quantpylib.hft.utils

exponential_weights(arr, unique_values=False, normalize=False)

Generates exponential weights for an array.

Parameters:

Name	Type	Description	Default
arr	ndarray or list	The input array.	required
unique_values	bool	If True, weights are generated based on the number of unique values in the array. Duplicate values share the same weight.	False
normalize	bool	If True, the weights are normalized to sum to 1.	False

Returns:

Type	Description
	np.ndarray: An array of exponential weights.

rolling_ema(arr, n)

Calculate the rolling Exponential Moving Average (EMA).

Parameters:

Name	Type	Description	Default
arr	ndarray	The input array.	required
n	int	The size of the rolling window.	required

Returns:

Type	Description
	np.ndarray: An array of rolling EMAs.

rolling_window(a, window)

Create a rolling window view of the array a.

Parameters:

Name	Type	Description	Default
a	ndarray	The input array.	required
window	int	The size of the rolling window.	required

Returns:

Type	Description
	np.ndarray: A view of the input array with the specified rolling window.

rolling_zscore(arr, n)

Calculate the rolling Z-score.

Parameters:

Name	Type	Description	Default
arr	ndarray	The input array.	required
n	int	The size of the rolling window.	required

Returns:

Type	Description
	np.ndarray: An array of rolling Z-scores.

simple_weights(arr, normalize=False)

Generates simple weights for an array.

Parameters:

Name	Type	Description	Default
arr	ndarray or list	The input array.	required
normalize	bool	If True, the weights are normalized to sum to 1.	False

Returns:

Type	Description
	np.ndarray: An array of simple weights.