SMA Crossover Long Strategy

Code backtrader

Summary

This code example implements a long-only moving average crossover strategy in Backtrader. It calculates two simple moving averages, with default lookback periods of 10 and 20 bars, and adds a long signal when the shorter average crosses the longer one. A fixed-size sizer sets the trade stake. Order notifications print completed trade details, while closed-trade notifications report profit after commissions.

The script loads Yahoo Finance data for a user-selected ticker and date range, sets starting cash, runs the strategy, and can plot the data. Strategy parameters, stake, cash, and plotting options can be supplied at the command line. The document provides implementation details but no backtest output, benchmark, transaction cost analysis beyond reporting commissions, or discussion of drawdowns and parameter sensitivity. The example therefore teaches how to wire a basic crossover signal into a backtesting framework; it does not establish that the signal is profitable or robust.

Key ideas

The strategy enters long when the shorter simple moving average crosses the longer one.
The default moving average lookbacks are 10 and 20 bars.
A fixed stake controls position size, and trade notifications report execution and closed-trade profit.
The script runs on selected Yahoo Finance data and optionally plots the results.
No backtest findings or robustness analysis are included.

Tags

Equities Trend following Technical indicators Backtesting Position sizing

Full text

# sigsmacross.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
import datetime

import backtrader as bt


class SmaCross(bt.SignalStrategy):
    params = dict(sma1=10, sma2=20)

    def notify_order(self, order):
        if not order.alive():
            print('{} {} {}@{}'.format(
                bt.num2date(order.executed.dt),
                'buy' if order.isbuy() else 'sell',
                order.executed.size,
                order.executed.price)
            )

    def notify_trade(self, trade):
        if trade.isclosed:
            print('profit {}'.format(trade.pnlcomm))

    def __init__(self):
        sma1 = bt.ind.SMA(period=self.params.sma1)
        sma2 = bt.ind.SMA(period=self.params.sma2)
        crossover = bt.ind.CrossOver(sma1, sma2)
        self.signal_add(bt.SIGNAL_LONG, crossover)


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

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

    data0 = bt.feeds.YahooFinanceData(
        dataname=args.data,
        fromdate=datetime.datetime.strptime(args.fromdate, '%Y-%m-%d'),
        todate=datetime.datetime.strptime(args.todate, '%Y-%m-%d'))
    cerebro.adddata(data0)

    cerebro.addstrategy(SmaCross, **(eval('dict(' + args.strat + ')')))
    cerebro.addsizer(bt.sizers.FixedSize, stake=args.stake)

    cerebro.run()
    if args.plot:
        cerebro.plot(**(eval('dict(' + args.plot + ')')))


def parse_args(pargs=None):

    parser = argparse.ArgumentParser(
        formatter_class=argparse.ArgumentDefaultsHelpFormatter,
        description='sigsmacross')

    parser.add_argument('--data', required=False, default='YHOO',
                        help='Yahoo Ticker')

    parser.add_argument('--fromdate', required=False, default='2011-01-01',
                        help='Ending date in YYYY-MM-DD format')

    parser.add_argument('--todate', required=False, default='2012-12-31',
                        help='Ending date in YYYY-MM-DD format')

    parser.add_argument('--cash', required=False, action='store', type=float,
                        default=10000, help=('Starting cash'))

    parser.add_argument('--stake', required=False, action='store', type=int,
                        default=1, help=('Stake to apply'))

    parser.add_argument('--strat', required=False, action='store', default='',
                        help=('Arguments for the strategy'))

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

    return parser.parse_args(pargs)


if __name__ == '__main__':
    runstrat()

```

Shown in full with attribution under the source's licence. Licence: GPL-3.0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.

Backtrader Long Strategy Using a Simple Moving Average Crossover

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