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. |