1
|
|
|
#!/usr/bin/env python |
2
|
|
|
# |
3
|
|
|
# Copyright 2014 Quantopian, Inc. |
4
|
|
|
# |
5
|
|
|
# Licensed under the Apache License, Version 2.0 (the "License"); |
6
|
|
|
# you may not use this file except in compliance with the License. |
7
|
|
|
# You may obtain a copy of the License at |
8
|
|
|
# |
9
|
|
|
# http://www.apache.org/licenses/LICENSE-2.0 |
10
|
|
|
# |
11
|
|
|
# Unless required by applicable law or agreed to in writing, software |
12
|
|
|
# distributed under the License is distributed on an "AS IS" BASIS, |
13
|
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
14
|
|
|
# See the License for the specific language governing permissions and |
15
|
|
|
# limitations under the License. |
16
|
|
|
|
17
|
|
|
"""Dual Moving Average Crossover algorithm. |
18
|
|
|
|
19
|
|
|
This algorithm buys apple once its short moving average crosses |
20
|
|
|
its long moving average (indicating upwards momentum) and sells |
21
|
|
|
its shares once the averages cross again (indicating downwards |
22
|
|
|
momentum). |
23
|
|
|
""" |
24
|
|
|
|
25
|
|
|
from zipline.api import order_target, record, symbol, history, add_history |
26
|
|
|
|
27
|
|
|
|
28
|
|
|
def initialize(context): |
29
|
|
|
# Register 2 histories that track daily prices, |
30
|
|
|
# one with a 100 window and one with a 300 day window |
31
|
|
|
add_history(100, '1d', 'price') |
32
|
|
|
add_history(300, '1d', 'price') |
33
|
|
|
|
34
|
|
|
context.sym = symbol('AAPL') |
35
|
|
|
|
36
|
|
|
context.i = 0 |
37
|
|
|
|
38
|
|
|
|
39
|
|
|
def handle_data(context, data): |
40
|
|
|
# Skip first 300 days to get full windows |
41
|
|
|
context.i += 1 |
42
|
|
|
if context.i < 300: |
43
|
|
|
return |
44
|
|
|
|
45
|
|
|
# Compute averages |
46
|
|
|
# history() has to be called with the same params |
47
|
|
|
# from above and returns a pandas dataframe. |
48
|
|
|
short_mavg = history(100, '1d', 'price').mean() |
49
|
|
|
long_mavg = history(300, '1d', 'price').mean() |
50
|
|
|
|
51
|
|
|
# Trading logic |
52
|
|
|
if short_mavg[context.sym] > long_mavg[context.sym]: |
53
|
|
|
# order_target orders as many shares as needed to |
54
|
|
|
# achieve the desired number of shares. |
55
|
|
|
order_target(context.sym, 100) |
56
|
|
|
elif short_mavg[context.sym] < long_mavg[context.sym]: |
57
|
|
|
order_target(context.sym, 0) |
58
|
|
|
|
59
|
|
|
# Save values for later inspection |
60
|
|
|
record(AAPL=data[context.sym].price, |
61
|
|
|
short_mavg=short_mavg[context.sym], |
62
|
|
|
long_mavg=long_mavg[context.sym]) |
63
|
|
|
|
64
|
|
|
|
65
|
|
|
# Note: this function can be removed if running |
66
|
|
|
# this algorithm on quantopian.com |
67
|
|
|
def analyze(context=None, results=None): |
68
|
|
|
import matplotlib.pyplot as plt |
69
|
|
|
import logbook |
70
|
|
|
logbook.StderrHandler().push_application() |
71
|
|
|
log = logbook.Logger('Algorithm') |
72
|
|
|
|
73
|
|
|
fig = plt.figure() |
74
|
|
|
ax1 = fig.add_subplot(211) |
75
|
|
|
results.portfolio_value.plot(ax=ax1) |
76
|
|
|
ax1.set_ylabel('Portfolio value (USD)') |
77
|
|
|
|
78
|
|
|
ax2 = fig.add_subplot(212) |
79
|
|
|
ax2.set_ylabel('Price (USD)') |
80
|
|
|
|
81
|
|
|
# If data has been record()ed, then plot it. |
82
|
|
|
# Otherwise, log the fact that no data has been recorded. |
83
|
|
|
if ('AAPL' in results and 'short_mavg' in results and |
84
|
|
|
'long_mavg' in results): |
85
|
|
|
results['AAPL'].plot(ax=ax2) |
86
|
|
|
results[['short_mavg', 'long_mavg']].plot(ax=ax2) |
87
|
|
|
|
88
|
|
|
trans = results.ix[[t != [] for t in results.transactions]] |
89
|
|
|
buys = trans.ix[[t[0]['amount'] > 0 for t in |
90
|
|
|
trans.transactions]] |
91
|
|
|
sells = trans.ix[ |
92
|
|
|
[t[0]['amount'] < 0 for t in trans.transactions]] |
93
|
|
|
ax2.plot(buys.index, results.short_mavg.ix[buys.index], |
94
|
|
|
'^', markersize=10, color='m') |
95
|
|
|
ax2.plot(sells.index, results.short_mavg.ix[sells.index], |
96
|
|
|
'v', markersize=10, color='k') |
97
|
|
|
plt.legend(loc=0) |
98
|
|
|
else: |
99
|
|
|
msg = 'AAPL, short_mavg & long_mavg data not captured using record().' |
100
|
|
|
ax2.annotate(msg, xy=(0.1, 0.5)) |
101
|
|
|
log.info(msg) |
102
|
|
|
|
103
|
|
|
plt.show() |
104
|
|
|
|
105
|
|
|
|
106
|
|
|
# Note: this if-block should be removed if running |
107
|
|
|
# this algorithm on quantopian.com |
108
|
|
|
if __name__ == '__main__': |
|
|
|
|
109
|
|
|
from datetime import datetime |
110
|
|
|
import pytz |
111
|
|
|
from zipline.algorithm import TradingAlgorithm |
112
|
|
|
from zipline.utils.factory import load_from_yahoo |
113
|
|
|
|
114
|
|
|
# Set the simulation start and end dates. |
115
|
|
|
start = datetime(2011, 1, 1, 0, 0, 0, 0, pytz.utc) |
116
|
|
|
end = datetime(2013, 1, 1, 0, 0, 0, 0, pytz.utc) |
117
|
|
|
|
118
|
|
|
# Load price data from yahoo. |
119
|
|
|
data = load_from_yahoo(stocks=['AAPL'], indexes={}, start=start, |
120
|
|
|
end=end) |
121
|
|
|
|
122
|
|
|
# Create and run the algorithm. |
123
|
|
|
algo = TradingAlgorithm(initialize=initialize, handle_data=handle_data, |
124
|
|
|
identifiers=['AAPL']) |
125
|
|
|
results = algo.run(data) |
126
|
|
|
|
127
|
|
|
# Plot the portfolio and asset data. |
128
|
|
|
analyze(results=results) |
129
|
|
|
|
Duplicated code is one of the most pungent code smells. If you need to duplicate the same code in three or more different places, we strongly encourage you to look into extracting the code into a single class or operation.
You can also find more detailed suggestions in the “Code” section of your repository.