common

enums

`expiration_date_field.ExpirationDateField`	Enumeration representing different expiration dates for futures contracts.
`frequency.Frequency`	Frequency enumeration.
`price_field.PriceField`	Represents one of the data fields that corresponds to OHLC and Volume.
`security_type.SecurityType`	Enum which denotes the type of the security, that the ticker is representing e.g.
`quandl_db_type.QuandlDBType`	An enumeration.

exceptions

`broker_exceptions.BrokerException`	Exception thrown when a Broker's operation fails.
`broker_exceptions.OrderCancellingException`	Order couldn't be cancelled (e.g.
`future_contracts_exceptions.NoValidTickerException`	Exception raised when there is no valid specific Ticker for a certain FutureTicker at a given point in time.

risk_parity_boxes

`ChangeDirection`	An enumeration.
`RiskParityBoxes`
`RiskParityBoxesFactory`	Makes timeseries for risk parity boxes.

tickers

`Ticker`	Representation of a security.
`BloombergTicker`	Representation of Bloomberg tickers.
`HaverTicker`	Haver tickers representation.
`QuandlTicker`	Representation of Quandl tickers.
`CcyTicker`	Representation of Cryptocurrency tickers.
`PortaraTicker`	Representation of Portara tickers.

timeseries_analysis

`return_attribution_analysis.ReturnAttributionAnalysis`	Class used for calculating metrics of performance attribution.
`risk_contribution_analysis.RiskContributionAnalysis`	Calculates risk contribution metrics.

utils

Classes

`confidence_interval.analytical_cone_base.AnalyticalConeBase`
`confidence_interval.analytical_cone.AnalyticalCone`
`confidence_interval.analytical_cone_oos.AnalyticalConeOOS`
`dateutils.date_format.DateFormat`	Class defining date formats (as strings).
`dateutils.timer.Timer`	Timer object which is a component in IOC.
`dateutils.timer.RealTimer`	Timer which gives the real current time.
`dateutils.timer.SettableTimer`	Timer object which doesn't give the real current time, but is "faking" it (current time can be set).
`factorization.data_models.data_model.DataModel`	Class grouping the results of factorization.
`factorization.data_models.data_model_input.DataModelInput`	Class storing an input data from which FactorizationDataModel is built.
`factorization.data_models.rolling_window_estimation.RollingWindowsEstimator`	Class for estimating parameters of rolling windows.
`factorization.data_presenters.data_presenter.DataPresenter`	Class used for presenting the data stored in the FactorizationDataModel.
`factorization.data_presenters.rolling_data_presenter.RollingDataPresenter`	Class used for presenting the data stored in the RollingFactorizationDataModel.
`factorization.factors_identification.elastic_net_factors_identifier.ElasticNetFactorsIdentifier`	Class used for identifying factors in the model with Elastic Net method (with Cross-validation).
`factorization.factors_identification.elastic_net_factors_identifier_simplified.ElasticNetFactorsIdentifierSimplified`	Class used for identifying factors in the model with Elastic Net method (with Cross-validation).
`factorization.factors_identification.stepwise_factor_identifier.StepwiseFactorsIdentifier`	Class used for identifying factors in the model with Stepwise Regression (with Forward Feature Selection).
`factorization.manager.FactorizationManager`	Facade class for factorization.
`miscellaneous.consecutive_duplicates.Method`	An enumeration.
`returns.is_return_stats.InSampleReturnStats`	Stores values of stats used to build confidence interval (Cone Chart)
`volatility.drift_independent_volatility.DriftIndependentVolatility`
`volatility.volatility_forecast.VolatilityForecast`	Creates class used for vol forecasting: describes the volatility forecast configuration as well as the input and output data (output is created and assigned by calling one of the class methods).
`volatility.volatility_manager.VolatilityManager`	VolatilityManager uses rolling window to asses the historical volatility of a series.
`data_cleaner.DataCleaner`	Cleans data which is partially incomplete, e.g.

Functions

`close_open_gap.close_open_gap.close_open_gap`	Calculates price changes during the night gap (opening price compared to closing price from the previous day).
`dateutils.common_start_and_end.get_common_start_and_end`	Finds the first and last valid dates (with a value different than NaN) for each column and then returns the latest of starting dates and the soonest ending date.
`dateutils.date_to_string.date_to_str`	Converts date object into string.
`dateutils.get_quarter.get_quarter`	Retrieves the quarter that the specified `date` is in.
`dateutils.get_values_common_dates.get_values_for_common_dates`	Gets list/tuple of series/dataframes (possibly mixed) and finds the common dates for all of them.
`dateutils.iso_to_gregorian.iso_to_gregorian`	Gregorian calendar date for the given ISO year, week and day.
`dateutils.string_to_date.str_to_date`	Converts string into date object.
`dateutils.to_days.to_days`	Converts Timedelta variable into number of days (expressed as float).
`miscellaneous.annualise_with_sqrt.annualise_with_sqrt`	Annualises samples of given frequency by multiplying each value by the square-rooted number of samples in a year for a given frequency.
`miscellaneous.average_true_range.average_true_range`	Calculates the average true range.
`miscellaneous.consecutive_duplicates.drop_consecutive_duplicates`	Removes consecutive duplicates (e.g.
`miscellaneous.function_name.get_function_name`	While called inside a function or a class method it returns the name of the function/method that called it as a string.
`miscellaneous.kelly.kelly`	Calculates the value of the Kelly Criterion (the fraction of money that should be invested) for the series of returns/prices.
`miscellaneous.kelly.kelly_binary`	Calculates the value of the Kelly Criterion (the fraction of money that should be invested) for a bet that has two possible outcomes.
`miscellaneous.periods_list.periods_list_from_bool_series`	Uses a timeseries containing boolean values to create periods of True values.
`miscellaneous.to_list_conversion.convert_to_list`	Converts a given value to list if necessary and returns information if the conversion was necessary.
`miscellaneous.volume_weighted_average_price.volume_weighted_average_price`	Aggregates prices in the prices_tms by calculating the average weighted price for each period.
`numberutils.is_finite_number.is_finite_number`	Checks if the given variable is number and if it is finite.
`ratios.calmar_ratio.calmar_ratio`	Calculates the Calmar ratio for a given timeseries of returns.
`ratios.gain_to_pain_ratio.gain_to_pain_ratio`	Calculates the gain to pain ratio for a given timeseries of returns.
`ratios.information_ratio.information_ratio`	The function calculates information ratio based on monthly returns.
`ratios.omega_ratio.omega_ratio`	Omega Ratio - The Omega Ratio is a measure of performance that doesn't assume a normal distribution of returns.
`ratios.sharpe_ratio.sharpe_ratio`	Calculates the Sharpe Ratio for a given timeseries of returns and given frequency.
`ratios.sorino_ratio.sorino_ratio`	Calculates the Sorino ratio for a given timeseries of returns.
`returns.annualise_total_return.annualise_total_return`	Calculates Annualised Rate of Return.
`returns.avg_drawdown.avg_drawdown`	Finds the average drawdown for the given timeseries of prices.
`returns.avg_drawdown_duration.avg_drawdown_duration`	Finds the average duration of a drawdown for the given timeseries of prices.
`returns.beta_and_alpha.beta_and_alpha_full_stats`	Calculates alpha and beta of the series versus the benchmark series.
`returns.cagr.cagr`	Returns the Compound Annual Growth Rate (CAGR) calculated for the given series.
`returns.convert_dataframe_frequency.convert_dataframe_frequency`	Converts each column in the dataframe to the specified frequency.
`returns.custom_returns_aggregating.aggregate_returns`	Aggregates returns using custom start dates and end dates.
`returns.cvar.cvar`	Calculates Conditional Value at Risk for a given percentage.
`returns.drawdown_tms.drawdown_tms`	Calculates the timeseries of the same dates as prices_tms, which contains the drawdown value for each date.
`returns.get_aggregate_returns.get_aggregate_returns`	Aggregates returns by week, month, or year.
`returns.index_grouping.get_grouping_for_frequency`	Returns a proper grouping function which can then be applied in the series.groupby() or dataframe.groupby().
`returns.list_longest_drawdowns.list_longest_drawdowns`	Analyses the specified series and finds the top `count` longest drawdowns.
`returns.list_of_max_drawdowns.list_of_max_drawdowns`	Finds the values of individual maximum drawdowns and the duration of each drawdown.
`returns.log_to_simple_return.log_to_simple_return`	Converts logarithmic return to corresponding simple return.
`returns.max_drawdown.max_drawdown`	Finds maximal drawdown for the given timeseries of prices.
`returns.return_distribution_helpers.get_cone_chart`	Helper function to plot simulated paths together with significant lines (like expectation)
`returns.return_distribution_helpers.generate_random_paths`	Generates random paths.
`returns.return_distribution_helpers.generate_random_log_paths`	Equivalent of generate_random_paths, but uses log Returns instead
`returns.simple_to_log_return.simple_to_log_return`	Converts simple return to the corresponding logarithmic return.
`returns.sqn.sqn`	Calculates the SQN = mean return of trade / std(returns of trades).
`returns.sqn.sqn_for100trades`	Calculates the SQN = mean return of trade / std(returns of trades) * sqrt(100)
`returns.sqn.avg_nr_of_trades_per1y`	Calculates average number of trades per year for a given data-frame of trades.
`returns.tail_events.tail_events`	Gets tail events of the benchmark and corresponding events in the examined timeseries.
`technical_analysis.utils.ta_series`	Function created to allow using TA-Lib functions with QFSeries.
`volatility.get_volatility.get_volatility`	Calculates a volatility for the given series of returns or prices.
`volatility.intraday_volatility.intraday_volatility`	Calculates annualised volatility from intraday samples of given interval.
`volatility.rolling_volatility.rolling_volatility`	Calculates the rolling volatility for the given series of returns.