pyfolio/timeseries.py
def downside_risk(returns, required_return=0, period=DAILY):
    """
    Determines the downside deviation below a threshold

    Parameters
    ----------
    returns : pd.Series or pd.DataFrame
        Daily returns of the strategy, noncumulative.
        - See full explanation in :func:`~pyfolio.timeseries.cum_returns`.
    required_return: float / series
        minimum acceptable return
    period : str, optional
        Defines the periodicity of the 'returns' data for purposes of
        annualizing. Can be 'monthly', 'weekly', or 'daily'.
        - Defaults to 'daily'.

    Returns
    -------
    depends on input type
    series ==> float
    DataFrame ==> np.array

        Annualized downside deviation
    """

    return ep.downside_risk(returns,
                            required_return=required_return,
                            period=period)
def downside_risk(returns, required_return=0, period=DAILY):
    """
    Determines the downside deviation below a threshold

    Parameters
    ----------
    returns : pd.Series or pd.DataFrame
        Daily returns of the strategy, noncumulative.
        - See full explanation in :func:`~pyfolio.timeseries.cum_returns`.
    required_return: float / series
        minimum acceptable return
    period : str, optional
        Defines the periodicity of the 'returns' data for purposes of
        annualizing. Can be 'monthly', 'weekly', or 'daily'.
        - Defaults to 'daily'.

    Returns
    -------
    depends on input type
    series ==> float
    DataFrame ==> np.array

        Annualized downside deviation
    """

    return ep.downside_risk(returns,
                            required_return=required_return,
                            period=period)
def downside_risk ( returns , required_return = 0 , period = DAILY ) : return ep . downside_risk ( returns , required_return = required_return , period = period )
Determines the downside deviation below a threshold

    Parameters
    ----------
    returns : pd.Series or pd.DataFrame
        Daily returns of the strategy, noncumulative.
        - See full explanation in :func:`~pyfolio.timeseries.cum_returns`.
    required_return: float / series
        minimum acceptable return
    period : str, optional
        Defines the periodicity of the 'returns' data for purposes of
        annualizing. Can be 'monthly', 'weekly', or 'daily'.
        - Defaults to 'daily'.

    Returns
    -------
    depends on input type
    series ==> float
    DataFrame ==> np.array

        Annualized downside deviation
Determines the downside deviation below a threshold