-
-
Notifications
You must be signed in to change notification settings - Fork 4.6k
Expand file tree
/
Copy pathAddRemoveSecurityRegressionAlgorithm.py
More file actions
65 lines (53 loc) · 2.79 KB
/
AddRemoveSecurityRegressionAlgorithm.py
File metadata and controls
65 lines (53 loc) · 2.79 KB
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
52
53
54
55
56
57
58
59
60
61
62
63
64
65
# 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>
### This algorithm demonstrates the runtime addition and removal of securities from your algorithm.
### With LEAN it is possible to add and remove securities after the initialization.
### </summary>
### <meta name="tag" content="using data" />
### <meta name="tag" content="assets" />
### <meta name="tag" content="regression test" />
class AddRemoveSecurityRegressionAlgorithm(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(2013,10,7) #Set Start Date
self.set_end_date(2013,10,11) #Set End Date
self.set_cash(100000) #Set Strategy Cash
# Find more symbols here: http://quantconnect.com/data
self.add_equity("SPY")
self._last_action = None
def on_data(self, data):
'''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.'''
if self._last_action is not None and self._last_action.date() == self.time.date():
return
if not self.portfolio.invested:
self.set_holdings("SPY", .5)
self._last_action = self.time
if self.time.weekday() == 1:
self.add_equity("AIG")
self.add_equity("BAC")
self._last_action = self.time
if self.time.weekday() == 2:
self.set_holdings("AIG", .25)
self.set_holdings("BAC", .25)
self._last_action = self.time
if self.time.weekday() == 3:
self.remove_security("AIG")
self.remove_security("BAC")
self._last_action = self.time
def on_order_event(self, order_event):
if order_event.status == OrderStatus.SUBMITTED:
self.debug("{0}: Submitted: {1}".format(self.time, self.transactions.get_order_by_id(order_event.order_id)))
if order_event.status == OrderStatus.FILLED:
self.debug("{0}: Filled: {1}".format(self.time, self.transactions.get_order_by_id(order_event.order_id)))