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https://github.com/wassname/catalyst.git
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Stewart Douglas
129 lines
4.2 KiB
Python
Executable File
129 lines
4.2 KiB
Python
Executable File
#!/usr/bin/env python
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#
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# Copyright 2014 Quantopian, Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Dual Moving Average Crossover algorithm.
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This algorithm buys apple once its short moving average crosses
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its long moving average (indicating upwards momentum) and sells
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its shares once the averages cross again (indicating downwards
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momentum).
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"""
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from zipline.api import order_target, record, symbol, history, add_history
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def initialize(context):
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# Register 2 histories that track daily prices,
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# one with a 100 window and one with a 300 day window
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add_history(100, '1d', 'price')
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add_history(300, '1d', 'price')
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context.sym = symbol('AAPL')
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context.i = 0
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def handle_data(context, data):
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# Skip first 300 days to get full windows
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context.i += 1
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if context.i < 300:
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return
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# Compute averages
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# history() has to be called with the same params
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# from above and returns a pandas dataframe.
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short_mavg = history(100, '1d', 'price').mean()
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long_mavg = history(300, '1d', 'price').mean()
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# Trading logic
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if short_mavg[context.sym] > long_mavg[context.sym]:
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# order_target orders as many shares as needed to
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# achieve the desired number of shares.
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order_target(context.sym, 100)
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elif short_mavg[context.sym] < long_mavg[context.sym]:
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order_target(context.sym, 0)
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# Save values for later inspection
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record(AAPL=data[context.sym].price,
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short_mavg=short_mavg[context.sym],
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long_mavg=long_mavg[context.sym])
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# Note: this function can be removed if running
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# this algorithm on quantopian.com
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def analyze(context=None, results=None):
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import matplotlib.pyplot as plt
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import logbook
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logbook.StderrHandler().push_application()
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log = logbook.Logger('Algorithm')
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fig = plt.figure()
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ax1 = fig.add_subplot(211)
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results.portfolio_value.plot(ax=ax1)
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ax1.set_ylabel('Portfolio value (USD)')
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ax2 = fig.add_subplot(212)
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ax2.set_ylabel('Price (USD)')
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# If data has been record()ed, then plot it.
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# Otherwise, log the fact that no data has been recorded.
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if ('AAPL' in results and 'short_mavg' in results and
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'long_mavg' in results):
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results['AAPL'].plot(ax=ax2)
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results[['short_mavg', 'long_mavg']].plot(ax=ax2)
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trans = results.ix[[t != [] for t in results.transactions]]
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buys = trans.ix[[t[0]['amount'] > 0 for t in
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trans.transactions]]
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sells = trans.ix[
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[t[0]['amount'] < 0 for t in trans.transactions]]
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ax2.plot(buys.index, results.short_mavg.ix[buys.index],
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'^', markersize=10, color='m')
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ax2.plot(sells.index, results.short_mavg.ix[sells.index],
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'v', markersize=10, color='k')
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plt.legend(loc=0)
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else:
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msg = 'AAPL, short_mavg & long_mavg data not captured using record().'
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ax2.annotate(msg, xy=(0.1, 0.5))
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log.info(msg)
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plt.show()
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# Note: this if-block should be removed if running
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# this algorithm on quantopian.com
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if __name__ == '__main__':
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from datetime import datetime
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import pytz
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from zipline.algorithm import TradingAlgorithm
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from zipline.utils.factory import load_from_yahoo
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# Set the simulation start and end dates.
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start = datetime(2011, 1, 1, 0, 0, 0, 0, pytz.utc)
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end = datetime(2013, 1, 1, 0, 0, 0, 0, pytz.utc)
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# Load price data from yahoo.
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data = load_from_yahoo(stocks=['AAPL'], indexes={}, start=start,
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end=end)
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# Create and run the algorithm.
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algo = TradingAlgorithm(initialize=initialize, handle_data=handle_data,
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identifiers=['AAPL'])
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results = algo.run(data)
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# Plot the portfolio and asset data.
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analyze(results=results)
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