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MAINT: Replace old ema_talib example with new one.

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Thomas Wiecki
2014-12-19 14:04:27 +01:00
parent 9d8bb3dfa9
commit 71effa5e98
2 changed files with 51 additions and 145 deletions
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zipline/examples/dual_ema_talib.py
+51 -49
View File
@@ -1,6 +1,6 @@
#!/usr/bin/env python
#
# Copyright 2013 Quantopian, Inc.
# Copyright 2014 Quantopian, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
@@ -14,70 +14,71 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import matplotlib.pyplot as plt
from zipline.algorithm import TradingAlgorithm
from zipline.utils.factory import load_from_yahoo
"""Dual Moving Average Crossover algorithm.
This algorithm buys apple once its short moving average crosses
its long moving average (indicating upwards momentum) and sells
its shares once the averages cross again (indicating downwards
momentum).
"""
# Import exponential moving average from talib wrapper
from zipline.transforms.ta import EMA
from datetime import datetime
import pytz
def initialize(context):
context.security = symbol('AAPL')
# Add 2 mavg transforms, one with a long window, one with a short window.
context.short_ema_trans = EMA(timeperiod=20)
context.long_ema_trans = EMA(timeperiod=40)
# To keep track of whether we invested in the stock or not
context.invested = False
class DualEMATaLib(TradingAlgorithm):
def handle_data(context, data):
short_ema = context.short_ema_trans.handle_data(data)
long_ema = context.long_ema_trans.handle_data(data)
if short_ema is None or long_ema is None:
return
"""Dual Moving Average Crossover algorithm.
buy = False
sell = False
This algorithm buys apple once its short moving average crosses
its long moving average (indicating upwards momentum) and sells
its shares once the averages cross again (indicating downwards
momentum).
if (short_ema > long_ema).all() and not context.invested:
order(context.security, 100)
context.invested = True
buy = True
elif (short_ema < long_ema).all() and context.invested:
order(context.security, -100)
context.invested = False
sell = True
"""
record(AAPL=data[context.security].price,
short_ema=short_ema[context.security],
long_ema=long_ema[context.security],
buy=buy,
sell=sell)
def initialize(self, short_window=20, long_window=40):
# Add 2 mavg transforms, one with a long window, one
# with a short window.
self.short_ema_trans = EMA(timeperiod=short_window)
self.long_ema_trans = EMA(timeperiod=long_window)
# To keep track of whether we invested in the stock or not
self.invested = False
def handle_data(self, data):
self.short_ema = self.short_ema_trans.handle_data(data)
self.long_ema = self.long_ema_trans.handle_data(data)
if self.short_ema is None or self.long_ema is None:
return
self.buy = False
self.sell = False
if (self.short_ema > self.long_ema).all() and not self.invested:
self.order('AAPL', 100)
self.invested = True
self.buy = True
elif (self.short_ema < self.long_ema).all() and self.invested:
self.order('AAPL', -100)
self.invested = False
self.sell = True
self.record(AAPL=data['AAPL'].price,
short_ema=self.short_ema['AAPL'],
long_ema=self.long_ema['AAPL'],
buy=self.buy,
sell=self.sell)
if __name__ == '__main__':
start = datetime(1990, 1, 1, 0, 0, 0, 0, pytz.utc)
end = datetime(1991, 1, 1, 0, 0, 0, 0, pytz.utc)
from datetime import datetime
import matplotlib.pyplot as plt
import pytz
from zipline.algorithm import TradingAlgorithm
from zipline.api import order, record, symbol
from zipline.utils.factory import load_from_yahoo
start = datetime(2014, 1, 1, 0, 0, 0, 0, pytz.utc)
end = datetime(2014, 11, 1, 0, 0, 0, 0, pytz.utc)
data = load_from_yahoo(stocks=['AAPL'], indexes={}, start=start,
end=end)
dma = DualEMATaLib()
results = dma.run(data).dropna()
algo = TradingAlgorithm(initialize=initialize, handle_data=handle_data)
results = algo.run(data).dropna()
fig = plt.figure()
ax1 = fig.add_subplot(211, ylabel='portfolio value')
@@ -92,3 +93,4 @@ if __name__ == '__main__':
'v', markersize=10, color='k')
plt.legend(loc=0)
plt.gcf().set_size_inches(18, 8)
plt.show()
zipline/examples/quantopian_dual_ema_talib.py
-96
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@@ -1,96 +0,0 @@
#!/usr/bin/env python
#
# Copyright 2014 Quantopian, Inc.
#
# 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.
"""Dual Moving Average Crossover algorithm.
This algorithm buys apple once its short moving average crosses
its long moving average (indicating upwards momentum) and sells
its shares once the averages cross again (indicating downwards
momentum).
"""
# Import exponential moving average from talib wrapper
from zipline.transforms.ta import EMA
def initialize(context):
context.security = symbol('AAPL')
# Add 2 mavg transforms, one with a long window, one with a short window.
context.short_ema_trans = EMA(timeperiod=20)
context.long_ema_trans = EMA(timeperiod=40)
# To keep track of whether we invested in the stock or not
context.invested = False
def handle_data(context, data):
short_ema = context.short_ema_trans.handle_data(data)
long_ema = context.long_ema_trans.handle_data(data)
if short_ema is None or long_ema is None:
return
buy = False
sell = False
if (short_ema > long_ema).all() and not context.invested:
order(context.security, 100)
context.invested = True
buy = True
elif (short_ema < long_ema).all() and context.invested:
order(context.security, -100)
context.invested = False
sell = True
record(AAPL=data[context.security].price,
short_ema=short_ema[context.security],
long_ema=long_ema[context.security],
buy=buy,
sell=sell)
if __name__ == '__main__':
from datetime import datetime
import matplotlib.pyplot as plt
import pytz
from zipline.algorithm import TradingAlgorithm
from zipline.api import order, record, symbol
from zipline.utils.factory import load_from_yahoo
start = datetime(2014, 1, 1, 0, 0, 0, 0, pytz.utc)
end = datetime(2014, 11, 1, 0, 0, 0, 0, pytz.utc)
data = load_from_yahoo(stocks=['AAPL'], indexes={}, start=start,
end=end)
algo = TradingAlgorithm(initialize=initialize, handle_data=handle_data)
results = algo.run(data).dropna()
fig = plt.figure()
ax1 = fig.add_subplot(211, ylabel='portfolio value')
results.portfolio_value.plot(ax=ax1)
ax2 = fig.add_subplot(212)
results[['AAPL', 'short_ema', 'long_ema']].plot(ax=ax2)
ax2.plot(results.ix[results.buy].index, results.short_ema[results.buy],
'^', markersize=10, color='m')
ax2.plot(results.ix[results.sell].index, results.short_ema[results.sell],
'v', markersize=10, color='k')
plt.legend(loc=0)
plt.gcf().set_size_inches(18, 8)
plt.show()