Library "FunctionADF"
Augmented Dickey-Fuller test (ADF), The ADF test is a statistical method used to assess whether a time series is stationary – meaning its statistical properties (like mean and variance) do not change over time. A time series with a unit root is considered non-stationary and often exhibits non-mean-reverting behavior, which is a key concept in technical analysis.
Reference:
-
- rtmath.net/assets/docs/finmath/html/93a7b7b9-e3c3-4f19-8a57-49c3938d607d.htm
- en.wikipedia.org/wiki/Augmented_Dickey–Fuller_test
adftest(data, n_lag, conf)
: Augmented Dickey-Fuller test for stationarity.
Parameters:
data (array<float>): Data series.
n_lag (int): Maximum lag.
conf (string): Confidence Probability level used to test for critical value, (`90%`, `95%`, `99%`).
Returns: `adf` The test statistic. \
`crit` Critical value for the test statistic at the 10 % levels. \
`nobs` Number of observations used for the ADF regression and calculation of the critical values.
Augmented Dickey-Fuller test (ADF), The ADF test is a statistical method used to assess whether a time series is stationary – meaning its statistical properties (like mean and variance) do not change over time. A time series with a unit root is considered non-stationary and often exhibits non-mean-reverting behavior, which is a key concept in technical analysis.
Reference:
-

- rtmath.net/assets/docs/finmath/html/93a7b7b9-e3c3-4f19-8a57-49c3938d607d.htm
- en.wikipedia.org/wiki/Augmented_Dickey–Fuller_test
adftest(data, n_lag, conf)
: Augmented Dickey-Fuller test for stationarity.
Parameters:
data (array<float>): Data series.
n_lag (int): Maximum lag.
conf (string): Confidence Probability level used to test for critical value, (`90%`, `95%`, `99%`).
Returns: `adf` The test statistic. \
`crit` Critical value for the test statistic at the 10 % levels. \
`nobs` Number of observations used for the ADF regression and calculation of the critical values.
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Pine脚本库
本着真正的TradingView精神,作者将此Pine代码发布为开源库,以便我们社区的其他Pine程序员可以重复使用它。向作者致敬!您可以私密或在其他开源出版物中使用此库,但在出版物中重复使用此代码受网站规则约束。
免责声明
这些信息和出版物并不意味着也不构成TradingView提供或认可的金融、投资、交易或其它类型的建议或背书。请在使用条款阅读更多信息。