Skip to content

Navigation Menu

Sign in
Appearance settings

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly

Appearance settings

Latest commit

 

History

History
History
66 lines (56 loc) · 2.94 KB

File metadata and controls

66 lines (56 loc) · 2.94 KB
Copy raw file
Download raw file
Open symbols panel
Edit and raw actions
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
66
# 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("System")
AddReference("QuantConnect.Algorithm")
AddReference("QuantConnect.Indicators")
AddReference("QuantConnect.Common")
from System import *
from QuantConnect import *
from QuantConnect.Algorithm import *
from QuantConnect.Indicators import *
### <summary>
### Uses daily data and a simple moving average cross to place trades and an ema for stop placement
### </summary>
### <meta name="tag" content="using data" />
### <meta name="tag" content="indicators" />
### <meta name="tag" content="trading and orders" />
class DailyAlgorithm(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(2013,1,1) #Set Start Date
self.SetEndDate(2014,1,1) #Set End Date
self.SetCash(100000) #Set Strategy Cash
# Find more symbols here: http://quantconnect.com/data
self.AddEquity("SPY", Resolution.Daily)
self.AddEquity("IBM", Resolution.Hour).SetLeverage(1.0)
self.macd = self.MACD("SPY", 12, 26, 9, MovingAverageType.Wilders, Resolution.Daily, Field.Close)
self.ema = self.EMA("IBM", 15 * 6, Resolution.Hour, Field.SevenBar)
self.lastAction = None
def OnData(self, data):
'''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
Arguments:
data: Slice object keyed by symbol containing the stock data
'''
if not self.macd.IsReady: return
if not data.ContainsKey("IBM"): return
if data["IBM"] is None:
self.Log("Price Missing Time: %s"%str(self.Time))
return
if self.lastAction is not None and self.lastAction.date() == self.Time.date(): return
self.lastAction = self.Time
quantity = self.Portfolio["SPY"].Quantity
if quantity <= 0 and self.macd.Current.Value > self.macd.Signal.Current.Value and data["IBM"].Price > self.ema.Current.Value:
self.SetHoldings("IBM", 0.25)
elif quantity >= 0 and self.macd.Current.Value < self.macd.Signal.Current.Value and data["IBM"].Price < self.ema.Current.Value:
self.SetHoldings("IBM", -0.25)
Morty Proxy This is a proxified and sanitized view of the page, visit original site.