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OpenBB/website/content/sdk/reference/forecast/rwd.md
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---------

Co-authored-by: jose-donato <zmcdonato@gmail.com>
Co-authored-by: jose-donato <43375532+jose-donato@users.noreply.github.com>
Co-authored-by: andrewkenreich <andrew.kenreich@gmail.com>
2023-10-30 21:01:29 +00:00

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---
title: rwd
description: This page represents the functions for Random Walk with Drift (RWD) forecasting
including the model and chart view. It provides parameters, their types, descriptions,
and default settings, and explains the purpose and results of each function.
keywords:
- rwd
- Random Walk with Drift forecasting
- forecasting model
- parameter description
- OpenBB-finance
- model object
- rwd view
- chart display
- data series
- fcast values
- predict
- start window
- forecast horizon
- export
- residuals
- forecast only
- naive
---
import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
<HeadTitle title="forecast.rwd - Reference | OpenBB SDK Docs" />
import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';
<Tabs>
<TabItem value="model" label="Model" default>
Performs Random Walk with Drift forecasting
Source Code: [[link](https://github.com/OpenBB-finance/OpenBBTerminal/tree/main/openbb_terminal/forecast/rwd_model.py#L27)]
```python
openbb.forecast.rwd(data: Union[pd.Series, pd.DataFrame], target_column: str = "close", n_predict: int = 5, start_window: float = 0.85, forecast_horizon: int = 5)
```
---
## Parameters
| Name | Type | Description | Default | Optional |
| ---- | ---- | ----------- | ------- | -------- |
| data | Union[pd.Series, np.ndarray] | Input data. | None | False |
| target_column | Optional[str]: | Target column to forecast. Defaults to "close". | close | True |
| n_predict | int | Number of days to forecast | 5 | True |
| start_window | float | Size of sliding window from start of timeseries and onwards | 0.85 | True |
| forecast_horizon | int | Number of days to forecast when backtesting and retraining historical | 5 | True |
---
## Returns
| Type | Description |
| ---- | ----------- |
| | Adjusted Data series,<br/>List of historical fcast values,<br/>List of predicted fcast values,<br/>Optional[float] precision,<br/>Fit RWD model object. |
---
</TabItem>
<TabItem value="view" label="Chart">
Display Random Walk with Drift Model
Source Code: [[link](https://github.com/OpenBB-finance/OpenBBTerminal/tree/main/openbb_terminal/forecast/rwd_view.py#L20)]
```python
openbb.forecast.rwd_chart(data: Union[pd.DataFrame, pd.Series], target_column: str = "close", dataset_name: str = "", n_predict: int = 5, start_window: float = 0.85, forecast_horizon: int = 5, export: str = "", residuals: bool = False, forecast_only: bool = False, start_date: Optional[datetime.datetime] = None, end_date: Optional[datetime.datetime] = None, naive: bool = False, export_pred_raw: bool = False, external_axes: Optional[List[axes]] = None)
```
---
## Parameters
| Name | Type | Description | Default | Optional |
| ---- | ---- | ----------- | ------- | -------- |
| data | Union[pd.Series, np.array] | Data to forecast | None | False |
| dataset_name str | None | The name of the ticker to be predicted | None | True |
| target_column | Optional[str]: | Target column to forecast. Defaults to "close". | close | True |
| n_predict | int | Number of days to forecast | 5 | True |
| start_window | float | Size of sliding window from start of timeseries and onwards | 0.85 | True |
| forecast_horizon | int | Number of days to forecast when backtesting and retraining historical | 5 | True |
| export | str | Format to export data | | True |
| residuals | bool | Whether to show residuals for the model. Defaults to False. | False | True |
| forecast_only | bool | Whether to only show dates in the forecasting range. Defaults to False. | False | True |
| start_date | Optional[datetime] | The starting date to perform analysis, data before this is trimmed. Defaults to None. | None | True |
| end_date | Optional[datetime] | The ending date to perform analysis, data after this is trimmed. Defaults to None. | None | True |
| naive | bool | Whether to show the naive baseline. This just assumes the closing price will be the same<br/>as the previous day's closing price. Defaults to False. | False | True |
| external_axes | Optional[List[plt.axes]] | External axes to plot on | None | True |
---
## Returns
This function does not return anything
---
</TabItem>
</Tabs>