Filters Reference

SessionFilter

class backtrader.filters.SessionFilter(data)

This class can be applied to a data source as a filter and will filter out intraday bars which fall outside of the regular session times (ie: pre/post market data)

This is a “non-simple” filter and must manage the stack of the data (passed during init and __call__)

It needs no “last” method because it has nothing to deliver

SessionFilterSimple

class backtrader.filters.SessionFilterSimple(data)

This class can be applied to a data source as a filter and will filter out intraday bars which fall outside of the regular session times (ie: pre/post market data)

This is a “simple” filter and must NOT manage the stack of the data (passed during init and __call__)

It needs no “last” method because it has nothing to deliver

Bar Management will be done by the SimpleFilterWrapper class made which is added durint the DataBase.addfilter_simple call

SessionFilller

class backtrader.filters.SessionFiller(data)

Bar Filler for a Data Source inside the declared session start/end times.

The fill bars are constructed using the declared Data Source timeframe and compression (used to calculate the intervening missing times)

Params:

  • fill_price (def: None):

    If None is passed, the closing price of the previous bar will be used. To end up with a bar which for example takes time but it is not displayed in a plot ... use float(‘Nan’)

  • fill_vol (def: float(‘NaN’)):

    Value to use to fill the missing volume

  • fill_oi (def: float(‘NaN’)):

    Value to use to fill the missing Open Interest

  • skip_first_fill (def: True):

    Upon seeing the 1st valid bar do not fill from the sessionstart up to that bar

CalendarDays

class backtrader.filters.CalendarDays(data)

Bar Filler to add missing calendar days to trading days

Params:

  • fill_price (def: None):

    > 0: The given value to fill 0 or None: Use the last known closing price -1: Use the midpoint of the last bar (High-Low average)

  • fill_vol (def: float(‘NaN’)):

    Value to use to fill the missing volume

  • fill_oi (def: float(‘NaN’)):

    Value to use to fill the missing Open Interest

BarReplayer_Open

class backtrader.filters.BarReplayer_Open(data)

This filters splits a bar in two parts:

  • Open: the opening price of the bar will be used to deliver an initial price bar in which the four components (OHLC) are equal

    The volume/openinterest fields are 0 for this initial bar

  • OHLC: the original bar is delivered complete with the original volume/openinterest

The split simulates a replay without the need to use the replay filter.

DaySplitter_Close

class backtrader.filters.DaySplitter_Close(data)

Splits a daily bar in two parts simulating 2 ticks which will be used to replay the data:

  • First tick: OHLX

    The Close will be replaced by the average of Open, High and Low

    The session opening time is used for this tick

and

  • Second tick: CCCC

    The Close price will be used for the four components of the price

    The session closing time is used for this tick

The volume will be split amongst the 2 ticks using the parameters:

  • closevol (default: 0.5) The value indicate which percentage, in absolute terms from 0.0 to 1.0, has to be assigned to the closing tick. The rest will be assigned to the OHLX tick.

This filter is meant to be used together with cerebro.replaydata

HeikinAshi

class backtrader.filters.HeikinAshi(data)

The filter remodels the open, high, low, close to make HeikinAshi candlesticks

See:

Renko

class backtrader.filters.Renko(data)

Modify the data stream to draw Renko bars (or bricks)

Params:

  • hilo (default: False) Use high and low instead of close to decide if a new brick is needed

  • size (default: None) The size to consider for each brick

  • autosize (default: 20.0) If size is None, this will be used to autocalculate the size of the bricks (simply dividing the current price by the given value)

  • dynamic (default: False) If True and using autosize, the size of the bricks will be recalculated when moving to a new brick. This will of course eliminate the perfect alignment of Renko bricks.

  • align (default: 1.0) Factor use to align the price boundaries of the bricks. If the price is for example 3563.25 and align is 10.0, the resulting aligned price will be 3560. The calculation:

    • 3563.25 / 10.0 = 356.325
    • round it and remove the decimals -> 356
    • 356 * 10.0 -> 3560
See: