January 2020
Beginner to intermediate
432 pages
11h 24m
English
Content preview from Python for Finance Cookbook
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In Step 2, we defined a function used for running the ADF test and printing out the results. We specified autolag='AIC' in the adfuller function, so the number of considered lags is automatically selected based on the Akaike Information Criterion (AIC). Alternatively, we could select this value manually.
For the kpss function (Step 3), we specified the regression argument. A value of 'c' corresponds to the null hypothesis stating that the series is level-stationary, while 'ct' corresponds to trend-stationary (removing the trend from the series would make it level-stationary).
For all the tests and the autocorrelation plots, we selected the significance level of 5%, which is the probability of rejecting the null hypothesis ...
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