FactorizationManager
- class qf_lib.common.utils.factorization.manager.FactorizationManager(analysed_tms: QFSeries, regressors_df: QFDataFrame, frequency: Frequency, 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:
Extracts data which is useful for building the model explaining the fund's timeseries.
Creates model explaining fund's timeseries.
Creates multiple models explaining fund's timeseries (one model for each time window).
- extract_data_for_analysis() Tuple[QFDataFrame, 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]