Buy-the-Dip Rule and Holding Period

Code backtrader

Summary

This script implements a long-only buy-the-dip strategy for a single price series. It measures declines using one of several definitions: close versus prior close, close versus open, close versus high, or low versus high. When the selected measure crosses a configurable negative threshold, it targets a chosen fraction of portfolio value and schedules an exit after a fixed number of bars. The default setup uses the daily high-to-low decline, a one-percent trigger, a two-bar holding period, and a full-value target.

The example runs through Backtrader with Yahoo Finance data or a local CSV, configurable dates, broker settings, leverage, and commissions. An observer tracks portfolio value, a leveraged value series, and the cumulative performance of the underlying asset. The document supplies implementation details but no backtest results or performance comparison. It therefore explains how to reproduce and configure the rule, not whether it is profitable; outcomes will depend on data, execution assumptions, costs, and parameter choices.

Key ideas

The strategy enters a long position when a selected price-decline measure reaches a negative threshold.
The decline can be measured from the prior close, the session open, the high, or between the session high and low.
After entry, the strategy closes the position after a configurable number of bars.
The position target, data source, broker settings, leverage, and commissions are configurable.

Tags

Mean reversion Backtesting Position sizing Equities

Full text

# btfd.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)

# References:
#  - https://www.reddit.com/r/algotrading/comments/5jez2b/can_anyone_replicate_this_strategy/
#  - http://dark-bid.com/BTFD-only-strategy-that-matters.html

import argparse
import datetime

import backtrader as bt


class ValueUnlever(bt.observers.Value):
    '''Extension of regular Value observer to add leveraged view'''
    lines = ('value_lever', 'asset')
    params = (('assetstart', 100000.0), ('lever', True),)

    def next(self):
        super(ValueUnlever, self).next()
        if self.p.lever:
            self.lines.value_lever[0] = self._owner.broker._valuelever

        if len(self) == 1:
            self.lines.asset[0] = self.p.assetstart
        else:
            change = self.data[0] / self.data[-1]
            self.lines.asset[0] = change * self.lines.asset[-1]


class St(bt.Strategy):
    params = (
        ('fall', -0.01),
        ('hold', 2),
        ('approach', 'highlow'),
        ('target', 1.0),
        ('prorder', False),
        ('prtrade', False),
        ('prdata', False),
    )

    def __init__(self):
        if self.p.approach == 'closeclose':
            self.pctdown = self.data.close / self.data.close(-1) - 1.0
        elif self.p.approach == 'openclose':
            self.pctdown = self.data.close / self.data.open - 1.0
        elif self.p.approach == 'highclose':
            self.pctdown = self.data.close / self.data.high - 1.0
        elif self.p.approach == 'highlow':
            self.pctdown = self.data.low / self.data.high - 1.0

    def next(self):
        if self.position:
            if len(self) == self.barexit:
                self.close()
                if self.p.prdata:
                    print(','.join(str(x) for x in
                                   ['DATA', 'CLOSE',
                                    self.data.datetime.date().isoformat(),
                                    self.data.close[0],
                                    float('NaN')]))
        else:
            if self.pctdown <= self.p.fall:
                self.order_target_percent(target=self.p.target)
                self.barexit = len(self) + self.p.hold

                if self.p.prdata:
                    print(','.join(str(x) for x in
                                   ['DATA', 'OPEN',
                                    self.data.datetime.date().isoformat(),
                                    self.data.close[0],
                                    self.pctdown[0]]))

    def start(self):
        if self.p.prtrade:
            print(','.join(
                ['TRADE', 'Status', 'Date', 'Value', 'PnL', 'Commission']))
        if self.p.prorder:
            print(','.join(
                ['ORDER', 'Type', 'Date', 'Price', 'Size', 'Commission']))
        if self.p.prdata:
            print(','.join(['DATA', 'Action', 'Date', 'Price', 'PctDown']))

    def notify_order(self, order):
        if order.status in [order.Margin, order.Rejected, order.Canceled]:
            print('ORDER FAILED with status:', order.getstatusname())
        elif order.status == order.Completed:
            if self.p.prorder:
                print(','.join(map(str, [
                    'ORDER', 'BUY' * order.isbuy() or 'SELL',
                    self.data.num2date(order.executed.dt).date().isoformat(),
                    order.executed.price,
                    order.executed.size,
                    order.executed.comm,
                ]
                )))

    def notify_trade(self, trade):
        if not self.p.prtrade:
            return

        if trade.isclosed:
            print(','.join(map(str, [
                'TRADE', 'CLOSE',
                self.data.num2date(trade.dtclose).date().isoformat(),
                trade.value,
                trade.pnl,
                trade.commission,
            ]
            )))
        elif trade.justopened:
            print(','.join(map(str, [
                'TRADE', 'OPEN',
                self.data.num2date(trade.dtopen).date().isoformat(),
                trade.value,
                trade.pnl,
                trade.commission,
            ]
            )))


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

    cerebro = bt.Cerebro()

    # Data feed kwargs
    kwargs = dict()

    # Parse from/to-date
    dtfmt, tmfmt = '%Y-%m-%d', 'T%H:%M:%S'
    for a, d in ((getattr(args, x), x) for x in ['fromdate', 'todate']):
        kwargs[d] = datetime.datetime.strptime(a, dtfmt + tmfmt * ('T' in a))

    if not args.offline:
        YahooData = bt.feeds.YahooFinanceData
    else:
        YahooData = bt.feeds.YahooFinanceCSVData

    # Data feed - no plot - observer will do the job
    data = YahooData(dataname=args.data, plot=False, **kwargs)
    cerebro.adddata(data)

    # Broker
    cerebro.broker = bt.brokers.BackBroker(**eval('dict(' + args.broker + ')'))

    # Add a commission
    cerebro.broker.setcommission(**eval('dict(' + args.comminfo + ')'))

    # Strategy
    cerebro.addstrategy(St, **eval('dict(' + args.strat + ')'))

    # Add specific observer
    cerebro.addobserver(ValueUnlever, **eval('dict(' + args.valobserver + ')'))

    # Execute
    cerebro.run(**eval('dict(' + args.cerebro + ')'))

    if args.plot:  # Plot if requested to
        cerebro.plot(**eval('dict(' + args.plot + ')'))


def parse_args(pargs=None):
    parser = argparse.ArgumentParser(
        formatter_class=argparse.ArgumentDefaultsHelpFormatter,
        description=(' - '.join([
            'BTFD',
            'http://dark-bid.com/BTFD-only-strategy-that-matters.html',
            ('https://www.reddit.com/r/algotrading/comments/5jez2b/'
             'can_anyone_replicate_this_strategy/')]))
        )

    parser.add_argument('--offline', required=False, action='store_true',
                        help='Use offline file with ticker name')

    parser.add_argument('--data', required=False, default='^GSPC',
                        metavar='TICKER', help='Yahoo ticker to download')

    parser.add_argument('--fromdate', required=False, default='1990-01-01',
                        metavar='YYYY-MM-DD[THH:MM:SS]',
                        help='Starting date[time]')

    parser.add_argument('--todate', required=False, default='2016-10-01',
                        metavar='YYYY-MM-DD[THH:MM:SS]',
                        help='Ending date[time]')

    parser.add_argument('--cerebro', required=False, default='stdstats=False',
                        metavar='kwargs', help='kwargs in key=value format')

    parser.add_argument('--broker', required=False,
                        default='cash=100000.0, coc=True',
                        metavar='kwargs', help='kwargs in key=value format')

    parser.add_argument('--valobserver', required=False,
                        default='assetstart=100000.0',
                        metavar='kwargs', help='kwargs in key=value format')

    parser.add_argument('--strat', required=False,
                        default='approach="highlow"',
                        metavar='kwargs', help='kwargs in key=value format')

    parser.add_argument('--comminfo', required=False, default='leverage=2.0',
                        metavar='kwargs', help='kwargs in key=value format')

    parser.add_argument('--plot', required=False, default='',
                        nargs='?', const='volume=False',
                        metavar='kwargs', help='kwargs in key=value format')

    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.

A Buy-the-Dip Rule Based on Price Declines and Fixed Holding Periods

Summary

Key ideas

Tags