mirror of
https://github.com/wassname/catalyst.git
synced 2026-08-12 11:50:11 +08:00
95 lines
3.2 KiB
Python
95 lines
3.2 KiB
Python
#!/usr/bin/env python
|
|
#
|
|
# Copyright 2013 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.
|
|
|
|
import matplotlib.pyplot as plt
|
|
|
|
from zipline.algorithm import TradingAlgorithm
|
|
from zipline.utils.factory import load_from_yahoo
|
|
|
|
# Import exponential moving average from talib wrapper
|
|
from zipline.transforms.ta import EMA
|
|
|
|
from datetime import datetime
|
|
import pytz
|
|
|
|
|
|
class DualEMATaLib(TradingAlgorithm):
|
|
|
|
"""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).
|
|
|
|
"""
|
|
|
|
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)
|
|
data = load_from_yahoo(stocks=['AAPL'], indexes={}, start=start,
|
|
end=end)
|
|
|
|
dma = DualEMATaLib()
|
|
results = dma.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)
|