mizarlabs.transformers.trading package¶
Submodules¶
mizarlabs.transformers.trading.bet_sizing module¶
- class mizarlabs.transformers.trading.bet_sizing.BetSizingBase[source]¶
Bases:
sklearn.base.BaseEstimator,sklearn.base.TransformerMixinBase class for bet sizing transformers
- class mizarlabs.transformers.trading.bet_sizing.BetSizingFromProbabilities(num_classes: int, average_active: bool = False, meta_labeling: bool = False, discretise: bool = False, step_size: Optional[float] = None, probability_column_name: str = 'prob', prediction_column_name: str = 'pred', side_column_name: str = 'side', event_end_time_column_name: str = 'event_end_time', bet_size_column_name: str = 'bet_size')[source]¶
Bases:
mizarlabs.transformers.trading.bet_sizing.BetSizingBaseCalculate the bet size using the predicted probability.
- Parameters
num_classes (int) – Number of labeled classes
average_active (bool, optional) – Whether we need to apply the average active to the bet sizing signal
meta_labeling (bool, optional) – Whether the bet sizing is calculated from a metalabeling signal
discretise (bool, optional) – Whether the output needs to be discretised
step_size (int, optional) – The step size of the discretisation
probability_column_name (str, optional) – The column name of the probabilities
prediction_column_name (str, optional) – The column name of the predictions
side_column_name (str, optional) – The column name of the side of the ‘simpler’ metalabeling model
event_end_time_column_name – The column name of the event end time
- Rtype event_end_time_column_name
str, optional
- mizarlabs.transformers.trading.bet_sizing.avg_active_signals(signals: pandas.core.frame.DataFrame, event_end_time_column_name: str = 'event_end_time', bet_size_column_name: str = 'bet_size') → pandas.core.series.Series[source]¶
Average the bet sizes of all concurrently not closed positions (e.i. no barrier has been hit yet)
- Parameters
signals – Signal from which the active average is calculated
event_end_time_column_name (str, optional) – the name of the event end time
bet_size_column_name (str, optional) – the name of the bet size column
- Rtype signals
pd.DataFrame
- Returns
The active average signal
- Return type
pd.DataFrame
- mizarlabs.transformers.trading.bet_sizing.discretise_signal(signal: pandas.core.series.Series, step_size: float) → pandas.core.series.Series[source]¶
Discretise the bet size signal based on the step size given.
- Parameters
signal (pd.Series) – Signal to discretise
step_size (float) – the step size to use for the discretisation
- Returns
Discretised signal
- Return type
pd.Series