OpenBB/website/content/platform/reference/quantitative/unitroot_test.md

title, description, keywords

title	description	keywords
unitroot_test	Learn about the Unit Root Test function in Python, including the Augmented Dickey-Fuller test and the Kwiatkowski-Phillips-Schmidt-Shin test. Explore the parameters, such as data, target, fuller_reg, and kpss_reg, and understand how to interpret the unit root tests summary.	Unit Root Test Augmented Dickey-Fuller test Kwiatkowski-Phillips-Schmidt-Shin test data target fuller_reg kpss_reg Time series data unit root tests unit root tests summary

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Get Unit Root Test.

This function applies two renowned tests to assess whether your data series is stationary or if it contains a unit root, indicating it may be influenced by time-based trends or seasonality. The Augmented Dickey-Fuller (ADF) test helps identify the presence of a unit root, suggesting that the series could be non-stationary and potentially unpredictable over time. On the other hand, the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test checks for the stationarity of the series, where failing to reject the null hypothesis indicates a stable, stationary series. Together, these tests provide a comprehensive view of your data's time series properties, essential for accurate modeling and forecasting.

Examples

from openbb import obb
# Get Unit Root Test.
stock_data = obb.equity.price.historical(symbol='TSLA', start_date='2023-01-01', provider='fmp').to_df()
obb.quantitative.unitroot_test(data=stock_data, target='close')
obb.quantitative.unitroot_test(target='close', data=[{'date': '2023-01-02', 'open': 110.0, 'high': 120.0, 'low': 100.0, 'close': 115.0, 'volume': 10000.0}, {'date': '2023-01-03', 'open': 165.0, 'high': 180.0, 'low': 150.0, 'close': 172.5, 'volume': 15000.0}, {'date': '2023-01-04', 'open': 146.67, 'high': 160.0, 'low': 133.33, 'close': 153.33, 'volume': 13333.33}, {'date': '2023-01-05', 'open': 137.5, 'high': 150.0, 'low': 125.0, 'close': 143.75, 'volume': 12500.0}, {'date': '2023-01-06', 'open': 132.0, 'high': 144.0, 'low': 120.0, 'close': 138.0, 'volume': 12000.0}])

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Parameters

Name	Type	Description	Default	Optional
data	List[Data]	Time series data.		False
target	str	Target column name.		False
fuller_reg	Literal["c", "ct", "ctt", "nc", "c"]	Regression type for ADF test.		False
kpss_reg	Literal["c", "ct"]	Regression type for KPSS test.		False

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Returns

OBBject
    results : UnitRootModel
        Unit root tests summary.