Tick Data and Resampling

backtrader could already do resampling up from minute data. Accepting tick data was not a problem, by simply setting the 4 usual fields (open, high, low, close) to the tick value.

But passing the tick data to be resampled produced the same data again. As or release 1.1.11.88 this is no longer so. Now

• TimeFrame (backtrader.TimeFrame) has been extended to contain constants and names for “Ticks”, “MicroSeconds” and “Seconds”

• Resampling can manage the 3 aforementioned timeframes and sample them up.

Note

Because tick data is the lowest possible timeframe it can actually be “compressed” (n bars to 1 bar) but not be sampled up from a smallest timeframe.

The new release contains a small tickdata.csv sample added to the sources data a new sample script resample-tickdata.py to play with it.

Note

Updated the script to use the new Cerebro.resampledata method which avoids the need to manually instantiate a backtrader.DataResampler

The default execution doesn’t touch the data:

$ ./resample-tickdata.py

Producing this chart:

Compressing 3 ticks to 1:

$ ./resample-tickdata.py --timeframe ticks --compression 3

Producing this chart:

After the compression we no longer have single “ticks” but “bars”.

Now compressing to seconds and 5 bars compression:

$ ./resample-tickdata.py --timeframe seconds --compression 5

With a new chart:

And finally to minutes. The sample data contains tick data from 4 different minutes (the last tick in the file is the only tick for the 4^th minute):

$ ./resample-tickdata.py --timeframe minutes

With a 4 bars (at the top it can be seen the final price was 3069). The 4^th bar is a single point given for this minute a single tick is present in the file.

The script usage:

$ ./resample-tickdata.py --help
usage: resample-tickdata.py [-h] [--dataname DATANAME]
                            [--timeframe {ticks,microseconds,seconds,minutes,daily,weekly,monthly}]
                            [--compression COMPRESSION]

Resampling script down to tick data

optional arguments:
  -h, --help            show this help message and exit
  --dataname DATANAME   File Data to Load
  --timeframe {ticks,microseconds,seconds,minutes,daily,weekly,monthly}
                        Timeframe to resample to
  --compression COMPRESSION
                        Compress n bars into 1

And the code.

from __future__ import (absolute_import, division, print_function,
                        unicode_literals)

import argparse

import backtrader as bt
import backtrader.feeds as btfeeds


def runstrat():
    args = parse_args()

    # Create a cerebro entity
    cerebro = bt.Cerebro(stdstats=False)

    # Add a strategy
    cerebro.addstrategy(bt.Strategy)

    # Load the Data
    datapath = args.dataname or '../../datas/ticksample.csv'

    data = btfeeds.GenericCSVData(
        dataname=datapath,
        dtformat='%Y-%m-%dT%H:%M:%S.%f',
        timeframe=bt.TimeFrame.Ticks,
    )

    # Handy dictionary for the argument timeframe conversion
    tframes = dict(
        ticks=bt.TimeFrame.Ticks,
        microseconds=bt.TimeFrame.MicroSeconds,
        seconds=bt.TimeFrame.Seconds,
        minutes=bt.TimeFrame.Minutes,
        daily=bt.TimeFrame.Days,
        weekly=bt.TimeFrame.Weeks,
        monthly=bt.TimeFrame.Months)

    # Resample the data
    data = cerebro.resampledata(data,
                                timeframe=tframes[args.timeframe],
                                compression=args.compression)

    # add a writer
    cerebro.addwriter(bt.WriterFile, csv=True)

    # Run over everything
    cerebro.run()

    # Plot the result
    cerebro.plot(style='bar')


def parse_args():
    parser = argparse.ArgumentParser(
        description='Resampling script down to tick data')

    parser.add_argument('--dataname', default='', required=False,
                        help='File Data to Load')

    parser.add_argument('--timeframe', default='ticks', required=False,
                        choices=['ticks', 'microseconds', 'seconds',
                                 'minutes', 'daily', 'weekly', 'monthly'],
                        help='Timeframe to resample to')

    parser.add_argument('--compression', default=1, required=False, type=int,
                        help=('Compress n bars into 1'))

    return parser.parse_args()


if __name__ == '__main__':
    runstrat()