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One can now add a unique identifier to each trade, even if running on the same data.

Following a request at Tick Data and Resampling release of backtrader support “MultiTrades”, ie: the ability to assign a tradeid to orders. This id is passed on to Trades which makes it possible to have different categories of trades and have them simultaneously open.

The tradeid can be specified when:

  • Calling with kwarg tradeid

  • Calling with kwarg tradeid

  • Creating an Order instance with kwarg tradeid

If not specified the default value is:

  • tradeid = 0

To test a small script has been implemented, visualizing the result with the implementation of a custom MTradeObserver which assigns different markers on the plot according tradeid (for the test values 0, 1 and 2 are used)

The script supports using the three ids (0, 1, 2) or simply use 0 (default)

An execution without enabling multiple ids:

$ ./ --plot

With the resulting chart showing all Trades carry id 0 and therefore cannot be diferentiated.


A second execution enables multitrades by cycling amongs 0, 1 and 2:

$ ./ --plot --mtrade

And now 3 different markers alternate showing each Trade can be distinguished using the tradeid member.



backtrader tries to use models which mimic reality. Therefore “trades” are not calculated by the Broker instance which only takes care of oders.

Trades are calculated by the Strategy.

And hence tradeid (or something similar) may not be supported by a real life broker in which case manually keeping track of the unique orde id assigned by the broker would be needed.

Now, the code for the custom observer

from __future__ import (absolute_import, division, print_function,

import math

import backtrader as bt

class MTradeObserver(
    lines = ('Id_0', 'Id_1', 'Id_2')

    plotinfo = dict(plot=True, subplot=True, plotlinelabels=True)

    plotlines = dict(
        Id_0=dict(marker='*', markersize=8.0, color='lime', fillstyle='full'),
        Id_1=dict(marker='o', markersize=8.0, color='red', fillstyle='full'),
        Id_2=dict(marker='s', markersize=8.0, color='blue', fillstyle='full')

    def next(self):
        for trade in self._owner._tradespending:

            if is not

            if not trade.isclosed:

            self.lines[trade.tradeid][0] = trade.pnlcomm

The main script usage:

$ ./ --help
usage: [-h] [--data DATA] [--fromdate FROMDATE]
                      [--todate TODATE] [--mtrade] [--period PERIOD]
                      [--onlylong] [--cash CASH] [--comm COMM] [--mult MULT]
                      [--margin MARGIN] [--stake STAKE] [--plot]
                      [--numfigs NUMFIGS]


optional arguments:
  -h, --help            show this help message and exit
  --data DATA, -d DATA  data to add to the system
  --fromdate FROMDATE, -f FROMDATE
                        Starting date in YYYY-MM-DD format
  --todate TODATE, -t TODATE
                        Starting date in YYYY-MM-DD format
  --mtrade              Activate MultiTrade Ids
  --period PERIOD       Period to apply to the Simple Moving Average
  --onlylong, -ol       Do only long operations
  --cash CASH           Starting Cash
  --comm COMM           Commission for operation
  --mult MULT           Multiplier for futures
  --margin MARGIN       Margin for each future
  --stake STAKE         Stake to apply in each operation
  --plot, -p            Plot the read data
  --numfigs NUMFIGS, -n NUMFIGS
                        Plot using numfigs figures

The code for the script.

from __future__ import (absolute_import, division, print_function,

import argparse
import datetime
import itertools

# The above could be sent to an independent module
import backtrader as bt
import backtrader.feeds as btfeeds
import backtrader.indicators as btind

import mtradeobserver

class MultiTradeStrategy(bt.Strategy):
    '''This strategy buys/sells upong the close price crossing
    upwards/downwards a Simple Moving Average.

    It can be a long-only strategy by setting the param "onlylong" to True
    params = dict(

    def log(self, txt, dt=None):
        if self.p.printout:
            dt = dt or[0]
            dt = bt.num2date(dt)
            print('%s, %s' % (dt.isoformat(), txt))

    def __init__(self):
        # To control operation entries
        self.order = None

        # Create SMA on 2nd data
        sma = btind.MovAv.SMA(, period=self.p.period)
        # Create a CrossOver Signal from close an moving average
        self.signal = btind.CrossOver(, sma)

        # To alternate amongst different tradeids
        if self.p.mtrade:
            self.tradeid = itertools.cycle([0, 1, 2])
            self.tradeid = itertools.cycle([0])

    def next(self):
        if self.order:
            return  # if an order is active, no new orders are allowed

        if self.signal > 0.0:  # cross upwards
            if self.position:
                self.log('CLOSE SHORT , %.2f' %[0])

            self.log('BUY CREATE , %.2f' %[0])
            self.curtradeid = next(self.tradeid)
  , tradeid=self.curtradeid)

        elif self.signal < 0.0:
            if self.position:
                self.log('CLOSE LONG , %.2f' %[0])

            if not self.p.onlylong:
                self.log('SELL CREATE , %.2f' %[0])
                self.curtradeid = next(self.tradeid)
                self.sell(size=self.p.stake, tradeid=self.curtradeid)

    def notify_order(self, order):
        if order.status in [bt.Order.Submitted, bt.Order.Accepted]:
            return  # Await further notifications

        if order.status == order.Completed:
            if order.isbuy():
                buytxt = 'BUY COMPLETE, %.2f' % order.executed.price
                self.log(buytxt, order.executed.dt)
                selltxt = 'SELL COMPLETE, %.2f' % order.executed.price
                self.log(selltxt, order.executed.dt)

        elif order.status in [order.Expired, order.Canceled, order.Margin]:
            self.log('%s ,' % order.Status[order.status])
            pass  # Simply log

        # Allow new orders
        self.order = None

    def notify_trade(self, trade):
        if trade.isclosed:
            self.log('TRADE PROFIT, GROSS %.2f, NET %.2f' %
                     (trade.pnl, trade.pnlcomm))

        elif trade.justopened:
            self.log('TRADE OPENED, SIZE %2d' % trade.size)

def runstrategy():
    args = parse_args()

    # Create a cerebro
    cerebro = bt.Cerebro()

    # Get the dates from the args
    fromdate = datetime.datetime.strptime(args.fromdate, '%Y-%m-%d')
    todate = datetime.datetime.strptime(args.todate, '%Y-%m-%d')

    # Create the 1st data
    data = btfeeds.BacktraderCSVData(,

    # Add the 1st data to cerebro

    # Add the strategy

    # Add the commission - only stocks like a for each operation

    # Add the commission - only stocks like a for each operation,

    # Add the MultiTradeObserver

    # And run it

    # Plot if requested
    if args.plot:
        cerebro.plot(numfigs=args.numfigs, volume=False, zdown=False)

def parse_args():
    parser = argparse.ArgumentParser(description='MultiTrades')

    parser.add_argument('--data', '-d',
                        help='data to add to the system')

    parser.add_argument('--fromdate', '-f',
                        help='Starting date in YYYY-MM-DD format')

    parser.add_argument('--todate', '-t',
                        help='Starting date in YYYY-MM-DD format')

    parser.add_argument('--mtrade', action='store_true',
                        help='Activate MultiTrade Ids')

    parser.add_argument('--period', default=15, type=int,
                        help='Period to apply to the Simple Moving Average')

    parser.add_argument('--onlylong', '-ol', action='store_true',
                        help='Do only long operations')

    parser.add_argument('--cash', default=100000, type=int,
                        help='Starting Cash')

    parser.add_argument('--comm', default=2, type=float,
                        help='Commission for operation')

    parser.add_argument('--mult', default=10, type=int,
                        help='Multiplier for futures')

    parser.add_argument('--margin', default=2000.0, type=float,
                        help='Margin for each future')

    parser.add_argument('--stake', default=1, type=int,
                        help='Stake to apply in each operation')

    parser.add_argument('--plot', '-p', action='store_true',
                        help='Plot the read data')

    parser.add_argument('--numfigs', '-n', default=1,
                        help='Plot using numfigs figures')

    return parser.parse_args()

if __name__ == '__main__':