Pipelines

systematica.portfolio.pipelines

portfolio_pipeline

portfolio_pipeline(
    data: vectorbtpro.data.base.Data,
    s1: str,
    s2: str,
    model_func: Callable,
    signal_func: Callable,
    long_entries: float,
    long_exits: float,
    short_entries: float,
    short_exits: float,
    preprocess_func: Callable = None,
    metrics: str | List[str] = None,
    use_close: bool = True,
    size: float | numpy.ndarray = 50,
    size_type: str | numpy.ndarray = 'valuepercent100',
    allow_partial: float | numpy.ndarray = None,
    fees: float | numpy.ndarray = None,
    fixed_fees: float | numpy.ndarray = None,
    slippage: float | numpy.ndarray = None,
    min_size: float | numpy.ndarray = None,
    max_size: float | numpy.ndarray = None,
    size_granularity: float | numpy.ndarray = None,
    sl_stop: float | numpy.ndarray = None,
    tsl_stop: float | numpy.ndarray = None,
    tp_stop: float | numpy.ndarray = None,
    accumulate: bool | str | numpy.ndarray = None,
    init_cash: float | numpy.ndarray = None,
    cash_sharing: bool = True,
    group_by: bool = True,
    call_seq: str | bool = 'auto',
    fill_pos_info: bool = False,
    log: bool | numpy.ndarray = None,
    portfolio_kwargs: Dict[str, Any] = None,
    **model_params,
) ‑> vectorbtpro.portfolio.base.Portfolio | float | List[float] | pandas.core.series.Series | pandas.core.frame.DataFrame

Executes the portfolio pipeline.

Parameters:

Name	Type	Default	Description
data	vbt.Data	--	The input data.
s1	str	--	First symbol.
s2	str	--	Second symbol.
model_func	tp.Callable	--	Function to compute model output.
signal_func	tp.Callable	--	Function to generate signals.
long_entries	float	--	Long entry signals.
long_exits	float	--	Long exit signals.
short_entries	float	--	Short entry signals.
short_exits	float	--	Short exit signals.
preprocess_func	tp.Callable	None	Preprocessing function(s) to apply (default is None).
metrics	str	None	Metrics to compute (default is None).
use_close	bool	True	Whether to use ‘Close’ prices (default is True).
size	float	50	Size of each order (default is 50).
size_type	str	valuepercent100	Type of size (default is “valuepercent100”).
allow_partial	float	None	Whether to allow partial fills (default is None).
fees	float	None	Fees per order (default is None).
fixed_fees	float	None	Fixed fees per order (default is None).
slippage	float	None	Slippage per order (default is None).
min_size	float	None	Minimum size of each order (default is None).
max_size	float	None	Maximum size of each order (default is None).
size_granularity	float	None	Granularity of size (default is None).
sl_stop	float	None	Stop-loss level (default is None).
tsl_stop	float	None	Trailing stop-loss level (default is None).
tp_stop	float	None	Take-profit level (default is None).
accumulate	bool	None	Whether to accumulate orders (default is None).
init_cash	float	None	Initial cash (default is None).
cash_sharing	bool	True	Whether to share cash between assets (default is True).
group_by	bool	True	Whether to group by symbol (default is True).
call_seq	bool	auto	Call sequence (default is “auto”).
fill_pos_info	bool	False	Whether to fill position info (default is False).
log	bool	None	Whether to log orders (default is None).
portfolio_kwargs	tp.Kwargs	None	Additional keyword arguments for the portfolio simulation.
model_params	tp.Kwargs	--	Additional parameters for model_func.

Returns:

Type	Description
vbt.Portfolio or float or tp.List[float] or tp.SeriesFrame	The result of the portfolio simulation.

portfolio_pipeline_nb

portfolio_pipeline_nb(
    open: numpy.ndarray,
    high: numpy.ndarray,
    low: numpy.ndarray,
    close: numpy.ndarray,
    preprocess_func_nb: Callable,
    model_func_nb: Callable,
    metrics_func_nb: Callable,
    signal_func_nb: Callable,
    long_entries: float = -1.0,
    long_exits: float = 0.0,
    short_entries: float = 1.0,
    short_exits: float = 0.0,
    size: int | float = 50,
    sl_stop: float = nan,
    tsl_stop: float = nan,
    tp_stop: float = nan,
) ‑> Any

Executes the portfolio pipeline.

Parameters:

Name	Type	Default	Description
open	tp.Array1d	--	Open prices.
high	tp.Array1d	--	High prices.
low	tp.Array1d	--	Low prices.
close	tp.Array1d	--	Close prices.
model_func_nb	tp.Callable	--	Function to compute model output.
metrics_func_nb	tp.Callable	--	Function to compute metrics.
signal_func_nb	tp.Callable	--	Function to generate signals.
long_entries	float	-1.0	Long entry signals. Defaults to -1.0.
long_exits	float	0.0	Long exit signals. Defaults to 0.0.
short_entries	float	1.0	Short entry signals. Defaults to 1.0.
short_exits	float	0.0	Short exit signals. Defaults to 0.0.
preprocess_func_nb	tp.Callable	None	Preprocessing function(s) to apply. Defaults to None.
size	int	--	or float, default 50 Size of each order. Defaults to 50.
sl_stop	float	np.nan	Stop-loss level. Defaults to np.nan.
tsl_stop	float	np.nan	Trailing stop-loss level. Defaults to np.nan.
tp_stop	float	np.nan	Take-profit level. Defaults to np.nan.

Returns:

Type	Description
tp.Any	The result of the portfolio simulation.