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2.1 KiB
Vendored
2.1 KiB
Vendored
title, description
| title | description |
|---|---|
| clenow | OpenBB SDK Function |
import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem';
clenow
Gets the Clenow Volatility Adjusted Momentum. this is defined as the regression coefficient on log prices
Source Code: [link]
openbb.ta.clenow(values: pd.Series, window: int = 90)
Parameters
| Name | Type | Description | Default | Optional |
|---|---|---|---|---|
| values | pd.Series | Values to perform regression for | None | False |
| window | int | Length of lookback period | 90 | True |
Returns
| Type | Description |
|---|---|
| R2 of fit to log data |
Examples
from openbb_terminal.sdk import openbb
df = openbb.stocks.load("AAPL")
openbb.ta.clenow(df["Close"])
Prints table and plots clenow momentum
Source Code: [link]
openbb.ta.clenow_chart(data: pd.Series, symbol: str = "", window: int = 90, export: str = "", external_axes: Optional[List[matplotlib.axes._axes.Axes]] = None)
Parameters
| Name | Type | Description | Default | Optional |
|---|---|---|---|---|
| data | pd.Series | Series of values | None | False |
| symbol | str | Symbol that the data corresponds to | True | |
| window | int | Length of window | 90 | True |
| export | str | Format to export data | True | |
| external_axes | Optional[List[plt.Axes]] | External axes (2 axes are expected in the list), by default None | None | True |
Returns
This function does not return anything
Examples
from openbb_terminal.sdk import openbb
df = openbb.stocks.load("AAPL")
openbb.ta.clenow_chart(df["Close"])