本节介绍如何使用收盘价的SMA价格的策略

from pyalgotrade import strategyfrom pyalgotrade.barfeed import yahoofeed from pyalgotrade.technical import ma class MyStrategy(strategy.BacktestingStrategy): def __init__(self, feed, instrument): super(MyStrategy, self).__init__(feed) # We want a 15 period SMA over the closing prices. self.__sma = ma.SMA(feed[instrument].getCloseDataSeries(), 15) self.__instrument = instrument def onBars(self, bars): bar = bars[self.__instrument] self.info("%s %s" % (bar.getClose(), self.__sma[-1])) # Load the yahoo feed from the CSV file feed = yahoofeed.Feed() feed.addBarsFromCSV("orcl", "orcl-2000.csv") # Evaluate the strategy with the feed's bars. myStrategy = MyStrategy(feed, "orcl") myStrategy.run()

这与前面的例子非常相似，只是：

• 用收盘价格数据系列中初始化SMA过滤器。
• 打印当前的SMA值以及收盘价。
  如果您运行脚本，您应该看到收盘价格和相应的SMA值，但在这种情况下，前14个SMA值为空。那是因为我们需要至少15个值来求取SMA：

  2000-01-03 00:00:00 strategy [INFO] 118.12 None2000-01-04 00:00:00 strategy [INFO] 107.69 None2000-01-05 00:00:00 strategy [INFO] 102.0 None2000-01-06 00:00:00 strategy [INFO] 96.0 None2000-01-07 00:00:00 strategy [INFO] 103.37 None2000-01-10 00:00:00 strategy [INFO] 115.75 None2000-01-11 00:00:00 strategy [INFO] 112.37 None2000-01-12 00:00:00 strategy [INFO] 105.62 None2000-01-13 00:00:00 strategy [INFO] 105.06 None2000-01-14 00:00:00 strategy [INFO] 106.81 None2000-01-18 00:00:00 strategy [INFO] 111.25 None2000-01-19 00:00:00 strategy [INFO] 57.13 None2000-01-20 00:00:00 strategy [INFO] 59.25 None2000-01-21 00:00:00 strategy [INFO] 59.69 None2000-01-24 00:00:00 strategy [INFO] 54.19 94.28666666672000-01-25 00:00:00 strategy [INFO] 56.44 90.1746666667...2000-12-27 00:00:00 strategy [INFO] 30.69 29.98666666672000-12-28 00:00:00 strategy [INFO] 31.06 30.04466666672000-12-29 00:00:00 strategy [INFO] 29.06 30.0946666667

作者：readilen

链接：http://www.jianshu.com/p/7a9e2635bfa1

來源：简书

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