FactorizationManager

class qf_lib.common.utils.factorization.manager.FactorizationManager(analysed_tms: qf_lib.containers.series.qf_series.QFSeries, regressors_df: qf_lib.containers.dataframe.qf_dataframe.QFDataFrame, frequency: qf_lib.common.enums.frequency.Frequency, factors_identifier: qf_lib.common.utils.factorization.factors_identification.factors_identifier.FactorsIdentifier, is_fit_intercept: bool = True)[source]

Bases: object

Facade class for factorization.

Parameters

  • analysed_tms – must have a set name in order to be displayed properly later on

  • regressors_df – must have a set name for each column in order to be displayed properly later on

  • frequency – frequency of every series (the same for all)

  • factors_identifier – class used for identifying significant factors for the model (picks them up from regressors_df)

  • is_fit_intercept – default True; True if the calculated model should include the intercept coefficient

Methods

extract_data_for_analysis()

Extracts data which is useful for building the model explaining the fund’s timeseries.

get_factorization_data_model()

Creates model explaining fund’s timeseries.

get_rolling_factorization_data_model()

Creates multiple models explaining fund’s timeseries (one model for each time window).
extract_data_for_analysis() → Tuple[qf_lib.containers.dataframe.qf_dataframe.QFDataFrame, qf_lib.containers.series.qf_series.QFSeries][source]

Extracts data which is useful for building the model explaining the fund’s timeseries.

Returns

Dataframe containing only those regressors which are useful for modeling fund’s timeseries and a Timeseries of fund which is preprocessed (cleaned data)

Return type

Tuple[QFDataFrame, QFSeries]

get_factorization_data_model() → qf_lib.common.utils.factorization.data_models.data_model.DataModel[source]

Creates model explaining fund’s timeseries.

get_rolling_factorization_data_model() → qf_lib.common.utils.factorization.data_models.rolling_data_model.RollingDataModel[source]

Creates multiple models explaining fund’s timeseries (one model for each time window).