into higher price shares.
elif upcoming_splits_data.split_date <= slice.time + timedelta(3) \
and upcoming_splits_data.split_factor > 1:
self.set_holdings(self.equity_symbol, -1)
# Close position 1 day after the splits realized to capitalized the popularity trend.
elif self.portfolio[self.equity_symbol].invested:
self.liquidate(self.equity_symbol)