ExposureGenerator#
- class qf_lib.analysis.exposure_analysis.exposure_generator.ExposureGenerator(settings: Settings, data_provider: DataProvider)[source]#
Bases:
objectClass to generate exposure data based on provided regressors tickers
- Parameters:
settings (Settings) – settings of the project
data_provider (DataProvider) – DataProvider which provides data both for the tickers and regressors
- get_factor_exposure(regression_len: int = 12)[source]#
Method used to generate factor-related coefficients of regressors defined in BacktestTradingSession
- Parameters:
regression_len (int) – Length of history taken for each regression in months. It is used to determine the coefficients
- Returns:
Contains computed coefficients for all available factor regressors
- Return type:
- get_sector_exposure(regression_len: int = 12)[source]#
Method used to generate sector-related coefficients of regressors defined in BacktestTradingSession
- Parameters:
regression_len (int) – Length of history taken for each regression in months. It is used to determine the coefficients
- Returns:
Contains computed coefficients for all available sector regressors
- Return type:
- set_factor_exposure_tickers(factor_exposure_tickers: List[Ticker])[source]#
Sets factor exposure tickers
- Parameters:
factor_exposure_tickers (List[Ticker]) – List of factor exposure tickers
Sets the timeseries used to normalize exposure
- Parameters:
portfolio_eod_series (PricesSeries) – timeseries of value of the portfolio expressed in currency units
- set_positions_history(positions_history: QFDataFrame, frequency: Frequency = Frequency.MONTHLY)[source]#
Sets the positions history with defined frequency sampling
- Parameters:
positions_history (QFDataFrame) – QFDataFrame containing summary of the positions in the portfolio for each day
frequency (Frequency) – Data frequency. Default: Frequency.MONTHLY