SMA_20.py

# A simple algo trading moving average strategy, this time simulating actual trading. The idea is very simple:

If the adjusted close price is above the SMA(20) we enter a long position (we place a buy market order).
If a long position is in place, and the adjusted close price drops below the SMA(20)
we exit the long position (we place a sell market order).


#The first thing that we’ll need to test our strategies is some data.

# Let’s use Oracle’s stock prices for year 2000, which we’ll download with the following command:
python -c "from pyalgotrade.tools import yahoofinance; yahoofinance.download_daily_bars('orcl', 2000, 'orcl-2000.csv')"



from pyalgotrade import strategy
from pyalgotrade.barfeed import yahoofeed
from pyalgotrade.technical import ma


class MyStrategy(strategy.BacktestingStrategy):
    def __init__(self, feed, instrument, smaPeriod):
        super(MyStrategy, self).__init__(feed, 1000)
        self.__position = None
        self.__instrument = instrument
        # We'll use adjusted close values instead of regular close values.
        self.setUseAdjustedValues(True)
        self.__sma = ma.SMA(feed[instrument].getPriceDataSeries(), smaPeriod)

    def onEnterOk(self, position):
        execInfo = position.getEntryOrder().getExecutionInfo()
        self.info("BUY at $%.2f" % (execInfo.getPrice()))

    def onEnterCanceled(self, position):
        self.__position = None

    def onExitOk(self, position):
        execInfo = position.getExitOrder().getExecutionInfo()
        self.info("SELL at $%.2f" % (execInfo.getPrice()))
        self.__position = None

    def onExitCanceled(self, position):
        # If the exit was canceled, re-submit it.
        self.__position.exitMarket()

    def onBars(self, bars):
        # Wait for enough bars to be available to calculate a SMA.
        if self.__sma[-1] is None:
            return

        bar = bars[self.__instrument]
        # If a position was not opened, check if we should enter a long position.
        if self.__position is None:
            if bar.getPrice() > self.__sma[-1]:
                # Enter a buy market order for 10 shares. The order is good till canceled.
                self.__position = self.enterLong(self.__instrument, 10, True)
        # Check if we have to exit the position.
        elif bar.getPrice() < self.__sma[-1] and not self.__position.exitActive():
            self.__position.exitMarket()


def run_strategy(smaPeriod):
    # Load the yahoo feed from the CSV file
    feed = yahoofeed.Feed()
    feed.addBarsFromCSV("orcl", "orcl-2000.csv")

    # Evaluate the strategy with the feed.
    myStrategy = MyStrategy(feed, "orcl", smaPeriod)
    myStrategy.run()
    print "Final portfolio value: $%.2f" % myStrategy.getBroker().getEquity()

run_strategy(20)


## the next step is to optimise for the parameter of the SMA period length - not necessarily optimal at 20