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39 lines
1.2 KiB
Markdown
Vendored
39 lines
1.2 KiB
Markdown
Vendored
---
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title: wma
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description: Learn how to use Weighted Moving Average (WMA) for better data analysis.
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This page provides a guide on how to implement WMA, with more weight on recent data
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and less on past data. It details the usage, parameters, defaults and offers a visual
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representation for clearer understanding.
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keywords:
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- Weighted Moving Average
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- WMA
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- Simple Moving Average
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- n_length
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- n_offset
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---
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import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
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<HeadTitle title="etf/ta/wma - Reference | OpenBB Terminal Docs" />
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A Weighted Moving Average puts more weight on recent data and less on past data. This is done by multiplying each bar’s price by a weighting factor. Because of its unique calculation, WMA will follow prices more closely than a corresponding Simple Moving Average.
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### Usage
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```python
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wma [-l N_LENGTH] [-o N_OFFSET]
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```
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---
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## Parameters
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| Name | Description | Default | Optional | Choices |
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| ---- | ----------- | ------- | -------- | ------- |
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| n_length | Window lengths. Multiple values indicated as comma separated values. | 20, 50 | True | None |
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| n_offset | offset | 0 | True | None |
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---
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