Returns

systematica.preprocessing.returns

get_returns

get_returns(
    close: pandas.core.series.Series,
) ‑> pandas.core.series.Series

Compute log returns from a pandas Series of closing prices.

Log returns are calculated as the difference of the natural logarithm of consecutive prices.

Parameters:

Name	Type	Default	Description
close	pd.Series	--	A pandas Series representing asset closing prices.

Returns:

Type	Description
pd.Series	A Series of log returns.

get_returns_nb

get_returns_nb(
    close: numpy.ndarray,
) ‑> numpy.ndarray

Compute log returns using a Numba-compiled function.

This function calculates log returns by taking the difference of the natural logarithm of consecutive prices.

Parameters:

Name	Type	Default	Description
close	tp.Array2d	--	A NumPy array representing asset closing prices.

Returns:

Type	Description
tp.Array2d	A NumPy array of log returns.

get_cumulative_returns

get_cumulative_returns(
    close: numpy.ndarray,
) ‑> numpy.ndarray

Compute cumulative log returns from a pandas Series of closing prices.

Cumulative returns are obtained by computing the cumulative sum of log returns.

Parameters:

Name	Type	Default	Description
close	pd.Series	--	A pandas Series representing asset closing prices.

Returns:

Type	Description
pd.Series	A Series of cumulative log returns.

get_cumulative_returns_nb

get_cumulative_returns_nb(
    close: numpy.ndarray,
) ‑> numpy.ndarray

Compute cumulative log returns using a Numba-compiled function.

This function calculates cumulative returns by computing the cumulative sum of log returns.

Parameters:

Name	Type	Default	Description
close	tp.Array2d	--	A 2-D NumPy array representing asset closing prices.

Returns:

Type	Description
tp.Array2d	A NumPy array of cumulative log returns.