Backtrader Target Orders for Size, Value, or Portfolio Allocation

# order_target.py


```py
#!/usr/bin/env python
# -*- coding: utf-8; py-indent-offset:4 -*-
###############################################################################
#
# Copyright (C) 2015-2023 Daniel Rodriguez
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program.  If not, see <http://www.gnu.org/licenses/>.
#
###############################################################################
from __future__ import (absolute_import, division, print_function,
                        unicode_literals)

import argparse
from datetime import datetime

import backtrader as bt


class TheStrategy(bt.Strategy):
    '''
    This strategy is loosely based on some of the examples from the Van
    K. Tharp book: *Trade Your Way To Financial Freedom*. The logic:

      - Enter the market if:
        - The MACD.macd line crosses the MACD.signal line to the upside
        - The Simple Moving Average has a negative direction in the last x
          periods (actual value below value x periods ago)

     - Set a stop price x times the ATR value away from the close

     - If in the market:

       - Check if the current close has gone below the stop price. If yes,
         exit.
       - If not, update the stop price if the new stop price would be higher
         than the current
    '''

    params = (
        ('use_target_size', False),
        ('use_target_value', False),
        ('use_target_percent', False),
    )

    def notify_order(self, order):
        if order.status == order.Completed:
            pass

        if not order.alive():
            self.order = None  # indicate no order is pending

    def start(self):
        self.order = None  # sentinel to avoid operrations on pending order

    def next(self):
        dt = self.data.datetime.date()

        portfolio_value = self.broker.get_value()
        print('%04d - %s - Position Size:     %02d - Value %.2f' %
              (len(self), dt.isoformat(), self.position.size, portfolio_value))

        data_value = self.broker.get_value([self.data])

        if self.p.use_target_value:
            print('%04d - %s - data value %.2f' %
                  (len(self), dt.isoformat(), data_value))

        elif self.p.use_target_percent:
            port_perc = data_value / portfolio_value
            print('%04d - %s - data percent %.2f' %
                  (len(self), dt.isoformat(), port_perc))

        if self.order:
            return  # pending order execution

        size = dt.day
        if (dt.month % 2) == 0:
            size = 31 - size

        if self.p.use_target_size:
            target = size
            print('%04d - %s - Order Target Size: %02d' %
                  (len(self), dt.isoformat(), size))

            self.order = self.order_target_size(target=size)

        elif self.p.use_target_value:
            value = size * 1000

            print('%04d - %s - Order Target Value: %.2f' %
                  (len(self), dt.isoformat(), value))

            self.order = self.order_target_value(target=value)

        elif self.p.use_target_percent:
            percent = size / 100.0

            print('%04d - %s - Order Target Percent: %.2f' %
                  (len(self), dt.isoformat(), percent))

            self.order = self.order_target_percent(target=percent)


def runstrat(args=None):
    args = parse_args(args)

    cerebro = bt.Cerebro()
    cerebro.broker.setcash(args.cash)

    dkwargs = dict()
    if args.fromdate is not None:
        dkwargs['fromdate'] = datetime.strptime(args.fromdate, '%Y-%m-%d')
    if args.todate is not None:
        dkwargs['todate'] = datetime.strptime(args.todate, '%Y-%m-%d')

    # data
    data = bt.feeds.YahooFinanceCSVData(dataname=args.data, **dkwargs)
    cerebro.adddata(data)

    # strategy
    cerebro.addstrategy(TheStrategy,
                        use_target_size=args.target_size,
                        use_target_value=args.target_value,
                        use_target_percent=args.target_percent)

    cerebro.run()

    if args.plot:
        pkwargs = dict(style='bar')
        if args.plot is not True:  # evals to True but is not True
            npkwargs = eval('dict(' + args.plot + ')')  # args were passed
            pkwargs.update(npkwargs)

        cerebro.plot(**pkwargs)


def parse_args(pargs=None):

    parser = argparse.ArgumentParser(
        formatter_class=argparse.ArgumentDefaultsHelpFormatter,
        description='Sample for Order Target')

    parser.add_argument('--data', required=False,
                        default='../../datas/yhoo-1996-2015.txt',
                        help='Specific data to be read in')

    parser.add_argument('--fromdate', required=False,
                        default='2005-01-01',
                        help='Starting date in YYYY-MM-DD format')

    parser.add_argument('--todate', required=False,
                        default='2006-12-31',
                        help='Ending date in YYYY-MM-DD format')

    parser.add_argument('--cash', required=False, action='store',
                        type=float, default=1000000,
                        help='Ending date in YYYY-MM-DD format')

    pgroup = parser.add_mutually_exclusive_group(required=True)

    pgroup.add_argument('--target-size', required=False, action='store_true',
                        help=('Use order_target_size'))

    pgroup.add_argument('--target-value', required=False, action='store_true',
                        help=('Use order_target_value'))

    pgroup.add_argument('--target-percent', required=False,
                        action='store_true',
                        help=('Use order_target_percent'))

    # Plot options
    parser.add_argument('--plot', '-p', nargs='?', required=False,
                        metavar='kwargs', const=True,
                        help=('Plot the read data applying any kwargs passed\n'
                              '\n'
                              'For example:\n'
                              '\n'
                              '  --plot style="candle" (to plot candles)\n'))

    if pargs is not None:
        return parser.parse_args(pargs)

    return parser.parse_args()


if __name__ == '__main__':
    runstrat()

```