Buy / Sell executing - but not being identified as Trades

sangoman

Hi,

Newbie Backtrader here. First up - thanks for the powerful tool.

Am importing a DF from a CSV and using it to generate buy’s and sells. Backtrader is able to identify Buy/ Sell orders and is also able to execute buys and sells.

However, Backtrader does not seem to be identifying the Buys and Sells as Trades. As a result the pnlplus and the pnlminus columns in the output file are all empty. Also when I plot using cerebro.plot(), I get a blank for the Trades section.

Am sure I am making a noob mistake. Please help.

Thank you.

Regards,
Sangoman

sangoman

Attaching Code :


import math
import pandas as pd
import matplotlib
matplotlib.use('QT5Agg')
from backtrader.feeds import PandasData
from backtrader.feeds import GenericCSVData


class PandasData_Signal(PandasData):
    # Add a 'pe' line to the inherited ones from the base class
    lines = ('Signal',)
    
    # add the parameter to the parameters inherited from the base class
    params = (('Signal', 18),)

import backtrader as bt


class MLSignal(bt.Strategy):
    def log(self, txt, dt=None):
        dt = dt or self.datas[0].datetime.datetime(0)
        print('%s,%s' % (dt.isoformat(),txt))
        pass

    def __init__(self):
        # Keep a reference to the "close" line in the data[0] dataseries
        self.dataclose = self.datas[0].close
        self.datasignal = self.datas[0].Signal
        self.order = None
        self.trade = None
        self.buyprice = None
        self.buycomm = None

    def notify_order(self, order):
        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():
                self.log(
                    'BUY EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %
                    (order.executed.price,
                     order.executed.value,
                     order.executed.comm))

                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))

                self.sellprice = order.executed.price
                self.sellcomm = order.executed.comm

            self.bar_executed = len(self)

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

        self.order = None


    def notify_trade(self, trade):
        if trade.justopened:
            self.log('----TRADE OPENED----')
            self.log('Size: {:.3f}, value: {:.3f}'.format(trade.size, trade.value))
        elif trade.isclosed:
            self.log('----TRADE CLOSED----')
            self.log('Profit: {} Gross {}, Net {}'.format(trade.size, round(trade.pnl,2), round(trade.pnlcomm,2)))
        else:
            self.log('NO TRADE')
            
            
    def next(self):
        self.log(' Close, %.2f' % self.dataclose[0])
        self.log(' Signal, %.2f' % self.datasignal[0])
        
        if self.order:
            return
        
        if self.datasignal[0] == 1:
            self.log('BUY CREATE, %.2f' % self.dataclose[0])
            self.order = self.buy()
        
        if self.datasignal[0] == -1:
            self.log('SELL CREATE, %.2f' % self.dataclose[0])
            self.order = self.sell()


class maxRiskSizer(bt.Sizer):
    '''
    Returns the number of shares rounded down that can be purchased for the
    max risk tolerance
    '''
    params = (('risk', 0.2),)

    def _getsizing(self, comminfo, cash, data, isbuy):
        if isbuy == True:
            size = math.floor((cash * self.p.risk) / data[0])
        else:
            size = math.floor((cash * self.p.risk) / data[0]) * -1
        return size




daaata = pd.read_csv("C:/Users/sangramb/Template/Development_Folder/Learning/SuperTrend.csv")
daaata['timestamp'] = pd.to_datetime(daaata['timestamp'],format='%Y-%m-%d %H:%M:%S')  

#print(dataframe.head())
data = PandasData_Signal(dataname=daaata,
                     #dtformat = ('%Y-%m-%d %H:%M:%S'),
                     datetime=0,
                     open=1,
                     high=2,
                     low=3,
                     close=4,
                     #volume=5,
                     #openinterest=-1
                     Signal=18)

cerebro = bt.Cerebro()

cerebro.broker.setcash(100000000)
print("STARTING CASH VALUE")
print(cerebro.broker.getvalue())
cerebro.addsizer(maxRiskSizer)


#cerebro.addwriter(bt.WriterFile, csv=args.writercsv, rounding= None)
cerebro.addwriter(bt.WriterFile, csv = True, out='signal_strategy_results1.csv')

# Set the commission
cerebro.broker.setcommission(commission=0.0015)

# Set our desired cash start
cerebro.adddata(data)
# Set our strategy
cerebro.addstrategy(MLSignal)
cerebro.run()
print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
print('Final value is %.2f times the initial investment'%(cerebro.broker.getvalue()/100000000))

#cerebro.addanalyzer(btanalyzers.DrawDown, _name='myDrawDown')
#cerebro.addanalyzer(btanalyzers.DrawDown, _name='myDrawDown')



cerebro.plot(iplot = False)

sangoman

And finally a pic of the Plot

@sangoman

vladisld

@sangoman said in Buy / Sell executing - but not being identified as Trades:

Backtrader does not seem to be identifying the Buys and Sells as Trades

AFAIU Backtrader reports a trade when particular position goes to zero. So if trades are not reported it could be related to the maxRiskSizer that you are using.

Could you attach the log output of your run and print the order sizes and the position on each order notification?

sangoman

@vladisld - thank you for your prompt and helpful message.

It seems like you were/ are absolutely correct. Here is a short extract from the log file (unable to paste the excel - sorry)

Your hunch was right - the size of the positions is different. Which then leads me to an alternate question. How do I use a position size such that for every long position I am using 20% of my portfolio. And when it comes to closing, I simply square the position.

2021-01-29T00:00:00, Signal, -1.00
2021-01-29T00:00:00,SELL CREATE, 34252.20
2021-01-30T00:00:00,SELL EXECUTED, Price: 34246.28, Size: -308.00, Comm 15821.78
2021-01-30T00:00:00, Close, 34262.88
2021-01-30T00:00:00, Signal, 0.00
2021-01-31T00:00:00, Close, 33092.98
2021-01-31T00:00:00, Signal, 0.00
2021-02-01T00:00:00, Close, 33526.37
2021-02-01T00:00:00, Signal, 0.00
2021-02-02T00:00:00, Close, 35466.24
2021-02-02T00:00:00, Signal, 0.00
2021-02-03T00:00:00, Close, 37618.87
2021-02-03T00:00:00, Signal, 0.00
2021-02-04T00:00:00, Close, 36936.66
2021-02-04T00:00:00, Signal, 0.00
2021-02-05T00:00:00, Close, 38290.24
2021-02-05T00:00:00, Signal, 0.00
2021-02-06T00:00:00, Close, 39186.94
2021-02-06T00:00:00, Signal, 0.00
2021-02-07T00:00:00, Close, 38795.69
2021-02-07T00:00:00, Signal, 0.00
2021-02-08T00:00:00, Close, 46374.87
2021-02-08T00:00:00, Signal, 0.00
2021-02-09T00:00:00, Close, 46420.42
2021-02-09T00:00:00, Signal, 1.00
2021-02-09T00:00:00,BUY CREATE, 46420.42
2021-02-10T00:00:00,BUY EXECUTED, Price: 46420.42, Size: 273.00, Comm 19009.16
2021-02-10T00:00:00, Close, 44807.58