Backtrader screener strategy

Screener strategy

# Create a Stratey
class TestStrategy(bt.Strategy):
    params = (
        ('maperiod', 20),
    )

    def log(self, txt, optimization=False, dt=None):
        if optimization:
            return
        
        ''' Logging function for this strategy'''
        dt = dt or self.datas[0].datetime.date(0)
        print('%s, %s' % (dt.isoformat(), txt))

    def __init__(self):
        # Keep a reference to the "close" line in the data[0] dataseries
        self.dataclose = self.datas[0].close

        # To keep track of pending orders and buy price/commission
        self.order = None
        self.buyprice = None
        self.buycomm = None

        self.hma = bt.indicators.HullMovingAverage(
            self.datas[0], period=self.params.maperiod)

    def notify_order(self, order):
        global lastBuy
        if order.status in [order.Submitted, order.Accepted]:
            # Buy/Sell order submitted/accepted to/by broker - Nothing to do
            return

        # Check if an order has been completed
        # Attention: broker could reject order if not enough cash
        if order.status in [order.Completed]:
            if order.isbuy():
                lastBuy = self.datas[0].datetime.date(0)
                self.log(
                    'BUY EXECUTED, Price: $%.2f, Cost: $%.2f ($Comm %.2f)' %
                    (order.executed.price,
                     order.executed.value,
                     order.executed.comm), optimization=optimization)

                self.buyprice = order.executed.price
                self.buycomm = order.executed.comm
            else:  # Sell
                self.log('SELL EXECUTED, Price: $%.2f, Cost: $%.2f (Comm $%.2f)' %
                         (order.executed.price,
                          order.executed.value,
                          order.executed.comm), optimization=optimization)

            self.bar_executed = len(self)

        elif order.status in [order.Canceled, order.Margin, order.Rejected]:
            self.log('Order Canceled/Margin/Rejected', optimization=optimization)

        # Write down: no pending order
        self.order = None

    def notify_trade(self, trade):
        if not trade.isclosed:
            return

        self.log('OPERATION GROSS $%.2f, NET $%.2f, PROFIT %.2f%%' %
                 (trade.pnl, trade.pnlcomm, trade.pnlcomm/trade.price*100), optimization=optimization)
        

    def next(self):
        # Check if an order is pending ... if yes, we cannot send a 2nd one
        if self.order:
            return

        # Check if we are in the market
        if not self.position:
            # check for HMA trend reversal
            if self.hma[-2] >= self.hma[-1] and \
               self.hma[-1] < self.hma[0]:

                self.log('BUY CREATE, $%.2f' % self.dataclose[0], optimization=optimization)

                # Keep track of the created order to avoid a 2nd order
                self.order = self.buy()

        else:
            # check for HMA trend reversal
            if self.hma[-2] <= self.hma[-1] and \
               self.hma[-1] > self.hma[0]:

                self.log('SELL CREATE, $%.2f' % self.dataclose[0], optimization=optimization)

                # Keep track of the created order to avoid a 2nd order
                self.order = self.sell()

    def stop(self):
        self.log('(MA Period %2d) Ending Value %.2f' %
                 (self.params.maperiod, self.broker.getvalue()), optimization=optimization)
        
        # keep track of results for each period backtest
        strategyResults[self.params.maperiod] = self.broker.getvalue()