#!/usr/bin/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.transforms import MovingAverage from zipline.utils.factory import load_from_yahoo class DualMovingAverage(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=200, long_window=400): # Add 2 mavg transforms, one with a long window, one # with a short window. self.add_transform(MovingAverage, 'short_mavg', ['price'], window_length=short_window) self.add_transform(MovingAverage, 'long_mavg', ['price'], window_length=long_window) # To keep track of whether we invested in the stock or not self.invested = False def handle_data(self, data): self.short_mavg = data['AAPL'].short_mavg['price'] self.long_mavg = data['AAPL'].long_mavg['price'] self.buy = False self.sell = False if self.short_mavg > self.long_mavg and not self.invested: self.order('AAPL', 100) self.invested = True self.buy = True elif self.short_mavg < self.long_mavg and self.invested: self.order('AAPL', -100) self.invested = False self.sell = True self.record(short_mavg=self.short_mavg, long_mavg=self.long_mavg, buy=self.buy, sell=self.sell) if __name__ == '__main__': data = load_from_yahoo(stocks=['AAPL'], indexes={}) dma = DualMovingAverage() results = dma.run(data) print results.short_mavg fig = plt.figure() ax1 = fig.add_subplot(211) results.portfolio_value.plot(ax=ax1) ax2 = fig.add_subplot(212) data['AAPL'].plot(ax=ax2) results[['short_mavg', 'long_mavg']].plot(ax=ax2) ax2.plot(results.ix[results.buy].index, results.short_mavg[results.buy], '^', markersize=10, color='m') ax2.plot(results.ix[results.sell].index, results.short_mavg[results.sell], 'v', markersize=10, color='k') plt.legend(loc=0) plt.show()