No error shown but no results, simply double crossover

JAS2210

Hello again friends,
I tried a simple strategy with 4 moving averages . MA1 e MA2 for a buy crossover and MA3 and MA4 for a sell/closing crossover .
The main reason is that I want to find eventually optimezed parameters of this 4 moving average.
But when I run no errors and no results... Where I can put some feedback like print or log to see If it is doing backtest or not? I use def stop() but nothing in the output..
code:

# Create a Stratey
class TestStrategy(bt.Strategy):
    params = (
        ('ma1period', 15),
        ('ma2period', 50),
        ('ma3period', 15),
        ('ma4period', 50))

    def log(self, txt, dt=None, doprint=False):
        ''' Logging function fot this strategy'''
        if self.params.printlog or doprint:
            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

        # Add a MovingAverageSimple indicator
        sma1 = bt.indicators.SimpleMovingAverage(
            self.datas[0], period=self.params.ma1period)
        sma2 = bt.indicators.SimpleMovingAverage(
            self.datas[0], period=self.params.ma2period)
        sma3 = bt.indicators.SimpleMovingAverage(
            self.datas[0], period=self.params.ma3period)
        sma4 = bt.indicators.SimpleMovingAverage(
            self.datas[0], period=self.params.ma4period)          
        
        self.crossover_b= bt.indicators.CrossOver(sma1, sma2)
        self.crossover_s= bt.indicators.CrossOver(sma3, sma4)

    def next(self):
        print("sto facendo")
        # Simply log the closing price of the series from the reference
        self.log('Close, %.2f' % self.dataclose[0])

        # 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:
            #if self.rsi[0]< self.params.rsi_treshold:
                if self.crossover_b > 0:
                    
                    # Not yet ... we MIGHT BUY if ...
                    #if self.dataclose[0] > self.sma1[0]:

                    # BUY, BUY, BUY!!! (with all possible default parameters)
                    self.log('BUY CREATE, %.2f' % self.dataclose[0])
                    self.buy()

        else:
            if self.crossover_s < 0:  # in the market & cross to the downside the other two moving average 
                self.close()  # close long position

if __name__ == '__main__':
    # Create a cerebro entity
    cerebro = bt.Cerebro()

    # Add a strategy
    strats = cerebro.optstrategy(
        TestStrategy,
        ma1period=range(10, 12),
        ma2period=range(20, 22), 
        ma3period=range(10, 12), 
        ma4period=range(20, 22)
        )
    # Add the Data Feed to Cerebro
    cerebro.adddata(data)

    # Set our desired cash start
    cerebro.broker.setcash(1000000)
    
    cerebro.addanalyzer(btanalyzers.SharpeRatio, _name = "sharpe")
    cerebro.addanalyzer(btanalyzers.DrawDown, _name = "drawdown")
    cerebro.addanalyzer(btanalyzers.Returns, _name = "returns")

    # Add a FixedSize sizer according to the stake
    cerebro.addsizer(bt.sizers.FixedSize, stake=0.5)

    # Set the commission
    cerebro.broker.setcommission(commission=0.001)

    # Run over everything
    back=cerebro.run()

Tony Shacklock

I'm new to Backtrader, too, but I may be able to help with this. (It helps my learning, too.)

I managed to get your code to run by doing these things:
Firstly, to get logging to work, add (printLog, True) to your strategy parameters, or call self.log(txt, True).
I reverted to non-optimisation to start with:

Change your strategy parameter default values to integers (not ranges).
Change cerebro.optstrategy() to cerebro.addstrategy().
Then if you uadd cerebro.plot() at the end you should see some output.

For optimisation:

Add the maxcpus=1 to your Cerebro instance, i.e. back=cerebro.run(maxcpus=1). At least my system needs it.

I hope that helps.

Tony Shacklock

I just spotted a couple of error in my response:
The parameter to add to the strategy should be ('printlog', True), not printLog.
The call to self.log(txt, doprint=True).
T

JAS2210

@tony-shacklock Hi , Thank you.
Now it works fine. But I thought when it runs blank it suggests some problems with the condition of buy or sell or in position, but those were right . I fell like sometimes backtrader don' t want to work proprely ahah maybe is jupyter notebook.
Anyway now I will do optimazation for this 4 parameters , I' ll let you know results.